Search results for: diagnosis and treatment intervals

Authors: Amel Benhadji, Mourad Taleb Ahmed, Rachida Maachi

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The challenge for the new millennium is to develop an industrial system that has minimal socio-ecological impacts, without compromising quality of life. Leather industry is one of these industries demanding environmentally friendly products. In this study, we investigated the possibility of applying innovative low cost biological treatment using Pseudomonas aeruginosa. This strain tested the efficiency of the batch biological treatment in the recovery of protein and hexavalent chromium from chromium tanning bath. We have compared suspended and fixed bacteria culture. The results showed the removal of the total protein of treatment and a decrease of hexavalent chromium concentration is during the treatment. The better efficiency of the biological treatment is obtained when using fixed culture of P. aeruginosa.

Keywords: tanning wastewater, biological treatment, protein removal, hexavalent chromium

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Authors: Bajraktarevic Adnan, Djukic Branka, Sporisevic Lutvo, Krdzalic Zecevic Belma, Uzicanin Sajra, Hadzimuratovic Admir, Hadzimuratovic Hadzipasic Emina, Abduzaimovic Alisa, Kustric Amer, Suljevic Ismet, Serafi Ismail, Tahmiscija Indira, Khatib Hakam, Semic Jusufagic Aida, Haas Helmut, Vladicic Aleksandra, Aplenc Richard, Kadic Deovic Aida

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Introduction: Joubert syndrome has an autosomal recessive pattern of inheritance. It is referred as the brain malfunctioning and caused due to the underdevelopment of the cerebellar vermis. Associated conditions involving the eye, the kidney, and ocular disease are well described. Aims: Research helps us better understand this diseases, Joubert syndrome and can lead to advances in diagnosis and treatment. Methods: Different several conditions have been described in which the molar tooth sign and characteristics of Joubert syndrome in ten different places in the world. Carrier testing and diagnosis are available if one of these gene mutations has been identified in an affected family member. Results: Authors have described eleven cases during twenty years of Joubert syndrome. It is a clinically and genetically heterogeneous group of disorders characterized by hypoplasia of the cerebellar vermis with the characteristic neuroradiologic molar tooth sign, and accompanying neurologic symptoms, including dysregulation of breathing pattern and developmental delay. We made confirmation of diagnosis in twin sisters with Joubert syndrome with renal anomalies. Ocular symptoms have existed in seven cases (63.64%) from total eleven. Eleven cases were different sex, five boys (45.45%) and six girls (54.44%). Conclusions: Joubert syndrome is inherited as an autosomal recessive genetic disorder with several features of the disease.

Keywords: Joubert syndrome, cerebellooculorenal syndrome, autosomal recessive genetic disorder (ARGD), children

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Authors: Jiri Kysucan, Dusan Klos, Katherine Vomackova, Pavel Koranda, Martin Lovecek, Cestmir Neoral, Roman Havlik

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Aim: The prognosis of patients with pancreatic cancer is poor. The median of survival after establishing diagnosis is 3-11 months without surgical treatment, 13-20 months with surgical treatment depending on the disease stage, 5-year survival is less than 5%. Radical surgical resection remains the only hope of curing the disease. Early diagnosis with valid establishment of tumor resectability is, therefore, the most important aim for patients with pancreatic cancer. The aim of the work is to evaluate the contribution and define the role of 18F-FDG PET/CT in preoperative staging. Material and Methods: In 195 patients (103 males, 92 females, median age 66,7 years, 32-88 years) with a suspect pancreatic lesion, as part of the standard preoperative staging, in addition to standard examination methods (ultrasonography, contrast spiral CT, endoscopic ultrasonography, endoscopic ultrasonographic biopsy), a hybrid 18F-FDG PET/CT was performed. All PET/CT findings were subsequently compared with standard staging (CT, EUS, EUS FNA), with peroperative findings and definitive histology in the operated patients as reference standards. Interpretation defined the extent of the tumor according to TNM classification. Limitations of resectability were local advancement (T4) and presence of distant metastases (M1). Results: PET/CT was performed in a total of 195 patients with a suspect pancreatic lesion. In 153 patients, pancreatic carcinoma was confirmed and of these patients, 72 were not indicated for radical surgical procedure due to local inoperability or generalization of the disease. The sensitivity of PET/CT in detecting the primary lesion was 92.2%, specificity was 90.5%. A false negative finding in 12 patients, a false positive finding was seen in 4 cases, positive predictive value (PPV) 97.2%, negative predictive value (NPV) 76,0%. In evaluating regional lymph nodes, sensitivity was 51.9%, specificity 58.3%, PPV 58,3%, NPV 51.9%. In detecting distant metastases, PET/CT reached a sensitivity of 82.8%, specificity was 97.8%, PPV 96.9%, NPV 87.0%. PET/CT found distant metastases in 12 patients, which were not detected by standard methods. In 15 patients (15.6%) with potentially radically resectable findings, the procedure was contraindicated based on PET/CT findings and the treatment strategy was changed. Conclusion: PET/CT is a highly sensitive and specific method useful in preoperative staging of pancreatic cancer. It improves the selection of patients for radical surgical procedures, who can benefit from it and decreases the number of incorrectly indicated operations.

Keywords: cancer, PET/CT, staging, surgery

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Authors: Judita Konečná, Dagmar Halo, Martin Matoulek

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Background: Personality pathology does not have to be a contraindication nor an obstacle in obesity treatment, or eventually, surgical treatment. Detection of specific maladaptive personality traits can help us understand the manner of behavior leading to obesity as well as to address the treatment better. Objective: Using The Personality Inventory for DSM-5 (PID-5) in combination with clinical interviews with the goal of gaining a psychological evaluation to set the treatment procedure. Data was collected from more than 400 patients to detect differences in constellations of maladaptive personality traits based on BMI, DM2 and gender. Conclusions: Besides the fact that a psychological evaluation can help address the treatment better, analyses showed that it is also useful to detect specific groups of patients. Implications for clinical practice are discussed, as well as recommendations for group education programs based on quantitative research.

Keywords: bariatric surgery, obesity, personality traits, PID-5, treatment

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Authors: Recep Keşli, Onur Türkyılmaz, Hayriye Tokay, Kasım Demir

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Objective: Coeliac disease (CD) is a primary small intestine disorder caused by high sensitivity to gluten which is present in the crops, characterized by inflammation in the small intestine mucosa. The goal of this study was to determine and to compare the sensitivity and specificity values of anti-endomysial IgA (EMA IgA) (IFA) and anti-tissue transglutaminase IgA (anti-tTG IgA) (ELISA) antibodies in the diagnosis of patients suspected with the CD. Methods: One thousand two hundred seventy three patients, who have applied to gastroenterology and pediatric disease polyclinics of Afyon Kocatepe University ANS Research and Practice Hospital were included into the study between 23.09.2010 and 30.05.2016. Sera samples were investigated by immunofluorescence method for EMA positiveness (Euroimmun, Luebeck, Germany). In order to determine quantitative value of Anti-tTG IgA (EIA) (Orgentec Mainz, Germany) fully automated ELISA device (Alisei, Seac, Firenze, Italy) were used. Results: Out of 1273 patients, 160 were diagnosed with coeliac disease according to ESPGHAN 2012 diagnosis criteria. Out of 160 CD patients, 120 were female, 40 were male. The EMA specificity and sensitivity were calculated as 98% and 80% respectively. Specificity and sensitivity of Anti-tTG IgA were determined as 99% and 96% respectively. Conclusion: The specificity of EMA for CD was excellent because all EMA-positive patients (n = 144) were diagnosed with CD. The presence of human anti-tTG IgA was found as a reliable marker for diagnosis and follow-up the CD. Diagnosis of CD should be established on both the clinical and serologic profiles together.

Keywords: anti-endomysial antibody, anti-tTG IgA, coeliac disease, immunofluorescence assay (IFA)

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Authors: Wei Qu, Cassandra Agius, Nikki Varvazovsky, Angela Meade

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The goals of the case study are to address the importance of early diagnosis of osmotic demyelination syndrome (ODS) and to analyse the types, duration, and intensities of the rehabilitation program to promote neurological and functional recovery. It can be associated with biphasic course of disease and severe neurological and neuropsychiatric symptoms. Although a few treatment modalities, such as plasmapheresis, immunoglobulin therapy, steroid, and thyrotrophin-releasing hormone, have been suggested, there is no effective treatment for ODS. The overall prognosis of established ODS is generally poor. A high proportion of patients have a severe permanent disability, which has led to social, economic, and emotional burdens to carers and societies. In this case, a 69-year-old retired pensioner with chronic alcoholism was admitted to the hospital with a reduced level of consciousness and tonic-clonic seizure. He had severe hyponatraemia (serum sodium 118 mmol/L) and hypokalemia (serum potassium 2.8 mmol/L). He was treated with anticonvulsants, 150ml 3% hypertonic saline over one hour, and 40 mmol potassium chloride over one hour, and his sodium was increased by 11 mmol/L in the first 24 hours. However, he had worsened neurological symptoms with quadriplegia, dysphagia, anarthria, and confusion, and the radiological features suggested the diagnosis of ODS. He had minimal neurological recovery during the first four weeks of hospital admission. He was treated with seven weeks of a multi-disciplinary intensive rehabilitation program. On discharge, he had made a significant cognitive and functional recovery and could mobilize independently without a walking aid. In conclusion, ODS can still occur despite correcting sodium following the current clinical guidelines. Patients with severe neurological deficits in the context of osmotic demyelination syndrome would benefit from intensive rehabilitation to facilitate their functional improvement and to promote their quality of life.

Keywords: osmotic demyelination syndrome, hyponatremia, central pontine and extrapontine myelinolysis, rehabilitation

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Authors: Hyun-Woo Cho

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For ensuring the safety of a manufacturing process one should quickly identify an assignable cause of a fault in an on-line basis. To this end, many statistical techniques including linear and nonlinear methods have been frequently utilized. However, such methods possessed a major problem of small sample size, which is mostly attributed to the characteristics of empirical models used for reference models. This work presents a new method to overcome the insufficiency of measurement data in the monitoring and diagnosis tasks. Some quasi-measurement data are generated from existing data based on the two indices of similarity and importance. The performance of the method is demonstrated using a real data set. The results turn out that the presented methods are able to handle the insufficiency problem successfully. In addition, it is shown to be quite efficient in terms of computational speed and memory usage, and thus on-line implementation of the method is straightforward for monitoring and diagnosis purposes.

Keywords: data analysis, diagnosis, monitoring, process data, quality control

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Authors: Karina Zaccari, Ernesto Cordeiro Marujo

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This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: machine learning, medical diagnosis, meningitis detection, pediatric research

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Authors: Akbar Gharbali, Ali Abbasian Ardekani, Afshin Mohammadi

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Introduction: Thyroid nodules have an incidence of 33-68% in the general population. More than 5-15% of these nodules are malignant. Early detection and treatment of thyroid nodules increase the cure rate and provide optimal treatment. Between the medical imaging methods, Ultrasound is the chosen imaging technique for assessment of thyroid nodules. The confirming of the diagnosis usually demands repeated fine-needle aspiration biopsy (FNAB). So, current management has morbidity and non-zero mortality. Objective: To explore diagnostic potential of automatic texture analysis (TA) methods in differentiation benign and malignant thyroid nodules by ultrasound imaging in order to help for reliable diagnosis and monitoring of the thyroid nodules in their early stages with no need biopsy. Material and Methods: The thyroid US image database consists of 70 patients (26 benign and 44 malignant) which were reported by Radiologist and proven by the biopsy. Two slices per patient were loaded in Mazda Software version 4.6 for automatic texture analysis. Regions of interests (ROIs) were defined within the abnormal part of the thyroid nodules ultrasound images. Gray levels within an ROI normalized according to three normalization schemes: N1: default or original gray levels, N2: +/- 3 Sigma or dynamic intensity limited to µ+/- 3σ, and N3: present intensity limited to 1% - 99%. Up to 270 multiscale texture features parameters per ROIs per each normalization schemes were computed from well-known statistical methods employed in Mazda software. From the statistical point of view, all calculated texture features parameters are not useful for texture analysis. So, the features based on maximum Fisher coefficient and the minimum probability of classification error and average correlation coefficients (POE+ACC) eliminated to 10 best and most effective features per normalization schemes. We analyze this feature under two standardization states (standard (S) and non-standard (NS)) with Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Non-Linear Discriminant Analysis (NDA). The 1NN classifier was performed to distinguish between benign and malignant tumors. The confusion matrix and Receiver operating characteristic (ROC) curve analysis were used for the formulation of more reliable criteria of the performance of employed texture analysis methods. Results: The results demonstrated the influence of the normalization schemes and reduction methods on the effectiveness of the obtained features as a descriptor on discrimination power and classification results. The selected subset features under 1%-99% normalization, POE+ACC reduction and NDA texture analysis yielded a high discrimination performance with the area under the ROC curve (Az) of 0.9722, in distinguishing Benign from Malignant Thyroid Nodules which correspond to sensitivity of 94.45%, specificity of 100%, and accuracy of 97.14%. Conclusions: Our results indicate computer-aided diagnosis is a reliable method, and can provide useful information to help radiologists in the detection and classification of benign and malignant thyroid nodules.

Keywords: ultrasound imaging, thyroid nodules, computer aided diagnosis, texture analysis, PCA, LDA, NDA

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Authors: Esmaeil Kouhgardi, Saeedeh Dashti, Hakimeh Fekrandish

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This research has been conducted to study the method of culture and comparing growth and biomass of Gracilariacorticata cultured on rope and net for 50 days through two treatments (first treatment: culture of alga on net and the second treatment: culture of alga on rope and each treatment was repeated by four cases). During culture period, the water of aquariums was replaced once every two days for 40-50%. Also, 0.3-0.5 grams of Urea fertilizer was added to the culture environment for fertilization. Moreover, some of the environmental factors such as pH, salinity and temperature of the environment were measured on a daily basis. During the culture period, extent of longitudinal growth of the species of both treatments was equal. The said length was reached from 8-10 cm to 10.5-13 cm accordingly. The resulted weight in repetitions of the first treatment was higher than that of the second treatment in such a way as in the first treatment, its weight reached from 10 grams to 21.119 grams and in the second treatment, its weight reached from 10 grams to 17.663 grams. On a whole, it may be stated that that kind of alga being studied has a considerable growth with respect to its volume. The results have revealed that the percentage of daily growth and wet weight at the end of the first treatment was higher than that of the second treatment and it was registered as 0.934, 6.072 and 811.432 in the first treatment and 0.797, 4.990 and 758.071 in the second treatment respectively. This difference is significant (P < 0.05). Growth and biomass of G. corticata through culture on net was more emphasizing on numerous branches due to wider bed. Moreover, higher level of the species in this method was exposed to sunlight and this increased biosynthesis and eventually increases of growth and biomass.

Keywords: red alga, growth, biomass, culture, net, rope

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Authors: Meryem Saban Guler, Saniye Bilici

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Malnutrition is a problem that significantly affects patients with cancer throughout the course of their illness, and it may be present from the moment of diagnosis until the end of treatment. We searched electronic databases using key terms such as ‘malnutrition in cancer patients’ or ‘nutritional status in cancer’ or ‘nutritional screening tools’ etc. Decline in nutritional status and continuing weight loss are associated with an increase in number and severity of complications, impaired quality of life and decreased survival rate. Nutrition is an important factor in the treatment and progression of cancer. Cancer patients are particularly susceptible to nutritional depletion due to the combined effects of the malignant disease and its treatment. With increasing incidence of cancer, identification and management of nutritional deficiencies are needed. Early identification of malnutrition, is substantial to minimize or prevent undesirable outcomes throughout clinical course. In determining the nutritional status; food consumption status, anthropometric methods, laboratory tests, clinical symptoms, psychosocial data are used. First-line strategies must include routine screening and identification of inpatients or outpatients at nutritional risk with the use of a simple and standardized screening tool. There is agreement among international nutrition organizations and accredited health care organizations that routine nutritional screening should be a standard procedure for every patient admitted to a hospital. There are f management of all cancer patients therefore routine nutritional screening with validated tools can identify cancer patients at risk.

Keywords: cancer, malnutrition, nutrition, nutritional screening

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Authors: Pakize Ozlem Kurt Polat, Gizem Metin, Koksal Yagdi

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In order to evaluate the effect of the different sources of salt on germination and early growth of five wheat cultivars (Katea, Bezostaja, Koksal-2000, Golia, Pehlivan) an experiment was conducted at the seed laboratory of the Uludag University, Agricultural Faculty, Department of Field Crops in Bursa/Turkey. Seeds were applied in five different resources media (KCl % 2, KCl %4, KNO₃ %0,5, KH₂PO₄ %0,5, PEG %10) and distilled water as the control). The seed was fully immersed in priming media at a temperature of 24ᵒC for durations of 12 and 24hours. Six different agronomic characters (seed germination, stem length, stem weight, radicle length, fresh weight, dry weight) were measured in 7th days and 14th days. Maximum seed germination percentage of seven days are Pehlivan was observed when the seeds were applied by KH₂PO₄ and Katea by distilled water as a control. The most stem length and stem weight were obtained for seeds were applied by KH₂PO₄ %0,5 with Katea and Bezostja immersed in priming media at 12h intervals beginning 7d after planting. Seeds were applied KH₂PO₄ %0,5 media produced maximum radicle length by Koksal and dry weight by Katea. The freshest weight obtains in Katea by KNO₃ %0,5 immersed in priming media at 24h. The most germination percent, dry weight, stem length of fourteen days was observed in Katea which subjected to KH₂PO₄ %0,5 solution. The most radicle length was observed Katea and Koksal in media of KH₂PO₄ %0,5. The most stem length was obtained for seeds were applied by KH₂PO₄ %0,5 and KNO₃ with Katea and Bezostaja. When the applied chemicals and all days examined KH₂PO₄ %0,5 treatment in fourteen days and immersed for the duration of 24 hours had better effects than other medias, seven days treatments and 12hours immersed. As a result of this research, the best response of media for the wheat germination can be said that the KH₂PO₄ %0,5 immersed in priming media at 24h intervals beginning 14 days after planting.

Keywords: germination, priming, seedling growth, wheat

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Authors: Ayami Umemura

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The purpose of this paper is to examine the meaning of verbalization in clinical practice using the keywords silence and singularity. A patient's experience of illness and treatment is singular, irreplaceable, and irreproducible and ultimately cannot be compared with that of others. In his book Difference and Repetition, Gilles Deleuze positioned irreplaceable singularity as the opposite concept of particularity as a generalizable and substitutable property and matched the former with universality. He also said that singularity could not be represented because of its irreplaceable nature. Representation or verbalization is a procedure that converts an irreplaceable, idiosyncratic reality into something that can be substituted. Considering the act of verbalizing medical diagnosis based on this, it can be said that diagnosis is the practice of decontextualizing and generalizing the suffering embedded in the patient's irreplaceable life history as a disease. This paper examines the above with the key concept of the practice of "non-verbalization" in traditional medical practices in Sri Lanka. In the practice of Sri Lankan traditional medicine and the inheritance of medical knowledge and care techniques, there is a tendency to avoid verbalizing specific matters or stating them aloud. Specifically, the following should be avoided. The healer informs the patient of the name of the disease, mentions the name of the herb used in front of the patient, explains the patient's condition to the healer, and referring the names of poisonous animals, such as poisonous snakes that have been damaged. And so on. Furthermore, when passing on medical knowledge and skills, it is also possible to avoid verbalizing knowledge of medicinal herbs and medical treatment methods and explaining them verbally. In addition to the local belief that the soul of language in Sri Lanka is deeply involved in this background, Sri Lankan traditional medicine has a unique view of the human body and personality that is rooted in the singularity that appears in the relationship with the movement of celestial bodies and the supernatural realm. It can be pointed out that it is premised on the view. In other words, the “silence” in Sri Lankan indigenous medicine is the reason for emphasizing specificity. Furthermore, we can say that "non-verbalization" is a practice aimed at healing. Based on these discussions, this paper will focus on the unique relationships between practitioners and patients that become invisible due to verbalization, which is overlooked by clinical medicine, where informed consent, ensuring transparency, and audit culture is dominant. We will examine the experience of treatment and aim to relativize clinical medicine, which is based on audit cultures.

Keywords: audit cultures, indigenous medicine, singularity, verbalization

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Authors: Gökçe Erdemir, İlhan Yaylım, Serap Erdem-Kuruca, Musa Mutlu Can

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It has been determined that the main reason for the death of cancer disease is caused by metastases rather than the primary tumor. The cells that leave the primary tumor and enter the circulation and cause metastasis in the secondary organs are called "circulating tumor cells" (CTCs). The presence and number of circulating tumor cells has been associated with poor prognosis in many major types of cancer, including breast, prostate, and colorectal cancer. It is thought that knowledge of circulating tumor cells, which are seen as the main cause of cancer-related deaths due to metastasis, plays a key role in the diagnosis and treatment of cancer. The fact that tissue biopsies used in cancer diagnosis and follow-up are an invasive method and are insufficient in understanding the risk of metastasis and the progression of the disease have led to new searches. Liquid biopsy tests performed with a small amount of blood sample taken from the patient for the detection of CTCs are easy and reliable, as well as allowing more than one sample to be taken over time to follow the prognosis. However, since these cells are found in very small amounts in the blood, it is very difficult to capture them and specially designed analytical techniques and devices are required. Methods based on the biological and physical properties of the cells are used to capture these cells in the blood. Early diagnosis is very important in following the prognosis of tumors of epithelial origin such as breast, lung, colon and prostate. Molecules such as EpCAM, vimentin, and cytokeratins are expressed on the surface of cells that pass into the circulation from very few primary tumors and reach secondary organs from the circulation, and are used in the diagnosis of cancer in the early stage. For example, increased EpCAM expression in breast and prostate cancer has been associated with prognosis. These molecules can be determined in some blood or body fluids to be taken from patients. However, more sensitive methods are required to be able to determine when they are at a low level according to the course of the disease. The aim is to detect these molecules found in very few cancer cells with the help of sensitive, fast-sensing biosensors, first in breast cancer cells reproduced in vitro and then in blood samples taken from breast cancer patients. In this way, cancer cells can be diagnosed early and easily and effectively treated.

Keywords: electrochemical biosensors, breast cancer, circulating tumor cells, EpCAM, Vimentin, Cytokeratins

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Authors: Jaci Mastrandrea

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Background: The National Comprehensive Cancer Network (NCCN) recommends that healthcare institutions have established processes for integrating palliative care (PC) into cancer treatment and that all cancer patients be screened for PC needs upon initial diagnosis as well as throughout the entire continuum of care (National Comprehensive Cancer Network, 2021). Early PC screening is directly correlated with improved patient outcomes. The Sky Lakes Cancer Treatment Center (SLCTC) is an institution that has access to PC services yet does not have protocols in place for identifying patients with palliative needs or a standardized referral process. The aim of this quality improvement project is to improve early access to PC services by establishing a standardized screening and referral process for outpatient oncology patients. Method: The sample population included all adult patients with an oncology diagnosis who presented to the SLCTC for treatment during the project timeline from March 15th, 2022, to April 29th, 2022. The “Palliative and Supportive Needs Assessment'' (PSNA) screening tool was developed from validated and evidence-based PC referral criteria. The tool was initially implemented using paper forms and later was integrated into the Epic-Beacon EHR system. Patients were screened by registered nurses on the SLCTC treatment team. Nurses responsible for screening patients received an educational inservice prior to implementation. Patients with a PSNA score of three or higher were considered to be a positive screen. Scores of five or higher triggered a PC referral order in the patient’s EHR for the oncologist to review and approve. All patients with a positive screen received an educational handout on the topic of PC, and the EHR was flagged for follow-up. Results: Prior to implementation of the PSCNA screening tool, the SLCTC had zero referrals to PC in the past year, excluding referrals to hospice. Data was collected from the first 100 patient screenings completed within the eight-week data collection period. Seventy-three percent of patients met criteria for PC referral with a score greater than or equal to three. Of those patients who met referral criteria, 53.4% (39 patients) were referred for a palliative and supportive care consultation. Patients that were not referred to PC upon meeting the criteria were flagged in the EHR for re-screening within one to three months. Patients with lung cancer, chronic hematologic malignancies, breast cancer, and gastrointestinal malignancy most frequently met criteria for PC referral and scored highest overall on the scale of 0-12. Conclusion: The implementation of a standardized PC screening tool at the SLCTC significantly increased awareness of PC needs among cancer patients in the outpatient setting. Additionally, data derived from this quality improvement project supports the national recommendation for PC to be an integral component of cancer treatment across the entire continuum of care.

Keywords: oncology, palliative care, symptom management, symptom screening, ambulatory oncology, cancer, supportive care

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Authors: Kiraz Esmeli, Alper Ozkan

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In this study, firstly, the effect of ultrasonic treatment on the stability of celestite suspension was investigated. In this context, the variations of the suspension stability with ultrasonic power, treatment time, immersion depth of ultrasonic probe, and treatment regime (batch and continuous) were determined. The experimental results showed that the suspension stability and zeta potential of celestite decreased with ultrasonic treatment. Also, the treatment time, immersion depth of probe, and treatment regime affected the stability of celestite suspension. Secondly, the effect of pre-treatment of the suspension with the ultrasonic process on the shear flocculation of celestite using sodium dodecyl sulfate (SDS) was studied and the variations of the flocculation, zeta potential, and contact angle of the mineral with SDS concentration were presented. It was found that the ultrasonic pre-treatment slightly improved the shear flocculation of celestite particles in accordance with the increase in the contact angles. In addition, the ultrasonic process again relatively reduced the magnitude of the negative potential of celestite particles in the presence of SDS.

Keywords: celestite, contact angle, suspension stability, ultrasonic treatment, zeta potential

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Authors: Y. Kourd, D. Lefebvre

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The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. This paper proposes a method of fault diagnosis based on a neuro-fuzzy hybrid structure. This hybrid structure combines the selection of threshold and decision tree. The validation of this method is obtained with the DAMADICS benchmark. In the first phase of the method, a model will be constructed that represents the normal state of the system to fault detection. Signatures of the faults are obtained with residuals analysis and selection of appropriate thresholds. These signatures provide groups of non-separable faults. In the second phase, we build faulty models to see the flaws in the system that cannot be isolated in the first phase. In the latest phase we construct the tree that isolates these faults.

Keywords: decision tree, residuals analysis, ANFIS, fault diagnosis

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Authors: Ashwini Mohan, Haris Batley

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An orthodontic index is used to rate or categorise an individual’s occlusion using a numeric or alphanumeric score. Indexing of malocclusions and their correction is important in epidemiology, diagnosis, communication between clinicians as well as their patients and assessing treatment outcomes. Many useful indices have been put forward, but to the author’s best knowledge, no one method to this day appears to be equally suitable for the use of epidemiologists, public health program planners and clinicians. This article describes the common clinical orthodontic indices and classifications used in United Kingdom.

Keywords: classification, indices, orthodontics, validity

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Authors: Yosep Chong, Yejin Kim, Jingyun Choi, Hwanjo Yu, Eun Jung Lee, Chang Suk Kang

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For the past decades, immunohistochemistry (IHC) has been playing an important role in the diagnosis of human neoplasms, by helping pathologists to make a clearer decision on differential diagnosis, subtyping, personalized treatment plan, and finally prognosis prediction. However, the IHC performed in various tumors of daily practice often shows conflicting and very challenging results to interpret. Even comprehensive diagnosis synthesizing clinical, histologic and immunohistochemical findings can be helpless in some twisted cases. Another important issue is that the IHC data is increasing exponentially and more and more information have to be taken into account. For this reason, we reached an idea to develop an expert supporting system to help pathologists to make a better decision in diagnosing human neoplasms with IHC results. We gave probabilistic decision tree algorithm and tested the algorithm with real case data of lymphoid neoplasms, in which the IHC profile is more important to make a proper diagnosis than other human neoplasms. We designed probabilistic decision tree based on Bayesian theorem, program computational process using MATLAB (The MathWorks, Inc., USA) and prepared IHC profile database (about 104 disease category and 88 IHC antibodies) based on WHO classification by reviewing the literature. The initial probability of each neoplasm was set with the epidemiologic data of lymphoid neoplasm in Korea. With the IHC results of 131 patients sequentially selected, top three presumptive diagnoses for each case were made and compared with the original diagnoses. After the review of the data, 124 out of 131 were used for final analysis. As a result, the presumptive diagnoses were concordant with the original diagnoses in 118 cases (93.7%). The major reason of discordant cases was that the similarity of the IHC profile between two or three different neoplasms. The expert supporting system algorithm presented in this study is in its elementary stage and need more optimization using more advanced technology such as deep-learning with data of real cases, especially in differentiating T-cell lymphomas. Although it needs more refinement, it may be used to aid pathological decision making in future. A further application to determine IHC antibodies for a certain subset of differential diagnoses might be possible in near future.

Keywords: database, expert supporting system, immunohistochemistry, probabilistic decision tree

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Authors: Nayer Mofidtabatabaei

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Advancements in artificial intelligence (AI) have transformed various fields, including psychology and behavioral sciences. This paper explores the diverse ways in which AI is applied to enhance research, diagnosis, therapy, and understanding of human behavior and mental health. We discuss the potential benefits and challenges associated with AI in these fields, emphasizing the ethical considerations and the need for collaboration between AI researchers and psychological and behavioral science experts. Artificial Intelligence (AI) has gained prominence in recent years, revolutionizing multiple industries, including healthcare, finance, and entertainment. One area where AI holds significant promise is the field of psychology and behavioral sciences. AI applications in this domain range from improving the accuracy of diagnosis and treatment to understanding complex human behavior patterns. This paper aims to provide an overview of the various AI applications in psychological and behavioral sciences, highlighting their potential impact, challenges, and ethical considerations. Mental Health Diagnosis AI-driven tools, such as natural language processing and sentiment analysis, can analyze large datasets of text and speech to detect signs of mental health issues. For example, chatbots and virtual therapists can provide initial assessments and support to individuals suffering from anxiety or depression. Autism Spectrum Disorder (ASD) Diagnosis AI algorithms can assist in early ASD diagnosis by analyzing video and audio recordings of children's behavior. These tools help identify subtle behavioral markers, enabling earlier intervention and treatment. Personalized Therapy AI-based therapy platforms use personalized algorithms to adapt therapeutic interventions based on an individual's progress and needs. These platforms can provide continuous support and resources for patients, making therapy more accessible and effective. Virtual Reality Therapy Virtual reality (VR) combined with AI can create immersive therapeutic environments for treating phobias, PTSD, and social anxiety. AI algorithms can adapt VR scenarios in real-time to suit the patient's progress and comfort level. Data Analysis AI aids researchers in processing vast amounts of data, including survey responses, brain imaging, and genetic information. Privacy Concerns Collecting and analyzing personal data for AI applications in psychology and behavioral sciences raise significant privacy concerns. Researchers must ensure the ethical use and protection of sensitive information. Bias and Fairness AI algorithms can inherit biases present in training data, potentially leading to biased assessments or recommendations. Efforts to mitigate bias and ensure fairness in AI applications are crucial. Transparency and Accountability AI-driven decisions in psychology and behavioral sciences should be transparent and subject to accountability. Patients and practitioners should understand how AI algorithms operate and make decisions. AI applications in psychological and behavioral sciences have the potential to transform the field by enhancing diagnosis, therapy, and research. However, these advancements come with ethical challenges that require careful consideration. Collaboration between AI researchers and psychological and behavioral science experts is essential to harness AI's full potential while upholding ethical standards and privacy protections. The future of AI in psychology and behavioral sciences holds great promise, but it must be navigated with caution and responsibility.

Keywords: artificial intelligence, psychological sciences, behavioral sciences, diagnosis and therapy, ethical considerations

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Authors: Sarah Odofin, Zhiwei Gao, Sun Kai

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Operations, maintenance and reliability of wind turbines have received much attention over the years due to rapid expansion of wind farms. This paper explores early fault diagnosis scale technique based on a unique scheme of a 5MW wind turbine system that is optimized by genetic algorithm to be very sensitive to faults and resilient to disturbances. A quantitative model based analysis is pragmatic for primary fault diagnosis monitoring assessment to minimize downtime mostly caused by components breakdown and exploit productivity consistency. Simulation results are computed validating the wind turbine model which demonstrates system performance in a practical application of fault type examples. The results show the satisfactory effectiveness of the applied performance investigated in a Matlab/Simulink/Gatool environment.

Keywords: disturbance robustness, fault monitoring and detection, genetic algorithm, observer technique

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Authors: Soheila Zhaeentan, Anders Von Heijne, Elisabet Hagert, André Stark, Björn Salomonsson

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Recommended treatment for traumatic rotator cuff tear (TRCT) is surgery within a few weeks after injury if the diagnosis is made early, especially if a functional impairment of the shoulder exists. This may lead to the assumption that a poor outcome then can be expected in delayed surgical treatment, when the patient is diagnosed at a later stage. The aim of this study was to investigate if a surgical repair later than three months after injury may result in successful outcomes and patient satisfaction. There is evidence in literature that good results of treatment can be expected up to three months after the injury, but little is known of later treatment with cuff repair. 73 patients (75 shoulders), 58 males/17 females, mean age 59 (range 34-­‐72), who had undergone surgical intervention for TRCT between January 1999 to December 2011 at our clinic, were included in this study. Patients were assessed by MRI investigation, clinical examination, Western Ontario Rotator Cuff index (WORC), Oxford Shoulder Score, Constant-­‐Murley Score, EQ-­‐5D and patient subjective satisfaction at follow-­‐up. The patients treated surgically within three months ( < 12 weeks) after injury (39 cases) were compared with patients treated more than three months ( ≥ 12 weeks) after injury (36 cases). WORC was used as the primary outcome measure and the other variables as secondary. A senior consultant radiologist, blinded to patient category and clinical outcome, evaluated all MRI-­‐images. Rotator cuff integrity, presence of arthritis, fatty degeneration and muscle atrophy was evaluated in all cases. The average follow-­‐up time was 56 months (range 14-­‐149) and the average time from injury to repair was 16 weeks (range 3-­‐104). No statistically significant differences were found for any of the assessed parameters or scores between the two groups. The mean WORC score was 77 (early group, range 25-­‐ 100 and late group, range 27-­‐100) for both groups (p= 0.86), Constant-­‐Murley Score (p= 0.91), Oxford Shoulder Score (p= 0.79), EQ-­‐5D index (p= 0.86). Re-­‐tear frequency was 24% for both groups, and the patients with re-­‐tear reported less satisfaction with outcome. Discussion and conclusion: This study shows that surgical repair of TRCT performed later than three months after injury may result in good functional outcomes and patient satisfaction. However, this does not motivate an intentional delay in surgery when there is an indication for surgical repair as that delay may adversely affect the possibility to perform a repair. Our results show that surgeons may safely consider surgical repair even if a delay in diagnosis has occurred. A retrospective cohort study on 75 shoulders shows good functional result after traumatic rotator cuff tear (TRCT) treated surgically up to one year after the injury.

Keywords: traumatic rotator cuff injury, time to surgery, surgical outcome, retrospective cohort study

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Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

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Authors: M. Bilal Ishfaq, Adnan N. Qureshi

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COVID-19 is the most infectious disease these days, it was first reported in Wuhan, the capital city of Hubei in China then it spread rapidly throughout the whole world. Later on 11 March 2020, the World Health Organisation (WHO) declared it a pandemic. Since COVID-19 is highly contagious, it has affected approximately 219M people worldwide and caused 4.55M deaths. It has brought the importance of accurate diagnosis of respiratory diseases such as pneumonia and COVID-19 to the forefront. In this paper, we propose a hybrid approach for the automated detection of COVID-19 using medical imaging. We have presented the hybridization of manually extracted and convolutional features. Our approach combines Haralick texture features and convolutional features extracted from chest X-rays and CT scans. We also employ a minimum redundancy maximum relevance (MRMR) feature selection algorithm to reduce computational complexity and enhance classification performance. The proposed model is evaluated on four publicly available datasets, including Chest X-ray Pneumonia, COVID-19 Pneumonia, COVID-19 CTMaster, and VinBig data. The results demonstrate high accuracy and effectiveness, with 0.9925 on the Chest X-ray pneumonia dataset, 0.9895 on the COVID-19, Pneumonia and Normal Chest X-ray dataset, 0.9806 on the Covid CTMaster dataset, and 0.9398 on the VinBig dataset. We further evaluate the effectiveness of the proposed model using ROC curves, where the AUC for the best-performing model reaches 0.96. Our proposed model provides a promising tool for the early detection and accurate diagnosis of COVID-19, which can assist healthcare professionals in making informed treatment decisions and improving patient outcomes. The results of the proposed model are quite plausible and the system can be deployed in a clinical or research setting to assist in the diagnosis of COVID-19.

Keywords: COVID-19, feature engineering, artificial neural networks, radiology images

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Authors: Retno Supriyanti, Ahmad Chuzaeri, Yogi Ramadhani, A. Haris Budi Widodo

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The use of ultrasonography in the medical world has been very popular including the diagnosis of pregnancy. In determining pregnancy, ultrasonography has many roles, such as to check the position of the fetus, abnormal pregnancy, fetal age and others. Unfortunately, all these things still need to analyze the role of the obstetrician in the sense of image raised by ultrasonography. One of the most striking is the determination of gestational age. Usually, it is done by measuring the length of the fetus manually by obstetricians. In this study, we developed a computer-aided diagnosis for the determination of gestational age by measuring the length of the fetus automatically using edge detection method and image morphology. Results showed that the system is sufficiently accurate in determining the gestational age based image processing.

Keywords: computer aided diagnosis, gestational age, and diameter of uterus, length of fetus, edge detection method, morphology image

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Authors: Tse-An Pan, Sheng-Long Lee

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The effect of non-isothermal aging on the mechanical properties and corrosion resistance of Al-9Zn-2.3Mg-1.9Cu (AA7056) alloys was investigated. The results revealed that thick materials were limited to retrogression and re-aging treatment (RRA). It could not reach the retrogression temperature in the RRA treatment. Compared with the RRA treatment, the non-isothermal aging (NIA) treatment produced discontinuous precipitates at grain boundaries, while the intragranular precipitates were fine and dense. The strength was similar to that of the RRA treatment; the corrosion resistance of the alloy was significantly improved by NIA aging. NIA treatment was less affected by the thickness of the alloy. The difference between the actual temperature and the setting temperature of the alloy is minimal during the aging process. The combination of properties could overcome the fact that RRA treatment cannot handle thick materials.

Keywords: Al-Zn-Mg-Cu alloy, corrosion, retrogression, re-aging, non-isothermal aging

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Authors: Fadime Eroglu

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Acanthamoeba genus belongs to kingdom protozoa, and it is known as free-living amoebae. Acanthamoeba genus has been isolated from human bodies, swimming pools, bottled mineral water, contact lens solutions, dust, and soil. The members of the genus Acanthamoeba causes Acanthamoeba Keratitis which is a painful sight-threatening disease of the eyes. In recent years, the prevalence of Acanthamoeba keratitis has been high rate reported. The eight different Acanthamoeba species are known to be effective in Acanthamoeba keratitis. These species are Acanthamoeba castellanii, Acanthamoeba polyphaga, Acanthamoeba griffini, Acanthamoeba hatchetti, Acanthamoeba culbertsoni and Acanhtamoeba rhysodes. The conventional diagnosis of Acanthamoeba Keratitis has relied on cytological preparations and growth of Acanthamoeba in culture. However molecular methods such as real-time PCR has been found to be more sensitive. The real-time PCR has now emerged as an effective method for more rapid testing for the diagnosis of infectious disease in decade. Therefore, a real-time PCR assay for the detection of Acanthamoeba keratitis and Acanthamoeba species have been developed in this study. The 18S rRNA sequences from Acanthamoeba species were obtained from National Center for Biotechnology Information and sequences were aligned with MEGA 6 programme. Primers and probe were designed using Custom Primers-OligoPerfectTMDesigner (ThermoFisherScientific, Waltham, MA, USA). They were also assayed for hairpin formation and degree of primer-dimer formation with Multiple Primer Analyzer ( ThermoFisherScientific, Watham, MA, USA). The eight different ATCC Acanthamoeba species were obtained, and DNA was extracted using the Qiagen Mini DNA extraction kit (Qiagen, Hilden, Germany). The DNA of Acanthamoeba species were analyzed using newly designed primer and probe set in real-time PCR assay. The early definitive laboratory diagnosis of Acanthamoeba Keratitis and the rapid initiation of suitable therapy is necessary for clinical prognosis. The results of the study have been showed that new primer and probes could be used for detection and distinguish for Acanthamoeba species. These new developing methods are helpful for diagnosis of Acanthamoeba Keratitis.

Keywords: Acathamoeba Keratitis, Acanthamoeba species, fast diagnosis, Real-Time PCR

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Authors: Jaci Marie Mastrandrea, Rosario Haro

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Background: The National Comprehensive Cancer Network (NCCN) recommends that healthcare institutions have established processes for integrating palliative care (PC) into cancer treatment and that all cancer patients be screened for PC needs upon initial diagnosis as well as throughout the entire continuum of care (National Comprehensive Cancer Network, 2021). Early PC screening and intervention is directly associated with improved patient outcomes. The Sky Lakes Cancer Treatment Center (SLCTC) is an institution that has access to PC services yet does not have protocols in place for identifying patients with palliative needs or a standardized referral process. The aim of this quality improvement project was to improve early access to PC services by establishing a standardized screening and referral process for outpatient oncology patients. Method: The sample population included all adult patients with an oncology diagnosis who presented to the SLCTC for treatment during the project timeline. The “Palliative and Supportive Needs Assessment'' (PSNA) screening tool was developed from validated, evidence-based PC referral criteria. The tool was initially implemented using paper forms, and data was collected over a period of eight weeks. Patients were screened by nurses on the SLCTC oncology treatment team. Nurses responsible for screening patients received an educational inservice prior to implementation. Patients with a PSNA score of three or higher received an educational handout on the topic of PC and education about PC and symptom management. A score of five or higher indicates that PC referral is strongly recommended, and the patient’s EHR is flagged for the oncology provider to review orders for PC referral. The PSNA tool was approved by Sky Lakes administration for full integration into Epic-Beacon. The project lead collaborated with the Sky Lakes’ information systems team and representatives from Epic on the tool’s aesthetic and functionality within the Epic system. SLCTC nurses and physicians were educated on how to document the PSNA within Epic and where to view results. Results: Prior to the implementation of the PSNA screening tool, the SLCTC had zero referrals to PC in the past year, excluding referrals to hospice. Data was collected from the completed screening assessments of 100 patients under active treatment at the SLCTC. Seventy-three percent of patients met criteria for PC referral with a score greater than or equal to three. Of those patients who met referral criteria, 53.4% (39 patients) were referred for a palliative and supportive care consultation. Patients that were not referred to PC upon meeting criteria were flagged in EPIC for re-screening within one to three months. Patients with lung cancer, chronic hematologic malignancies, breast cancer, and gastrointestinal malignancy most frequently met the criteria for PC referral and scored highest overall on the scale of 0-12. Conclusion: The implementation of a standardized PC screening tool at the SLCTC significantly increased awareness of PC needs among cancer patients in the outpatient setting. Additionally, data derived from this quality improvement project supports the national recommendation for PC to be an integral component of cancer treatment across the entire continuum of care.

Keywords: oncology, palliative and supportive care, symptom management, outpatient oncology, palliative screening tool

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Authors: Deepika Bhalla, Raj Kumar Bansal, Hari Om Gupta

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Dissolved Gas Analysis (DGA) has been widely used for fault diagnosis in a transformer. Artificial neural networks (ANN) have high accuracy but are regarded as black boxes that are difficult to interpret. For many problems it is desired to extract knowledge from trained neural networks (NN) so that the user can gain a better understanding of the solution arrived by the NN. This paper applies a pedagogical approach for rule extraction from function approximating neural networks (REFANN) with application to incipient fault diagnosis using the concentrations of the dissolved gases within the transformer oil, as the input to the NN. The input space is split into subregions and for each subregion there is a linear equation that is used to predict the type of fault developing within a transformer. The experiments on real data indicate that the approach used can extract simple and useful rules and give fault predictions that match the actual fault and are at times also better than those predicted by the IEC method.

Keywords: artificial neural networks, dissolved gas analysis, rules extraction, transformer

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Authors: Mustafa Al-Yaseen, Haider Mohammed Mahdi, Haider Ali Al–Zahid, Nazar S. Haddad

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Background: Early diagnosis of musculoskeletal infections is of vital importance to avoid devastating complications. There is no single laboratory marker which is sensitive and specific in diagnosing these infections accurately. White blood cell count, erythrocyte sedimentation rate, and C-reactive protein are not specific as they can also be elevated in conditions other than bacterial infections. Materials Culture and sensitivity is not a true gold standard due to its varied positivity rates. Serum Procalcitonin is one of the new laboratory markers for pyogenic infections. The objective of this study is to assess the value of PCT in the diagnosis of soft tissue, bone, and joint infections. Patients and Methods: Patients of all age groups (seventy-four patients) with a diagnosis of musculoskeletal infection are prospectively included in this study. All patients were subjected to White blood cell count, erythrocyte sedimentation rate, C-reactive protein, and serum Procalcitonin measurements. A healthy non infected outpatient group (twenty-two patients) taken as a control group and underwent the same evaluation steps as the study group. Results: The study group showed mean Procalcitonin levels of 1.3 ng/ml. Procalcitonin, at 0.5 ng/ml, was (42.6%) sensitive and (95.5%) specific in diagnosing of musculoskeletal infections with (positive predictive value of 87.5% and negative predictive value of 48.3%) and (positive likelihood ratio of 9.3 and negative likelihood ratio of 0.6). Conclusion: Serum Procalcitonin, at a cut – off of 0.5 ng/ml, is a specific but not sensitive marker in the diagnosis of musculoskeletal infections, and it can be used effectively to rule in the diagnosis of infection but not to rule out it.

Keywords: procalcitonin, infection, labratory markers, musculoskeletal

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