Search results for: disease diagnosis

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: Jakub Młoźniak, Adam Szymański, Gabriela Stondzik, Dagny Krankowska, Tomasz Mikuła

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Nontuberculous mycobacteria (NTM) are bacterial species that cause diversely manifesting diseases mainly in immunocompromised patients. In people with HIV, NTM infection is an AIDS-defining disease and usually appears when the lymphocyte T CD4 count is below 50 cells/μl. The usage of antiretroviral therapy has decreased the prevalence of NTM among people with HIV, but the disease can still be observed especially among patients with late HIV diagnosis. Common presence in environment, human colonization, clinical similarity with tuberculosis and slow growth on culture makes NTM especially hard to diagnose. The study aimed to analyze the epidemiology and clinical course of NTM among patients with HIV. This study included patients with NTM and HIV admitted to our department between 2017 and 2023. Medical records of patients were analyzed and data on age, sex, median time from HIV diagnosis to identification of NTM infection, median CD4 count at NTM diagnosis, methods of determining NTM infection, type of species of mycobacteria identified, clinical symptoms and treatment course were gathered. Twenty-four patients (20 men, 4 women) with identified NTM were included in this study. Among them, 20 were HIV late presenters. The patients' median age was 40. The main symptoms which patients presented were fever, weight loss and cough. Pulmonary disease confirmed with positive cultures from sputum/bronchoalveolar lavage was present in 18 patients. M. avium was the most common species identified. M. marinum caused disseminated skin lesions in 1 patient. Out of all, 5 people were not treated for NTM caused by lack of symptoms and suspicion of colonization with mycobacterium. Concomitant tuberculosis was present in 6 patients. The median diagnostic time from HIV to NTM infections was 3.5 months. The median CD4 count at NTM identification was 69.5 cells/μl. Median NTM treatment time was 16 months but 7 patients haven’t finished their treatment yet. The most commonly used medications were ethambutol and clarithromycin. Among analyzed patients, 4 of them have died. NTM infections are still an important disease among patients who are HIV late presenters. This disease should be taken into consideration during the differential diagnosis of fever, weight loss and cough in people with HIV with lymphocyte T CD4 count <100 cells/μl. Presence of tuberculosis does not exclude nontuberculous mycobacterium coinfection.

Keywords: mycobacteriosis, HIV, late presenter, epidemiology

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Authors: Praveen S. Muthukumarana, Achala C. Aponso

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A large percentage of global crop harvest is lost due to crop diseases. Timely identification and treatment of crop diseases is difficult in many developing nations due to insufficient trained professionals in the field of agriculture. Many crop diseases can be accurately diagnosed by visual symptoms. In the past decade, deep learning has been successfully utilized in domains such as healthcare but adoption in agriculture for plant disease detection is rare. The literature shows that models trained with popular datasets such as PlantVillage does not generalize well on real world images. This paper attempts to find out how to make plant disease identification models that generalize well with real world images.

Keywords: agriculture, convolutional neural network, deep learning, plant disease classification, plant disease detection, plant disease diagnosis

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Authors: Jyoti Agrawal

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Introduction: Renal diseases in children and young adult can be difficult to diagnose early as it may present only with few symptoms, tends to have different course than adult and respond variously to different treatment. The pattern of renal disease in children is different from developing countries as compared to developed countries. Methods: This study was a hospital based prospective observational study carried from March, 2014 to February 2015 at BP Koirala institute of health sciences. Patients with renal disease, both inpatient and outpatient from birth to 14 years of age were enrolled in the study. The diagnosis of renal disease was be made on clinical and laboratory criteria. Results: Total of 120 patients were enrolled in our study which contributed to 3.74% % of total admission. The commonest feature of presentation was edema (75%), followed by fever (65%), hypertension (60%), decreased urine output (45%) and hematuria (25%). Most common diagnosis was acute glomerulonephritis (40%) followed by Nephrotic syndrome (25%) and urinary tract infection (25%). Renal biopsy was done for 10% of cases and most of them were steroid dependent nephrotic syndrome. 5% of our cases expired because of multiorgan dysfunction syndrome, sepsis and acute kidney injury. Conclusion: Renal disease contributes to a large part of hospital pediatric admission as well as mortality and morbidity to the children.

Keywords: glomerulonephritis, nephrotic syndrome, renal disease, urinary tract infection

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Authors: James Boag

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The needs of people with a diagnosis of dementia and their carers and families are physical, psychosocial, and psychological and begin at the time of diagnosis. There is frequently a lack of emotional support and counselling. Care- giving support is required from the presentation of the first symptoms of dementia until death. Alzheimer's disease begins decades before the clinical symptoms begin to appear, and in many cases, it remains undiagnosed, or diagnosed too late for any possible interventions to have any effect. However, if an incorrect diagnosis is given, it may result in a person being treated, without effect, for a type of dementia they do not have and delaying the interventions they should have received. Being diagnosed with dementia can cause emotional distress to the person, and physical and emotional support is needed, which will become more important as the disease progresses. The severity of the patient's dementia and their symptoms has a bearing of the impact on the carer and the support needed. A lack of insight and /or a denial of the diagnosis, grief, reacting to anticipated future losses, and coping methods to maximise the disease outcome, are things that should be addressed. Because of the stigma, it is important for carers not to lose contact with family and others because social isolation leads to depression and burnout. The impact on a carer's well- being and quality of life can be influenced by the severity of the illness, its type of dementia, its symptoms, healthcare support, financial and social status, career, age, health, residential setting, and relationship to the patient. Carer burnout due to lack of support leads to people diagnosed with dementia being put into residential care prematurely. Often dementia is not recognised as a terminal illness, limiting the ability of the person diagnosed with dementia and their carers to work on advance care planning and getting access to palliative and other support. Many carers have been satisfied with the physical support they were given in their everyday life, however, it was agreed that there was an immense unmet need for psychosocial support, especially after diagnosis and approaching end of life. Providing continuity and coordination of care is important. Training is necessary for providers to understand that every case is different, and they should understand the complexities. Grief, the emotional response to loss, is suffered during the progression of the disease and long afterwards, and carers should continue to be supported after the death of the person they were caring for.

Keywords: dementia, caring, challenges, needs

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Authors: Robert Krause

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Primary progressive aphasia (PPA) is a neurodegenerative disease similar to frontotemporal and semantic dementia, while having a different clinical image and anatomic pathology topography. Nonetheless, they are often included under an umbrella term: frontotemporal lobar degeneration (FTLD). In the study, examples of diagnosing PPA are presented through the multidisciplinary lens of specialists from different fields (neurologists, psychiatrists, clinical speech therapists, clinical neuropsychologists and others) using a variety of diagnostic tools such as MR, PET/CT, genetic screening and neuropsychological and logopedic methods. Thanks to that, specialists can get a better and clearer understanding of PPA diagnosis. The study summarizes the concrete procedures and results of different specialists while diagnosing PPA in a patient of younger middle age and illustrates the importance of multidisciplinary approach to differential diagnosis of PPA.

Keywords: primary progressive aphasia, etiology, diagnosis, younger middle age

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Authors: Sally Shepherd, Richard De Boer, Craig Murphy

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Background: Invasive lobular carcinoma (ILC) can metastasize to atypical sites within the peritoneal cavity, gastrointestinal, or genitourinary tract. Management varies depending on the symptom presentation, extent of disease burden, particularly if the primary disease is occult, and patient wishes. Case Series: 6 patients presented with general surgical presentations of ILC, including incomplete large bowel obstruction, cholecystitis, persistent lower abdominal pain, and faecal incontinence. 3 were diagnosed with their primary and metastatic disease in the same presentation, whilst 3 patients developed metastasis from 5 to 8 years post primary diagnosis of ILC. Management included resection of the metastasis (laparoscopic cholecystectomy), excision of the primary (mastectomy and axillary clearance), followed by a combination of aromatase inhibitors, biologic therapy, and chemotherapy. Survival post diagnosis of metastasis ranged from 3 weeks to 7 years. Conclusion: Metastatic ILC must be considered with any gastrointestinal or genitourinary symptoms in patients with a current or past history of ILC. Management may not be straightforward to chemotherapy if the acute pathology is resulting in a surgically resectable disease.

Keywords: breast cancer, gastrointestinal metastasis, invasive lobular carcinoma, metastasis

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Authors: Shalini Tripathi, Pardeep Kumar

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The method of translating observed symptoms into disease names is known as disease diagnosis. The ability to solve clinical problems in a complex manner is critical to a doctor's effectiveness in providing health care. The accuracy of his or her expertise is crucial to the survival and well-being of his or her patients. Artificial Intelligence (AI) has a huge economic influence depending on how well it is applied. In the medical sector, human brain-simulated intellect can help not only with classification accuracy, but also with reducing diagnostic time, cost and pain associated with pathologies tests. In light of AI's present and prospective applications in the biomedical, we will identify them in the paper based on potential benefits and risks, social and ethical consequences and issues that might be contentious but have not been thoroughly discussed in publications and literature. Current apps, personal tracking tools, genetic tests and editing programmes, customizable models, web environments, virtual reality (VR) technologies and surgical robotics will all be investigated in this study. While AI holds a lot of potential in medical diagnostics, it is still a very new method, and many clinicians are uncertain about its reliability, specificity and how it can be integrated into clinical practice without jeopardising clinical expertise. To validate their effectiveness, more systemic refinement of these implementations, as well as training of physicians and healthcare facilities on how to effectively incorporate these strategies into clinical practice, will be needed.

Keywords: Artificial Intelligence, medical diagnosis, virtual reality, healthcare ethical implications 

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Authors: Sanjeev Kumar Shukla, Govind Singh, Prabhat Pant Shahzad Ahmad

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Background: Graves’ disease is an autoimmune disorder with a genetic predisposition, and CD40 plays a pathogenic role in various autoimmune diseases. A single nucleotide polymorphism at position –1 of the Kozak sequence of the 5 untranslated regions of the CD40 gene of exon 1 has been reported to be associated with the development of Graves’ Disease. Objective: The aim of the present study was to investigate whether CD40 gene polymorphism confers susceptibility to Graves’ disease in the Kumaon region. CD40 gene polymorphisms were studied in Graves’ Disease patients (n=50) and healthy control subjects without anti-thyroid autoantibodies or a family history of autoimmune disorders (n=50). Material and Method: CD40 gene polymorphisms were studied in fifty Graves’ Disease patients and fifty healthy control subjects. All samples were collected from STG Hospital, Haldwani, Nainital. A C/T polymorphism at position –1 of the CD40 gene was measured using the polymerase chain reaction-restriction fragment length polymorphism. Results: There was no significant difference in allele or genotype frequency of the CD40 SNP between Graves’ Disease and control subjects. There was a significant decrease in the TT genotype frequency in the Graves’ Disease patients who developed Graves’ Disease after 40 years old than those under 40 years of age. These data suggest that the SNP of the CD40 gene is associated with susceptibility to the later onset of Graves’ Disease. Conclusion: The CD40 gene was a different susceptibility gene for Graves’ Disease within certain families because it was both linked and associated with Graves’ Disease.

Keywords: autoimmune diseases, pathogenesis, diagnosis, therapy

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Authors: Zahra Rakhshan Masoudi, Sona Rostampour Yasouri

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Considering that the only way to save the lives of patients and healthy people who have suffered sudden accidents is blood transfusion, what is important is the presence of the known HCV virus as the most important cause of the disease after blood transfusion. HCV is one of the major global problems, and its transmission through blood causes life-threatening complications and extensive legal, social and economic consequences. On the one hand, unfortunately, there is still no effective vaccine available to prevent HCV. In Iran, the exact statistics of the prevalence of this disease have not yet been fully announced. The main purpose of this study is to investigate the prevalence rate and rapid diagnosis of HCV among those who refer to laboratory centers in Tehran. From spring to winter of 1401 (2022-2023), 2166 blood samples were collected from laboratory centers in Tehran. Blood samples were evaluated for the presence of HCV by Electrochemiluminescence (ECL) and PCR techniques along with specific HCV primers. In general, 36 samples (1.6%) were tested positive by the mentioned techniques. The results indicated that the ECL technique is a sensitive and specific diagnostic method for detecting HCV in the early stages of the disease and can be very helpful and provide the possibility of starting the treatment steps to prevent the exacerbation of the disease earlier. Also, the results of PCR technique showed that PCR is an accurate, sensitive and fast method for definitive diagnosis of HCV. It seems that the incidence rate of this disease is increasing in Iran, and investigating the spread of the disease throughout Iran for a longer period of time in the continuation of our research can be helpful in the future to take the necessary measures to prevent the transmission of the disease to people and the rapid onset Treatment steps for patients with HCV should be carried out.

Keywords: electrochemiluminescence, HCV, PCR, prevalence

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Authors: Ilker Ali Ozkan

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In this study, an artificial neural network model has been developed to estimate chronic kidney failure which is a common disease. The patients’ age, their blood and biochemical values, and 24 input data which consists of various chronic diseases are used for the estimation process. The input data have been subjected to preprocessing because they contain both missing values and nominal values. 147 patient data which was obtained from the preprocessing have been divided into as 70% training and 30% testing data. As a result of the study, artificial neural network model with 25 neurons in the hidden layer has been found as the model with the lowest error value. Chronic kidney failure disease has been able to be estimated accurately at the rate of 99.3% using this artificial neural network model. The developed artificial neural network has been found successful for the estimation of chronic kidney failure disease using clinical data.

Keywords: estimation, artificial neural network, chronic kidney failure disease, disease diagnosis

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Authors: H. Al-Awaisi, M. H. Al-Azri, S. Al-Rasbi, M. Al-Moundhri

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Breast cancer is the most common cancer among females worldwide. It is also the most common cancer among females in Oman with 100 new breast cancer cases diagnosed every year. It has been found that breast cancer have a devastating effect on women’s life. Women diagnosed with breast cancer might develop negative attitudes towards the illness and their bodies. They might also suffer from psychological ailments such as depression. Despite the evidence on the impact of breast cancer diagnosis on women, there was no study found to explore the impact of breast cancer diagnosis among women in Oman. A phenomenological qualitative study was conducted to explore the impact of breast cancer diagnosis on Omani women. Data was collected through semi-structured individual interviews with 11 Omani women diagnosed with breast cancer. Interviews were transcribed verbatim and data were analyzed thematically. From the data, there are four main themes identified in relation to the impact of cancer diagnosis on Omani women. These are 'shock and disbelieve', 'a death sentence', “uncertain future” and “social stigma”. At the time of interviews, all participants had advanced breast cancer with some participants having metastatic disease. The impact of the word “cancer” had a profound and catastrophic effect on the women and their close relatives. In conclusion, breast cancer diagnosis was shocking and mainly perceived as a death sentence by Omani women with uncertain future and social stigma. Regardless of age, maternal status and education level, it is evident that Omani women participated in this study lacked awareness about breast cancer diagnosis, treatment and prognosis.

Keywords: breast cancer, coping, diagnosis, Oman, women

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Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

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Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

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Authors: Roseline Oghogho Osaseri, Osaseri E. I.

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Lassa fever is an epidemic hemorrhagic fever caused by the Lassa virus, an extremely virulent arena virus. This highly fatal disorder kills 10% to 50% of its victims, but those who survive its early stages usually recover and acquire immunity to secondary attacks. One of the major challenges in giving proper treatment is lack of fast and accurate diagnosis of the disease due to multiplicity of symptoms associated with the disease which could be similar to other clinical conditions and makes it difficult to diagnose early. This paper proposed an Adaptive Neuro Fuzzy Inference System (ANFIS) for the prediction of Lass Fever. In the design of the diagnostic system, four main attributes were considered as the input parameters and one output parameter for the system. The input parameters are Temperature on admission (TA), White Blood Count (WBC), Proteinuria (P) and Abdominal Pain (AP). Sixty-one percent of the datasets were used in training the system while fifty-nine used in testing. Experimental results from this study gave a reliable and accurate prediction of Lassa fever when compared with clinically confirmed cases. In this study, we have proposed Lassa fever diagnostic system to aid surgeons and medical healthcare practictionals in health care facilities who do not have ready access to Polymerase Chain Reaction (PCR) diagnosis to predict possible Lassa fever infection.

Keywords: anfis, lassa fever, medical diagnosis, soft computing

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Authors: Eva Karaskova, Jana Volejnikova, Dusan Holub, Maria Velganova-Veghova, Michaela Spenerova, Dagmar Pospisilova

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Background: Hepcidin is the central regulator of iron metabolism. Its production is mainly affected by an iron deficiency and the presence of inflammatory activity in the body. The aim of this study was to compare serum hepcidin levels in paediatric patients with newly diagnosed inflammatory bowel disease and hepcidin levels during maintenance therapy, correlate changes of serum hepcidin levels with selected markers of iron metabolism and inflammation and type of provided treatment. Methods: Children with newly diagnosed Crohn's disease (CD) and ulcerative colitis (UC) were included in this prospective study. Blood and stool samples were collected before treatment (baseline). Serum hepcidin, hemoglobin levels, platelet counts, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), interleukin-6 (IL 6), ferritin, iron, soluble transferrin receptors, and fecal calprotectin were assessed. The same parameters were measured and compared with the baseline levels in the follow-up period, during maintenance therapy (average of 39 months after diagnosis). Results: Patients with CD (n=30) had higher serum hepcidin levels (expressed as a median and interquartile range) at diagnosis than subjects with UC (n=13). These levels significantly decreased during the follow-up (from 36.5 (11.5-79.6) ng/ml to 2.1 (0.9-6.7) ng/ml). Contrarily, no significant serum hepcidin level changes were observed in UC (from 5.4 (3.4-16.6) ng/ml to 4.8 (0.9-8.1) ng/ml). While in children with CD hepcidin level dynamics correlated with disease activity and inflammatory markers (ESR, CRP), an only correlation with serum iron levels was observed in patients with UC. Conclusion: Children with CD had higher serum hepcidin levels at diagnosis compared to subjects with UC. Decrease of serum hepcidin in the CD group during anti-inflammatory therapy has been observed, whereas low hepcidin levels in children with UC have remained unchanged. Acknowledgment: This study was supported by grant MH CZ–DRO (FNOl, 00098892).

Keywords: children, Crohn's disease, ulcerative colitis, anaemia, hepcidin

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Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

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Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

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Authors: Khenenou Tarek, Benzaoui Hassina, Melizi Mohamed

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The diagnosis requires a background of current knowledge in the field and also complementary means in which the laboratory occupies the central place for a better investigation. A correct diagnosis allows to establish the most appropriate treatment as soon as possible and avoids both the economic losses associated with mortality and growth retardation often observed in poultry furthermore it may reduce the high cost of treatment. Epedemiologic survey, hematologic and histopathologic study’s are three aspects of diagnosis heavily used in both human and veterinary pathology and the advanced researches in human medicine would be exploited to be applied in veterinary medicine with given modification .Whereas, the diagnostic methods in the east of Algeria are limited to the clinical signs and necropsy finding. Therefore, the diagnosis is based simply on the success or the failure of the therapeutic methods (therapeutic diagnosis).

Keywords: chicken, diagnosis, hematology, histopathology

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Authors: Abdolreza Esmaeilzadeh, Mehri Mirzaei

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Objective: Rheumatic disease is a chronic disease that causes pain, stiffness, swelling and limited motion and function of many joints. RA is the most common form of autoimmune arthritis, affecting more than 1.3 million Americans. Of these, about 75% are women. Materials and Methods: This study was formed due to the misconception about ANA test, which is frequently performed with methods based upon solid phase as ELISA. This experiment was conducted on 430 patients, with clinical symptoms that are likely affected with rheumatic diseases, simultaneously by means of ANA and FANA. Results: 36 cases (8.37%) of patients, despite positive ANA, have demonstrated negative results via Indirect Immunofluorescence Assay (IIFA), (false positive). 116 cases (27%) have demonstrated negative ANA results, by means of the ELISA technique, although they had positive IIFA results. Conclusion: Other advantages of IIFA are antibody titration and specific pattern detection that have the capability of distinguishing positive dsDNA results. According to the restrictions and false negative cases, in patients, IIFA test is highly recommended for these disease's diagnosis.

Keywords: autoimmune disease, IIFA, EIA, rheumatic disease

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Authors: Bharti Chogtu Magazine, Dhanya Soodana Mohan, Shruti Nair, Tanwi Trushna

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The study was undertaken to analyse the cardiovascular drugs being prescribed in patients with concomitant reactive airway disease and hypertension or ischemic heart diseases (IHD). Also, the effect of beta-blockers on respiratory symptoms in these patients was recorded. Data was collected from medical records of patients with reactive airway disease and concomitant hypertension and IHD. It included demographic details of the patients, diagnosis, drugs prescribed and the patient outcome regarding the exacerbation of asthma symptoms with intake of beta blockers. Medical records of 250 patients were analysed.13% of patients were prescribed beta-blockers. 12% of hypertensive patients, 16.6% of IHD patients and 20% of patients with concomitant hypertension and IHD were prescribed beta blockers. Of the 33 (13%) patients who were on beta-blockers, only 3 patients had an exacerbation of bronchial asthma symptoms. Cardioselective beta-blockers under supervision appear to be safe in patients with reactive airway disease and concomitant hypertension and IHD.

Keywords: beta blockers, hypertension, ischemic heart disease, asthma

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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: Leonardo C. Pacheco-Londoño, Nataly J. Galan-Freyle, Lisandro Pacheco-Lugo, Antonio Acosta, Elkin Navarro, Gustavo Aroca-Martínez, Karin Rondón-Payares, Samuel P. Hernández-Rivera

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In our Life Science Research Center of the University Simon Bolivar (LSRC), one of the focuses is the diagnosis and prognosis of different diseases; we have been implementing the use of gold nanoparticles (Au-NPs) for various biomedical applications. In this case, Au-NPs were used for Surface-Enhanced Raman Spectroscopy (SERS) in different diseases' diagnostics, such as Lupus Nephritis (LN), hypertension (H), preeclampsia (PC), and others. This methodology is proposed for the diagnosis of each disease. First, good signals of the different metabolites by SERS were obtained through a mixture of urine samples and Au-NPs. Second, PLS-DA models based on SERS spectra to discriminate each disease were able to differentiate between sick and healthy patients with different diseases. Finally, the sensibility and specificity for the different models were determined in the order of 0.9. On the other hand, a second methodology was developed using machine learning models from all data of the different diseases, and, as a result, a discriminant spectral map of the diseases was generated. These studies were possible thanks to joint research between two university research centers and two health sector entities, and the patient samples were treated with ethical rigor and their consent.

Keywords: SERS, Raman, PLS-DA, diseases

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Authors: Ecem Deniz Kırkpantur, Ozge Ecmel Onur, Tuba Cimilli Ozturk, Ebru Unal Akoglu

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Moyamoya disease is a unique chronic progressive cerebrovascular disease characterized by bilateral stenosis or occlusion of the arteries around the circle of Willis with prominent arterial collateral circulation. The occurrence of Moyamoya disease is related to immune, genetic and other factors. There is no curative treatment for Moyamoya disease. Secondary prevention for patients with symptomatic Moyamoya disease is largely centered on surgical revascularization techniques. We present here a 62-year old male presented with headache and vision loss for 2 days. He was previously diagnosed with hypertension and glaucoma. On physical examination, left eye movements were restricted medially, both eyes were hyperemic and their movements were painful. Other neurological and physical examination were normal. His vital signs and laboratory results were within normal limits. Computed tomography (CT) showed dilated vascular structures around both lateral ventricles and atherosclerotic changes inside the walls of internal carotid artery (ICA). Magnetic resonance imaging (MRI) and angiography (MRA) revealed dilated venous vascular structures around lateral ventricles and hyper-intense gliosis in periventricular white matter. Ischemic gliosis around the lateral ventricles were present in the Digital Subtracted Angiography (DSA). After the neurology, ophthalmology and neurosurgery consultation, the patient was diagnosed with Moyamoya disease, pulse steroid therapy was started for vision loss, and super-selective DSA was planned for further investigation. Moyamoya disease is a rare condition, but it can be an important cause of stroke in both children and adults. It generally affects anterior circulation, but posterior cerebral circulation may also be affected, as well. In the differential diagnosis of acute vision loss, occipital stroke related to Moyamoya disease should be considered. Direct and indirect surgical revascularization surgeries may be used to effectively revascularize affected brain areas, and have been shown to reduce risk of stroke.

Keywords: headache, Moyamoya disease, stroke, visual loss

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Authors: Mahdi Bazarganigilani

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Aortic enlargement, also known as an aortic aneurysm, can occur when the walls of the aorta become weak. This disease can become deadly if overlooked and undiagnosed. In this paper, a computer-aided diagnosis (CAD) system was introduced to accurately diagnose aortic enlargement from chest x-ray images. An enhanced convolutional neural network (CNN) was employed and then trained by transfer learning by using three different main areas from the original images. The areas included the left lung, heart, and right lung. The accuracy of the system was then evaluated on 1001 samples by using 4-fold cross-validation. A promising accuracy of 90% was achieved in terms of the F-measure indicator. The results showed using different areas from the original image in the training phase of CNN could increase the accuracy of predictions. This encouraged the author to evaluate this method on a larger dataset and even on different CAD systems for further enhancement of this methodology.

Keywords: computer-aided diagnosis systems, aortic enlargement, chest X-ray, image processing, convolutional neural networks

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Authors: Arrate Barrenechea Garro

Abstract:

Background: Bilingualism has been shown to enhance cognitive reserve and potentially delay the onset of dementia symptoms. This study investigates the impact of bilingualism on cognitive reserve and the age of diagnosis in Parkinson's Disease (PD). Methodology: The study involves 16 non-demented monolingual PD patients and 12 non-demented bilingual PD patients, matched for age, sex, and years of education. All participants are native Spanish speakers, with Spanish as their first language (L1). Cognitive performance is assessed through a neuropsychological examination covering all cognitive domains. Cognitive reserve is measured using the Cognitive Reserve Index Questionnaire (CRIq), while language proficiency is evaluated using the Bilingual Language Profile (BLP). The age at diagnosis is recorded for both monolingual and bilingual patients. Results: Bilingual PD patients demonstrate higher scores on the CRIq compared to monolingual PD patients, with significant differences between the groups. Furthermore, there is a positive correlation between cognitive reserve (CRIq) and the utilization of the second language (L2) as indicated by the BLP. Bilingual PD patients are diagnosed, on average, three years later than monolingual PD patients. Conclusion: Bilingual PD patients exhibit higher levels of cognitive reserve compared to monolingual PD patients, as indicated by the CRIq scores. The utilization of the second language (L2) is positively correlated with cognitive reserve. Bilingual PD patients are diagnosed with PD, on average, three years later than monolingual PD patients. These findings suggest that bilingualism may contribute to cognitive reserve and potentially delay the onset of clinical symptoms associated with PD. This study adds to the existing literature supporting the relationship between bilingualism and cognitive reserve. Further research in this area could provide valuable insights into the potential protective effects of bilingualism in neurodegenerative disorders.

Keywords: bilingualis, cogntiive reserve, diagnosis, parkinson's disease

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Authors: Alice Huffman, Joseph Hartland, Sam Gibbs

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Dermatology is often a neglected specialty in low-resource settings, despite the high morbidity associated with skin disease. This becomes even more significant when associated with HIV infection, as dermatological conditions are more common and aggressive in HIV positive patients. African countries have the highest HIV infection rates and skin conditions are frequently misdiagnosed and mismanaged, because of a lack of dermatological training and educational material. The frequent lack of diagnostic tests in the African setting renders basic clinical skills all the more vital. This project aimed to improve diagnosis and treatment of skin disease in the HIV population in a district hospital in Malawi. A basic dermatological clinical tool was developed and produced in collaboration with local staff and based on available literature and data collected from clinics. The aim was to improve diagnostic accuracy and provide guidance for the treatment of skin disease in HIV positive patients. A literature search within Embase, Medline and Google scholar was performed and supplemented through data obtained from attending 5 Antiretroviral clinics. From the literature, conditions were selected for inclusion in the resource if they were described as specific, more prevalent, or extensive in the HIV population or have more adverse outcomes if they develop in HIV patients. Resource-appropriate treatment options were decided using Malawian Ministry of Health guidelines and textbooks specific to African dermatology. After the collection of data and discussion with local clinical and pharmacy staff a list of 15 skin conditions was included and a booklet created using the simple layout of a picture, a diagnostic description of the disease and treatment options. Clinical photographs were collected from local clinics (with full consent of the patient) or from the book ‘Common Skin Diseases in Africa’ (permission granted if fully acknowledged and used in a not-for-profit capacity). This tool was evaluated by the local staff, alongside an educational teaching session on skin disease. This project aimed to reduce uncertainty in diagnosis and provide guidance for appropriate treatment in HIV patients by gathering information into one practical and manageable resource. To further this project, we hope to review the effectiveness of the tool in practice.

Keywords: dermatology, HIV, Malawi, skin disease

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Authors: A. A. M. A. S. S. Perera, L. A. Ranasinghe, T. K. H. Nimeshika, D. M. Dhanushka Dissanayake, Namalie Walgampaya

Abstract:

Nowadays, skin fungal diseases are mostly found in people of tropical countries like Sri Lanka. A skin fungal disease is a particular kind of illness caused by fungus. These diseases have various dangerous effects on the skin and keep on spreading over time. It becomes important to identify these diseases at their initial stage to control it from spreading. This paper presents an automated skin fungal disease identification system implemented to speed up the diagnosis process by identifying skin fungal infections in digital images. An image of the diseased skin lesion is acquired and a comprehensive computer vision and image processing scheme is used to process the image for the disease identification. This includes colour analysis using RGB and HSV colour models, texture classification using Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix and Local Binary Pattern, Object detection, Shape Identification and many more. This paper presents the approach and its outcome for identification of four most common skin fungal infections, namely, Tinea Corporis, Sporotrichosis, Malassezia and Onychomycosis. The main intention of this research is to provide an automated skin fungal disease identification system that increase the diagnostic quality, shorten the time-to-diagnosis and improve the efficiency of detection and successful treatment for skin fungal diseases.

Keywords: Circularity Index, Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix, Local Binary Pattern, Object detection, Ring Detection, Shape Identification

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Authors: Aran Abd Al Rahman

Abstract:

Joubert syndrome regards as a congenital cerebellar ataxia caused by autosomal recessive carried on X chromosome. The disease diagnosed by brain imaging—the so-called molar tooth sign. Neurological signs were present from the neonatal period and include hypotonia progressing to ataxia, global developmental delay, ocular motor apraxia, and breathing dysregulation. These signs are variably associated with multiorgan involvement, mainly of the retina, kidneys, skeleton, and liver. 30 causative genes have been identified so far, all of which encode for proteins of the primary cilium or its apparatus, The purpose of our project was to detect the mutant gene (INPP5E gene) which cause Joubert syndrome. There were many methods used for diagnosis such as MRI and CT- scan and molecular diagnosis by doing ARMS PCR for detection of mutant gene that we were used in this research project. In this research for individual family which reported, the two children with parents, the two children were affected and were carrier.

Keywords: Joubert syndrome, genetic disease, Kurdistan region, Sulaimani

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Authors: Ali Berkan Ural

Abstract:

This paper presents the analysis, evaluation, and pre-diagnosis of early stage breast based diagnostic problems (breast cancer, nodulesorlumps) by Computer Aided Diagnosing (CAD) system from mammogram radiological images. According to the statistics, the time factor is crucial to discover the disease in the patient (especially in women) as possible as early and fast. In the study, a new algorithm is developed using advanced image processing and deep learning method to detect and classify the problem at earlystagewithmoreaccuracy. This system first works with image processing methods (Image acquisition, Noiseremoval, Region Growing Segmentation, Morphological Operations, Breast BorderExtraction, Advanced Segmentation, ObtainingRegion Of Interests (ROIs), etc.) and segments the area of interest of the breast and then analyzes these partly obtained area for cancer detection/lumps in order to diagnosis the disease. After segmentation, with using the Spectrogramimages, 5 different deep learning based methods (specified Convolutional Neural Network (CNN) basedAlexNet, ResNet50, VGG16, DenseNet, Xception) are applied to classify the breast based problems.

Keywords: computer aided diagnosis, breast cancer, region growing, segmentation, deep learning

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Authors: Meriche Hacene

Abstract:

Introduction: Celiac disease (CD) is a chronic immune-mediated enteropathy triggered by gluten found in wheat or oats or rye. Celiac disease is associated with the HLA-DQ2 and HLA-DQ8 susceptibility alleles. This association with the HLA DQ2/DQ8 molecules confirmed the responsibility of genetic factors that intervene in the triggering of the autoimmune process of this condition. Objective: To evaluate the results of HLA DQ2 and HLA DQ8 typing of 40 patients suspected of having CD by PCR-SSP (Polymerase Chain Reaction Sequence Specific Primers). Material and method : 40 patients suspected of celiac disease with IgA transglutaminase serology (-) and duodenal biopsy (+). HLADR/DQ PCR-SSP (fluogen-innotrain) typing was carried out. Results : The average age of adults was 40 years, children: 4 years, the sex ratio was 1M/3F. In our patients the HLA DQ2 allele is found with a frequency of 75%, the DQ8 with a frequency of 25%, 17.5% were HLA-DQ2 homozygous and 15% were HLADQ2/HLADQ8. In our series, HLADQ2, DQ8 are found in almost all patients with a frequency of 95%. 30% of patients in our study had associated positivity of HLA-DRB3, DRB4 or DRB5 alleles. Conclusion : A high prevalence of positivity of HLADQ2 alleles at the expense of HLA DQ8 was found, which is consistent with literature data. These molecules constitute an additional marker for screening and diagnosis of CD.

Keywords: HLA typing, coeliac disease, HLA DQ 2, HLA DQ8

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