Search results for: multiple conditions diagnosis

Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: Young Hee Geum

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In this paper,we develop the complex dynamics of a family of optimal fourth-order multiple-root solvers and plot their basins of attraction. Mobius conjugacy maps and extraneous fixed points applied to a prototype quadratic polynomial raised to the power of the known integer multiplicity m are investigated. A 300 x 300 uniform grid centered at the origin covering 3 x 3 square region is chosen to visualize the initial values on each basin of attraction in accordance with a coloring scheme based on their dynamical behavior. The illustrative basins of attractions applied to various test polynomials and the corresponding statistical data for convergence are shown to confirm the theoretical convergence.

Keywords: basin of attraction, conjugacy, fourth-order, multiple-root finder

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Authors: Anisa Suraya Ab Razak, Izza Hayat

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Introduction: The diagnosis and management of severe hyponatremia in neuropsychiatric patients present a significant challenge to physicians. Several factors contribute, including diagnostic shadowing and attributing abnormal behavior to intellectual disability or psychiatric conditions. Hyponatraemia is the commonest electrolyte abnormality in the inpatient population, ranging from mild/asymptomatic, moderate to severe levels with life-threatening symptoms such as seizures, coma and death. There are several documented fatal case reports in the literature of severe hyponatremia secondary to psychogenic polydipsia, often diagnosed only in autopsy. This paper presents a case study of acute severe hyponatremia in a neuropsychiatric patient with early diagnosis and admission to intensive care. Case study: A 21-year old Caucasian male with known epilepsy and learning disability was admitted from residential living with generalized tonic-clonic self-terminating seizures after refusing medications for several weeks. Evidence of superficial head injury was detected on physical examination. His laboratory data demonstrated mild hyponatremia (125 mmol/L). Computed tomography imaging of his brain demonstrated no acute bleed or space-occupying lesion. He exhibited abnormal behavior - restlessness, drinking water from bathroom taps, inability to engage, paranoia, and hypersexuality. No collateral history was available to establish his baseline behavior. He was loaded with intravenous sodium valproate and leveritircaetam. Three hours later, he developed vomiting and a generalized tonic-clonic seizure lasting forty seconds. He remained drowsy for several hours and regained minimal recovery of consciousness. A repeat set of blood tests demonstrated profound hyponatremia (117 mmol/L). Outcomes: He was referred to intensive care for peripheral intravenous infusion of 2.7% sodium chloride solution with two-hourly laboratory monitoring of sodium concentration. Laboratory monitoring identified dangerously rapid correction of serum sodium concentration, and hypertonic saline was switched to a 5% dextrose solution to reduce the risk of acute large-volume fluid shifts from the cerebral intracellular compartment to the extracellular compartment. He underwent urethral catheterization and produced 8 liters of urine over 24 hours. Serum sodium concentration remained stable after 24 hours of correction fluids. His GCS recovered to baseline after 48 hours with improvement in behavior -he engaged with healthcare professionals, understood the importance of taking medications, admitted to illicit drug use and drinking massive amounts of water. He was transferred from high-dependency care to ward level and was initiated on multiple trials of anti-epileptics before achieving seizure-free days two weeks after resolution of acute hyponatremia. Conclusion: Psychogenic polydipsia is often found in young patients with intellectual disability or psychiatric disorders. Patients drink large volumes of water daily ranging from ten to forty liters, resulting in acute severe hyponatremia with mortality rates as high as 20%. Poor outcomes are due to challenges faced by physicians in making an early diagnosis and treating acute hyponatremia safely. A low index of suspicion of water intoxication is required in this population, including patients with known epilepsy. Monitoring urine output proved to be clinically effective in aiding diagnosis. Early referral and admission to intensive care should be considered for safe correction of sodium concentration while minimizing risk of fatal complications e.g. central pontine myelinolysis.

Keywords: epilepsy, psychogenic polydipsia, seizure, severe hyponatremia

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Authors: Anthony S. Machi, Joseph Minardi

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We present a case report of left atrial myxoma diagnosed by bedside transesophageal (TEE) ultrasound. Left atrial myxoma is the most common benign cardiac tumor and can obstruct blood flow and cause valvular insufficiency. Common symptoms consist of dyspnea, pulmonary edema and other features of left heart failure in addition to thrombus release in the form of tumor fragments. The availability of bedside ultrasound equipment is essential for the quick diagnosis and treatment of various emergency conditions including cardiac neoplasms. A 48-year-old Caucasian female with a four-year history of an untreated renal mass and anemia presented to the ED with two months of sharp, intermittent, bilateral flank pain radiating into the abdomen. She also reported intermittent vomiting and constipation along with generalized body aches, night sweats, and 100-pound weight loss over last year. She had a CT in 2013 showing a 3 cm left renal mass and a second CT in April 2016 showing a 3.8 cm left renal mass along with a past medical history of diverticulosis, chronic bronchitis, dyspnea on exertion, uncontrolled hypertension, and hyperlipidemia. Her maternal family history is positive for breast cancer, hypertension, and Type II Diabetes. Her paternal family history is positive for stroke. She was a current everyday smoker with an 11 pack/year history. Alcohol and drug use were denied. Physical exam was notable for a Grade II/IV systolic murmur at the right upper sternal border, dyspnea on exertion without angina, and a tender left lower quadrant. Her vitals and labs were notable for a blood pressure of 144/96, heart rate of 96 beats per minute, pulse oximetry of 96%, hemoglobin of 7.6 g/dL, hypokalemia, hypochloremia, and multiple other abnormalities. Physicians ordered a CT to evaluate her flank pain which revealed a 7.2 x 8.9 x 10.5 cm mixed cystic/solid mass in the lower pole of the left kidney and a filling defect in the left atrium. Bedside TEE was ordered to follow up on the filling defect. TEE reported an ejection fraction of 60-65% and visualized a mobile 6 x 3 cm mass in the left atrium attached to the interatrial septum extending into the mitral valve. Cardiothoracic Surgery and Urology were consulted and confirmed a diagnosis of left atrial myxoma and clear cell renal cell carcinoma. The patient returned a week later due to worsening nausea and vomiting and underwent emergent nephrectomy, lymph node dissection, and colostomy due to a necrotic colon. Her condition declined over the next four months due to lung and brain metastases, infections, and other complications until she passed away.

Keywords: bedside ultrasound, echocardiography, emergency medicine, left atrial myxoma

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Authors: Pranav Ajmera, Amit Kharat, Tanveer Gupte, Richa Pant, Viraj Kulkarni, Vinay Duddalwar, Purnachandra Lamghare

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The cardiothoracic ratio (CTR) is the ratio of the diameter of the heart to the diameter of the thorax. An abnormal CTR, that is, a value greater than 0.55, is often an indicator of an underlying pathological condition. The accurate prediction of an abnormal CTR from chest X-rays (CXRs) aids in the early diagnosis of clinical conditions. We propose a deep learning-based model for automatic CTR calculation that can assist the radiologist with the diagnosis of cardiomegaly and optimize the radiology flow. The study population included 1012 posteroanterior (PA) CXRs from a single institution. The Attention U-Net deep learning (DL) architecture was used for the automatic calculation of CTR. A CTR of 0.55 was used as a cut-off to categorize the condition as cardiomegaly present or absent. An observer performance test was conducted to assess the radiologist's performance in diagnosing cardiomegaly with and without artificial intelligence (AI) assistance. The Attention U-Net model was highly specific in calculating the CTR. The model exhibited a sensitivity of 0.80 [95% CI: 0.75, 0.85], precision of 0.99 [95% CI: 0.98, 1], and a F1 score of 0.88 [95% CI: 0.85, 0.91]. During the analysis, we observed that 51 out of 1012 samples were misclassified by the model when compared to annotations made by the expert radiologist. We further observed that the sensitivity of the reviewing radiologist in identifying cardiomegaly increased from 40.50% to 88.4% when aided by the AI-generated CTR. Our segmentation-based AI model demonstrated high specificity and sensitivity for CTR calculation. The performance of the radiologist on the observer performance test improved significantly with AI assistance. A DL-based segmentation model for rapid quantification of CTR can therefore have significant potential to be used in clinical workflows.

Keywords: cardiomegaly, deep learning, chest radiograph, artificial intelligence, cardiothoracic ratio

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Authors: S. Fazi, B. Behdani

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The inland transportation of maritime containers entails the use of different modalities whose capacity is typically booked in advance. Containers may miss their scheduled departure time at a terminal for several reasons, such as delays, change of transport modes, multiple bookings pending. In those cases, it may be difficult for transport service providers to find last minute containers to fill the vacant capacity. Similarly to other industries, overbooking could potentially limit these drawbacks at the cost of a lower service level in case of actual excess of capacity in overbooked rides. However, the presence of multiple modalities may provide the required flexibility in rescheduling and limit the dissatisfaction of the shippers in case of containers in overbooking. This flexibility is known with the term 'synchromodality'. In this paper, we evaluate via discrete event simulation the application of overbooking. Results show that in certain conditions overbooking can significantly increase profit and utilization of high-capacity means of transport, such as barges and trains. On the other hand, in case of high penalty costs and limited no-show, overbooking may lead to an excessive use of expensive trucks.

Keywords: discrete event simulation, flexibility, inland shipping, multimodality, overbooking

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Authors: Muhsin Kizhisseri, Jorg Schluter, Saleh Gharie

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Atherosclerosis is the main reason of stroke, which is one of the deadliest diseases in the world. The carotid artery in the brain is the prominent location for atherosclerotic progression, which hinders the blood flow into the brain. The inclusion of computational fluid dynamics (CFD) into the diagnosis cycle to understand the hemodynamics of the patient-specific carotid artery can give insights into stroke prediction. Realistic outlet boundary conditions are an inevitable part of the numerical simulations, which is one of the major factors in determining the accuracy of the CFD results. The Windkessel model-based outlet boundary conditions can give more realistic characteristics of the distal vascular branches of the carotid artery, such as the resistance to the blood flow and compliance of the distal arterial walls. This study aims to find the most influential distal branches of the carotid artery by using the Windkessel model parameters in the outlet boundary conditions. The parametric study approach to Windkessel model parameters can include the geometrical features of the distal branches, such as radius and length. The incorporation of the variations of the geometrical features of the major distal branches such as the middle cerebral artery, anterior cerebral artery, and ophthalmic artery through the Windkessel model can aid in identifying the most influential distal branch in the carotid artery. The results from this study can help physicians and stroke neurologists to have a more detailed and accurate judgment of the patient's condition.

Keywords: stroke, carotid artery, computational fluid dynamics, patient-specific, Windkessel model, distal vascular branches

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Authors: Dona Pamoda W. Jayatunga, Veer Bala Gupta, Eugene Hone, Ralph N. Martins

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Being a neurodegenerative disorder, Alzheimer’s disease (AD) affects a majority of the elderly demented worldwide. The key risk factors for AD are age, metabolic syndrome, allele status of APOE gene, head injuries and lifestyle. The progressive nature of AD is characterized by symptoms of multiple cognitive deficits exacerbated over time, leading to death within a decade from clinical diagnosis. However, it is revealed that AD originates via a prodromal phase that spans from one to few decades before symptoms first manifest. The key pathological hallmarks of AD brains are deposition of amyloid beta (Aβ) plaques and neurofibrillary tangles (NFT). However, the yet unknown etiology of the disease fails to distinguish mitochondrial dysfunction between a cause or an outcome. The absence of early diagnosis tools and definite therapies for AD have permitted recruits of nutraceutical-based approaches aimed at reducing the risk of AD by modulating lifestyle or be used as preventive tools during AD prodromal state before widespread neurodegeneration begins. The objective of the present study was to investigate beneficial effects of luteolin, a plant-based flavone compound, against AD. The neuroprotective effects of luteolin on amyloid beta (Aβ) (1-42)-induced neurotoxicity was measured using cultured human neuroblastoma BE(2)-M17 cells. After exposure to 20μM Aβ (1-42) for 48 h, the neuroblastoma cells exhibited marked apoptotic death. Co-treatment of 20μM Aβ (1-42) with luteolin (0.5-5μM) significantly protected the cells against Aβ (1-42)-induced toxicity, as assessed by the MTS [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2(4sulfophenyl)-2H-tetrazolium, inner salt; MTS] reduction assay and the lactate dehydrogenase (LDH) cell death assay. The results suggest that luteolin prevents Aβ (1-42)-induced apoptotic neuronal death. However, further studies are underway to determine its protective mechanisms in AD including the activity against tau hyperphosphorylation and mitochondrial dysfunction.

Keywords: Aβ (1-42)-induced toxicity, Alzheimer’s disease, luteolin, neuroblastoma cells

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Authors: Bummo Ahn

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Palpation is widely used to measure soft tissue firmness or stiffness in the living condition in order to apply detection, diagnosis, and treatment of tumors, scar tissue, abnormal muscle tone, or muscle spasticity. Since these methods are subjective and depend on the proficiency level, it is concluded that there are other diagnoses depending on the condition of the experts and the results are not objective. The mechanical property obtained by using the elasticity of the tissue is important to calculate a predictive variable for monitoring abnormal tissues. If the mechanical load such as reaction force on the foot increases in the same region under the same conditions, the mechanical property of the tissue is changed. Therefore, objective diagnosis is possible not only for experts but also for patients using this quantitative information. Furthermore, the portable system also allows non-experts to easily diagnose at home, not in hospitals or institutions. In this paper, we introduce a portable palpation system that can be used to measure the mechanical properties of human tissue, which can be applied to monitor diabetic foot ulceration patients with measuring the mechanical property change of foot tissue. The system was designed to be smaller and portable in comparison with the conventional palpation systems. It is consists of the probe, the force sensor, linear actuator, micro control unit, the display module, battery, and housing. Using this system, we performed validation experiments by applying different palpations (3 and 5 mm) to soft tissue (silicone rubber) and measured reaction forces. In addition, we estimated the elastic moduli of the soft tissue against different palpations and compare the estimated elastic moduli that show similar value even if the palpation depths are different.

Keywords: palpation probe, portable, diabetic foot ulceration, monitoring, mechanical property

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Authors: Mohamad Ahrari, Kayvan Sadri, Mahmoud Reza Jafari

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PEGylated liposomes have a smaller volume of distribution and decreased clearance, consequently, due to their more prolonged presence in bloodstream and maintaining their stability during this period, these liposomes can be applied for imaging tumoral sites. The purpose of this study is to develop an appropriate radiopharmaceutical agent in long-term imaging for improved diagnosis and evaluation of tumors. In this study, liposomal formulations encapsulating albumin is synthesized by solvent evaporation method along with homogenization, and their characteristics were assessed. Then these liposomes labeled by Philips method and the rate of stability of labeled liposomes in serum, and ultimately the rate of biodistribution and gamma scintigraphy in C26-colon carcinoma tumor-bearing mice, were studied. The result of the study of liposomal characteristics displayed that capable of accumulating in tumor sites based of EPR phenomenon. these liposomes also have high stability for maintaining encapsulated albumin in a long time. In the study of biodistribution of these liposomes in mice, they accumulated more in the kidney, liver, spleen, and tumor sites, which, even after clearing formulations in the bloodstream, they existed in high levels in these organs up to 96 hours. In gamma scintigraphy also, organs with high activity accumulation from early hours up to 96 hours were visible in the form of hot spots. concluded that PEGylated liposomal formulation encapsulating albumin can be labeled with In-Oxine, and obtained stabilized formulation for long-term imaging, that have more favorable conditions for the evaluation of tumors and it will cause early diagnosis of tumors.

Keywords: nano liposome, 111In-oxine, imaging, biodistribution, tumor

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Authors: Ghazala Hcini, Imen Jdey, Hela Ltifi

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Malaria disease should be considered and handled as a potential restorative catastrophe. One of the most challenging tasks in the field of microscopy image processing is due to differences in test design and vulnerability of cell classifications. In this article, we focused on applying deep learning to classify patients by identifying images of infected and uninfected cells. We performed multiple forms, counting a classification approach using the Hue, Saturation, Value (HSV) color space. HSV is used since of its superior ability to speak to image brightness; at long last, for classification, a convolutional neural network (CNN) architecture is created. Clusters of focus were used to deliver the classification. The highlights got to be forbidden, and a few more clamor sorts are included in the information. The suggested method has a precision of 99.79%, a recall value of 99.55%, and provides 99.96% accuracy.

Keywords: deep learning, convolutional neural network, image classification, color transformation, HSV color, malaria diagnosis, malaria cells images

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Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

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Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: artificial immune system, breast cancer diagnosis, Euclidean function, Gaussian function

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Authors: S. Mohd Afzal, R. O'Connell

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Kaposi's sarcoma (KS) is the most common HIV-related cancer, and ocular manifestations constitute at least 25% of all KS cases. However, ocular presentations often occur in the context of systemic KS, and isolated lesions are rare. We report a unique case of ocular KS masquerading as subconjunctival haemorrhage, and only developing systemic manifestations after initiation of HIV treatment. Case: A 49-year old man with previous hypertensive stroke and newly diagnosed HIV infection presented with an acutely red left eye following repeated bouts of coughing. Given the convincing history of poorly controlled hypertension and cough, a diagnosis of subconjunctival haemorrhage was made. Over the next week, his ocular lesion began to improve and he subsequently started anti-retroviral therapy. Prior to receiving anti-retroviral therapy, his CD4+ lymphocyte count was 194 cells/mm3 with HIV viral load greater than 1 million/ml. This rapidly improved to a viral load of 150 copies/ml within 2 weeks of starting treatment. However, a few days after starting HIV treatment, his ocular lesion recurred. Ophthalmic examination was otherwise normal. He also developed widespread lymphadenopathy and multiple dark lesions on his torso. Histology and virology confirmed KS, systemically triggered by Immune Reconstitution Syndrome (KS-IRIS). The patient has since undergone chemotherapy successfully. Discussion: Kaposi's sarcoma is an atypical tumour caused by human herpesvirus 8 (HHV-8), also known as Kaposi’s sarcoma-associated herpesvirus (KSHV). In immunosuppressed patients, KSHV can also cause lymphoproliferative disorders such as primary effusion lymphoma and Castleman's disease (in our patient’s case, this was excluded through histological analysis of lymph nodes). KSHV is one of the seven currently known human oncoviruses, and its pathogenesis is poorly understood. Up to 13% of patients with HIV-related KS experience worsening of the disease after starting anti-retroviral treatment, due to a sudden increase in CD4 cell counts. Histology remains the diagnostic gold standard. Current British HIV Association (BHIVA) guidelines recommend treatment using anti-retroviral drugs, with either intralesional vinblastine for local disease or systemic chemotherapy for disseminated KS. Conclusion: This case is unique as ocular KS as initial presentation is rare and our patient's diagnosis was only made after systemic lesions were triggered by immune reconstitution. KS should be considered as an important differential diagnosis for red eyes in all patients at risk of acquiring HIV infection.

Keywords: human herpesvirus 8, human immunodeficiency virus, immune reconstitution syndrome, Kaposi’s sarcoma, Kaposi’s sarcoma-associated herpesvirus

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Authors: Ayesha S. Rahman, Khaled Haddad, Ataur Rahman

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At-site flood frequency analysis is used to estimate flood quantiles when at-site record length is reasonably long. In Australia, FLIKE software has been introduced for at-site flood frequency analysis. The advantage of FLIKE is that, for a given application, the user can compare a number of most commonly adopted probability distributions and parameter estimation methods relatively quickly using a windows interface. The new version of FLIKE has been incorporated with the multiple Grubbs and Beck test which can identify multiple numbers of potentially influential low flows. This paper presents a case study considering six catchments in eastern Australia which compares two outlier identification tests (original Grubbs and Beck test and multiple Grubbs and Beck test) and two commonly applied probability distributions (Generalized Extreme Value (GEV) and Log Pearson type 3 (LP3)) using FLIKE software. It has been found that the multiple Grubbs and Beck test when used with LP3 distribution provides more accurate flood quantile estimates than when LP3 distribution is used with the original Grubbs and Beck test. Between these two methods, the differences in flood quantile estimates have been found to be up to 61% for the six study catchments. It has also been found that GEV distribution (with L moments) and LP3 distribution with the multiple Grubbs and Beck test provide quite similar results in most of the cases; however, a difference up to 38% has been noted for flood quantiles for annual exceedance probability (AEP) of 1 in 100 for one catchment. These findings need to be confirmed with a greater number of stations across other Australian states.

Keywords: floods, FLIKE, probability distributions, flood frequency, outlier

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Authors: Rubén Manrique, Delio Balcázar, José Parrado, Sebastián Rodríguez

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Hand in hand with the evolution of technology, education systems have moved to virtual environments to provide increased coverage and facilitate the access to education. However, measuring student performance in virtual environments presents significant challenges to ensure students are acquiring the expected skills. In this study, the confidence and performance of engineering students in virtual environments is analyzed through different evaluation strategies. The effect of the assessment strategy in student confidence is identified using educational data mining techniques. Four assessment strategies were used. First, a conventional multiple choice test; second, a multiple choice test with feedback; third, a multiple choice test with a second chance; and fourth; a multiple choice test with feedback and second chance. Our results show that applying testing with online feedback strategies can influence positively student confidence.

Keywords: assessment strategies, educational data mining, student performance, student confidence

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Authors: Janice Keener, Christine Houlihan

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Over the last several years, there has been an increase in children identified as having Autism Spectrum Disorder (ASD). Specialists across several disciplines: mental health and medical professionals have been tasked with ensuring accurate and timely evaluations for children with suspected ASD. Due to the nature of the ASD symptom presentation, an interdisciplinary assessment and treatment approach best addresses the needs of the whole child. During the unprecedented COVID-19 Pandemic, clinicians were faced with how to continue with interdisciplinary assessments in a telehealth arena. Instruments that were previously used to assess ASD in-person were no longer appropriate measures to use due to the safety restrictions. For example, The Autism Diagnostic Observation Schedule requires examiners and children to be in very close proximity of each other and if masks or face shields are worn, they render the evaluation invalid. Similar issues arose with the various cognitive measures that are used to assess children such as the Weschler Tests of Intelligence and the Differential Ability Scale. Thus the need arose to identify measures that are able to be safely and accurately administered using safety guidelines. The incidence of ASD continues to rise over time. Currently, the Center for Disease Control estimates that 1 in 59 children meet the criteria for a diagnosis of ASD. The reasons for this increase are likely multifold, including changes in diagnostic criteria, public awareness of the condition, and other environmental and genetic factors. The rise in the incidence of ASD has led to a greater need for diagnostic and treatment services across the United States. The uncertainty of the diagnostic process can lead to an increased level of stress for families of children with suspected ASD. Along with this increase, there is a need for diagnostic clarity to avoid both under and over-identification of this condition. Interdisciplinary assessment is ideal for children with suspected ASD, as it allows for an assessment of the whole child over the course of time and across multiple settings. Clinicians such as Psychologists and Developmental Pediatricians play important roles in the initial evaluation of autism spectrum disorder. An ASD assessment may consist of several types of measures such as standardized checklists, structured interviews, and direct assessments such as the ADOS-2 are just a few examples. With the advent of telehealth clinicians were asked to continue to provide meaningful interdisciplinary assessments via an electronic platform and, in a sense, going to the family home and evaluating the clinical symptom presentation remotely and confidently making an accurate diagnosis. This poster presentation will review the benefits, limitations, and interpretation of these various instruments. The role of other medical professionals will also be addressed, including medical providers, speech pathology, and occupational therapy.

Keywords: Autism Spectrum Disorder Assessments, Interdisciplinary Evaluations , Tele-Assessment with Autism Spectrum Disorder, Diagnosis of Autism Spectrum Disorder

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Authors: Tianle Yang

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As a common mental disorder, depression is a leading cause of various diseases worldwide. Early detection and treatment of depression can dramatically promote remission and prevent relapse. However, conventional ways of depression diagnosis require considerable human effort and cause economic burden, while still being prone to misdiagnosis. On the other hand, recent studies report that physical characteristics are major contributors to the diagnosis of depression, which inspires us to mine the internal relationship by neural networks instead of relying on clinical experiences. In this paper, neural networks are constructed to predict depression from physical characteristics. Two initialization methods are examined - Xaiver and Kaiming initialization. Experimental results show that a 3-layers neural network with Kaiming initialization achieves 83% accuracy.

Keywords: depression, neural network, Xavier initialization, Kaiming initialization

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Authors: Yaser Meeralam, Walaa Alharthi, Hadeel Ashi, Alaa Bakhsh, Kholood Aljabri, Ebtihal Bin Salim

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Background:Basidiobolusranrum causes one of the rare fungal diseases that infects mainly immunocompetent individuals. Gastrointestinal Basidiobolomycosis (GIB) is a rare and uncommon form of this fungal infection. It’s still ambiguous how this fungus is reaching the gastrointestinal tract leading to Gastrointestinal Basidiobolomycosis. Objective: To summarize the clinical features, imaging, and histopathological of patients diagnosed with GIB in our institution. Patients and methods: A series of five cases of patients who diagnosed by basidiobolomycosis in King Abdullah Medical City, Makkah, Saudi Arabia, which reviewed by latest literature related to diagnosis and treatment. Results: Most of the patients were externally evaluated and were initially misdiagnosed. Some of them were suspected of colonic malignancy, other presumed to have hepatic hemangioma and fistulizing crohn’s disease. The definitive diagnosis is often based on histopathological examination and fungal culture of the surgically resected mass. An optimum standardized treatment of basidiobolomycosis has not yet been established. Conclusion: Deeper knowledge of clinical characteristics, diagnosis, and treatment of basidiobolomycosis will allow early initiating of treatment with a subsequent positive impact on the patients’ outcome. More studies are needed to establish a definite treatment.

Keywords: gastrointestinal infection, crohn's mimics, malignancy mimics, fungal infection

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Authors: Mohamed Gar Alalm

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This study aims to investigate various operating conditions that affect the performance of the electro-Fenton process for degradation of pesticides. Stainless steel electrodes were utilized in the electro-Fenton cell due to their relatively low cost. The favored conditions of current intensity, pH, iron loading, and pesticide concentration were deeply discussed. Complete removal of pesticide was attained at the optimum conditions. The degradation kinetics were described by pseudo- first-order pattern. In addition, a response surface model was developed to describe the performance of electro-Fenton process under different operational conditions. The model indicated that the coefficient of determination was (R² = 0.995).

Keywords: electro-Fenton, stainless steel, pesticide, wastewater

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Yaya Gao, Jifeng Liu, Yafeng Liu

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Objectives: This study aimed to improve clinicians' understanding and diagnosis of the Mammary analogue secretory carcinoma of the salivary gland（MASC）. Methods: The clinical features of a MASC patient who was admitted to WestChina Hospital of Sichuan University in July 2020 were reviewed and analyzed. A 49-year-old woman with left upper neck pain for three months was admitted to the hospital. She underwent adenoma resection of the left submandibular gland 14 years ago and mucoepidermoid carcinoma resection surgery five years ago. Three months before admission, the patient developed pain in the left mandibular angle after "fatigue" and gradually developed radiation pain in the left ear, which could be relieved after rest. A mass of 1cm could be touched at the mandibular, with tenderness, poor mobility, and hard texture. No swelling, heat, pain, rupture, or pus was found on the surrounding skin. Color doppler ultrasonography of the salivary gland indicated a weak echo mass of 23*14*17mm in the left parotid gland. Results: Surgical excision was completed. Immunohistochemistry of the tumor samples after operation showed that P63（a few，+）, CK7（+）, S100（+）, DOG1（-）, Ki67（MIB-1）（+，5%），pan-TRK（+）, PAS(+) . ETV-6 gene translocation was detected in FISH in postoperative pathology, which indicated MASC. After this diagnosis, the patient sent the postoperative specimen of the second submandibular tumor to our hospital for consultation. The morphology of the two was similar. FISH detected ETV-6 gene translocation, so the second pathological diagnosis was revised to MASC. Conclusion: MASC of the salivary gland is a rare salivary gland tumor whose diagnosis depends on the result of the ETV6-NTRK3 fusion gene.

Keywords: mammary analogue secretory carcinoma, ETV6-NTRK3, salivary gland, misdiagnosed

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Authors: Muhammad Fiaz Qamar, Uzma Mehreen, Muhammad Arfan Zaman, Kazim Ali

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Ovine Theileriosis is a world-wide concern, especially in tropical and subtropical areas, due to having tick abundance that has received less awareness in different developed and developing areas due to less worth of sheep, low to the middle level of infection in different small ruminants herd. Across Asia, the prevalence reports have been conducted to provide equivalent calculation of flock and animal level prevalence of Theileriosisin animals. It is a challenge for veterinarians to timely diagnosis & control of Theileriosis and famers because of the nature of the organism and inadequacy of restricted plans to control. All most work is based upon the development of such a technique which should be farmer-friendly, less expensive, and easy to perform into the field. By the timely diagnosis of this disease will decrease the irrational use of the drugs, and other plan was to determine the prevalence of Theileriosis in District Jhang by using the conventional method, PCR and qPCR, and LAMP. We quantify the molecular epidemiology of T.lestoquardiin sheep from Jhang districts, Punjab, Pakistan. In this study, we concluded that the overall prevalence of Theileriosis was (32/350*100= 9.1%) in sheep by using Giemsa staining technique, whereas (48/350*100= 13%) is observed by using PCR technique (56/350*100=16%) in qPCR and the LAMP technique have shown up to this much prevalence percentage (60/350*100= 17.1%). The specificity and sensitivity also calculated in comparison with the PCR and LAMP technique. Means more positive results have been shown when the diagnosis has been done with the help of LAMP. And there is little bit of difference between the positive results of PCR and qPCR, and the least positive animals was by using Giemsa staining technique/conventional method. If we talk about the specificity and sensitivity of the LAMP as compared to PCR, The cross tabulation shows that the results of sensitivity of LAMP counted was 94.4%, and specificity of LAMP counted was 78%. Advances in scientific field must be upon reality based ideas which can lessen the gaps and hurdles in the way of scientific research; the lamp is one of such techniques which have done wonders in adding value and helping human at large. It is such a great biological diagnostic tools and has helped a lot in the proper diagnosis and treatment of certain diseases. Other methods for diagnosis, such as culture techniques and serological techniques, have exposed humans with great danger. However, with the help of molecular diagnostic technique like LAMP, exposure to such pathogens is being avoided in the current era Most prompt and tentative diagnosis can be made using LAMP. Other techniques like PCR has many disadvantages when compared to LAMP as PCR is a relatively expensive, time consuming, and very complicated procedure while LAMP is relatively cheap, easy to perform, less time consuming, and more accurate. LAMP technique has removed hurdles in the way of scientific research and molecular diagnostics, making it approachable to poor and developing countries.

Keywords: distribution, thelaria, LAMP, primer sequences, PCR

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Authors: Seung-Jun Yu, Yeong-Seop Ahn, Young-Min Ko, Hyoung-Kyu Song

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In order to achieve high data rate and increase the spectral efficiency, multiple input multiple output (MIMO) system has been proposed. However, multiple antennas are limited by size and cost. Therefore, recently developed cooperative diversity scheme, which profits the transmit diversity only with the existing hardware by constituting a virtual antenna array, can be a solution. However, most of the introduced cooperative techniques have a common fault of decreased transmission rate because the destination should receive the decodable compositions of symbols from the source and the relay. In this paper, we propose a cooperative cyclic delay diversity (CDD) scheme that uses hierarchical modulation. This scheme is free from the rate loss and allows seamless cooperative communication.

Keywords: MIMO, cooperative communication, CDD, hierarchical modulation

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Authors: Satyasen Panda, Urmila Bhanja

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In this paper, we have presented and analyzed three-dimensional (3-D) matrices of wavelength/time/space code for optical code division multiple access (OCDMA) networks with NAND subtraction detection technique. The 3-D codes are constructed by integrating a two-dimensional modified quadratic congruence (MQC) code with one-dimensional modified prime (MP) code. The respective encoders and decoders were designed using fiber Bragg gratings and optical delay lines to minimize the bit error rate (BER). The performance analysis of the 3D-OCDMA system is based on measurement of signal to noise ratio (SNR), BER and eye diagram for a different number of simultaneous users. Also, in the analysis, various types of noises and multiple access interference (MAI) effects were considered. The results obtained with NAND detection technique were compared with those obtained with OR and AND subtraction techniques. The comparison results proved that the NAND detection technique with 3-D MQC\MP code can accommodate more number of simultaneous users for longer distances of fiber with minimum BER as compared to OR and AND subtraction techniques. The received optical power is also measured at various levels of BER to analyze the effect of attenuation.

Keywords: Cross Correlation (CC), Three dimensional Optical Code Division Multiple Access (3-D OCDMA), Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA), Multiple Access Interference (MAI), Phase Induced Intensity Noise (PIIN), Three Dimensional Modified Quadratic Congruence/Modified Prime (3-D MQC/MP) code

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Authors: Parveen Kundu, Zile Singh, Kunika Kundu, Swaran Kaur

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Context: Tuberculous osteomyelitis is a relatively uncommon condition that can present with various clinical and radiological features, often mimicking bone tumors or tumor-like lesions. In endemic countries like India, tuberculosis should be considered as a potential differential diagnosis for lytic bone lesions. This study aimed to highlight the different presentations of tuberculosis that can mimic tumors or tumor-like lesions in bone and emphasize the successful outcome of antitubercular therapy (ATT) in treating these cases. Research Aim: The main objective of this research was to explore the varied presentations of tuberculosis that mimic bone tumors or tumor-like lesions both clinically and radiologically, focusing on different bones. The study aimed to raise awareness among clinicians about this possibility and highlight the importance of histopathological confirmation before initiating treatment for lytic bone lesions. Methodology: This study utilized a retrospective review of 22 patients with suspected lytic bone lesions, who were subsequently diagnosed with tuberculous osteomyelitis through histopathological examination. The cases were collected over a period of ten years. Eleven cases required curettage for extensive lesions with sequestrations, while all 22 patients received 12 months of antitubercular therapy. Findings: The study included 14 male and 8 female patients, ranging in age from 3 to 61 years, with an average age of 22.05. The clinical and radiological presentations varied, with examples including bone cysts in the metaphyseal area of long bones, lesions resembling chondroblastomas, giant cell tumors, and osteoid osteoma, as well as multifocal lytic lesions resembling metastasis or multiple myeloma. One patient had lesions in both the clavicle and hand. Lesions mimicking chondromas were also observed in the phalanges of the hand and foot metatarsal. All patients showed resolution of the lesions and no residual disability following ATT. Theoretical Importance: This study highlights the importance of considering tuberculosis as a potential differential diagnosis for lytic bone lesions, particularly in endemic regions. It emphasizes the need for histopathological confirmation to accurately diagnose tuberculous osteomyelitis, as this is considered the gold standard. Data Collection and Analysis Procedures: Data for this study were collected retrospectively from medical records and radiological images of the 22 patients. The cases were analyzed based on clinical presentation, radiological findings, and histopathological confirmation. The outcomes of antitubercular therapy were also assessed. The data were summarized and presented descriptively. Question Addressed: This study aimed to address the question of how tuberculosis can mimic different bone tumors and tumor-like lesions clinically and radiologically. It also aimed to assess the successful outcome of antitubercular therapy in treating these cases. Conclusion: Tuberculous osteomyelitis can present with varied clinical and radiological features, often mimicking bone tumors or tumor-like lesions. Clinicians should consider tuberculosis as a potential diagnosis for lytic bone lesions, especially in endemic areas. Histopathological confirmation is essential for accurate diagnosis. Antitubercular therapy is an effective treatment for tuberculous osteomyelitis, leading to the resolution of the lesions with no residual disability.

Keywords: tuberculosis, tumor, curettage, bone

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Authors: Rachel Shukrun, Szilvia Baron, Victoria Fidel, Anna Shusterman, Osnat Sher, Netanya Kollender, Dror Levin, Yair Peled, Yair Gortzak, Yoav Ben-Shahar, Revital Caspi, Sagi Gordon, Michal Manisterski, Ronit Elhasid

Abstract:

Ewing sarcoma (EWS) is a highly aggressive cancer with a survival rate of 70–80% for patients with localized disease and under 30% for those with metastatic disease. Tumor-infiltrating neutrophils (TIN) can generate extracellular net-like DNA structures known as neutrophil extracellular traps (NETs). However, little is known about the presence and prognostic significance of tumor-infiltrating NETs in EWS. Herein, we investigated 46 patients diagnosed with EWS and treated in the Tel Aviv Medical Center between 2010 and 2021. TINs and NETs were identified in diagnostic biopsies of EWS by immunofluorescent. In addition, NETs were investigated in neutrophils isolated from peripheral blood samples of EWS patients at diagnosis and following neoadjuvant chemotherapy. The relationships between the presence of TINs and NETs, pathological and clinical features, and outcomes were analyzed. Our results demonstrate that TIN and NETs at diagnosis were higher in EWS patients with metastatic disease compared to those with local disease. High NETs formation at diagnosis predicted poor response to neo-adjuvant chemotherapy, relapse, and death from disease (P < .05). NETs formation in peripheral blood samples at diagnosis was significantly elevated among patients with EWS compared to pediatric controls and decreased significantly following neoadjuvant chemotherapy. In conclusion, NETs formation seems to have a role in the EWS immune microenvironment. Their presence can refine risk stratification, predict chemotherapy resistance and survival, and serve as a therapeutic target in patients with EWS.

Keywords: Ewing sarcoma, tumor microenvironment, neutrophil, neutrophil extracellular traps (NETs), prognosis

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Authors: Masoud Shahmanzari

Abstract:

The aim of this paper is to present a Variable Neighborhood Search (VNS) with Tabu Search (TS) conditions for the Roaming Salesman Problem (RSP). The RSP is a special case of the well-known traveling salesman problem (TSP) where a set of cities with time-dependent rewards and a set of campaign days are given. Each city can be visited on any day and a subset of cities can be visited multiple times. The goal is to determine an optimal campaign schedule consist of daily open/closed tours that visit some cities and maximizes the total net benefit while respecting daily maximum tour duration constraints and the necessity to return campaign base frequently. This problem arises in several real-life applications and particularly in election logistics where depots are not fixed. We formulate the problem as a mixed integer linear programming (MILP), in which we capture as many real-world aspects of the RSP as possible. We also present a hybrid metaheuristic algorithm based on a VNS with TS conditions. The initial feasible solution is constructed via a new matheuristc approach based on the decomposition of the original problem. Next, this solution is improved in terms of the collected rewards using the proposed local search procedure. We consider a set of 81 cities in Turkey and a campaign of 30 days as our largest instance. Computational results on real-world instances show that the developed algorithm could find near-optimal solutions effectively.

Keywords: optimization, routing, election logistics, heuristics

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Authors: Anukriti Verma, Bhawna Rathi, Shivani Sharda

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Reactive Arthritis (ReA) is a disorder that causes inflammation in joints due to certain infections at distant sites in the body. ReA begins with stiffness, pain, and inflammation in these areas especially the ankles, knees, and hips. It gradually causes several complications such as conjunctivitis in the eyes, skin lesions in hand, feet and nails and ulcers in the mouth. Nowadays the diagnosis of ReA is based upon a differential diagnosis pattern. The parameters for differentiating ReA from other similar disorders include physical examination, history of the patient and a high index of suspicion. There are no standard lab tests or markers available for ReA hence the early diagnosis of ReA becomes difficult and the chronicity of disease increases with time. It is reported that enteric disorders such as Inflammatory Bowel Disease (IBD) that is inflammation in gastrointestinal tract namely Crohn’s Disease (CD) and Ulcerative Colitis (UC) are reported to be linked with ReA. Several microorganisms are found such as Campylobacter, Salmonella, Shigella and Yersinia causing IBD leading to ReA. The aim of our study was to perform the in-silico analysis in order to find interactions between microorganisms and human host causing IBD leading to ReA. A systems biology approach for metabolic network reconstruction and simulation was used to find the essential genes of the reported microorganisms. Interactomics study was used to find the interactions between the pathogen genes and human host. Genes such as nhaA (pathogen), dpyD (human), nagK (human) and kynU (human) were obtained that were analysed further using the functional, pathway and network analysis. These genes can be used as putative drug targets and biomarkers in future for early diagnosis, prevention, and treatment of IBD leading to ReA.

Keywords: drug targets, inflammatory bowel disease, reactive arthritis, systems biology

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Authors: Kemka C. Ihemelandu, Chukwuemeka U. Ihemelandu

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The incidence of melanoma has been increasing rapidly over the past two decades, making melanoma a current public health crisis. Unfortunately, even as screening efforts continue to expand in an effort to ameliorate the death rate from melanoma, there is a need to improve diagnostic accuracy to decrease misdiagnosis. Artificial intelligence (AI) a new frontier in patient care has the ability to improve the accuracy of melanoma diagnosis. Convolutional neural network (CNN) a form of deep neural network, most commonly applied to analyze visual imagery, has been shown to outperform the human brain in pattern recognition. However, there are noted limitations with the accuracy of the CNN models. Our aim in this study was the optimization of convolutional neural network algorithms for the automated diagnosis of melanoma. We hypothesized that Optimal selection of the momentum and batch hyperparameter increases model accuracy. Our most successful model developed during this study, showed that optimal selection of momentum of 0.25, batch size of 2, led to a superior performance and a faster model training time, with an accuracy of ~ 83% after nine hours of training. We did notice a lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone. Training set image transformations did not result in a superior model performance in our study.

Keywords: melanoma, convolutional neural network, momentum, batch hyperparameter

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Authors: Sadia Munir

Abstract:

Preeclampsia is the contributor to the worldwide maternal mortality of approximately 100,000 deaths a year. It complicates about 10% of all pregnancies and is the first cause of maternal admission to intensive care units. Predicting preeclampsia is a major challenge in obstetrics. More importantly, no major progress has been achieved in the treatment of preeclampsia. As placenta is the main cause of the disease, the only way to treat the disease is to extract placental and deliver the baby. In developed countries, the cost of an average case of preeclampsia is estimated at £9000. Interestingly, preeclampsia may have an impact on the health of mother or infant, beyond the pregnancy. We performed a systematic search of PubMed including the combination of terms such as preeclampsia, biomarkers, treatment, hypoxia, inflammation, oxidative stress, vascular endothelial growth factor A, activin A, inhibin A, placental growth factor, transforming growth factor β-1, Nodal, placenta, trophoblast cells, microRNAs. In this review, we have summarized current knowledge on the identification of potential biomarkers for the diagnosis of preeclampsia. Although these studies show promising data in early diagnosis of preeclampsia, the current value of these factors as biomarkers, for the precise prediction of preeclampsia, has its limitation. Therefore, future studies need to be done to support some of the very promising and interesting data to develop affordable and widely available tests for early detection and treatment of preeclampsia.

Keywords: activin, biomarkers, growth factors, miroRNA

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