RFFE – Random Forest Fuzzy Entropy for the classification of Diabetes Mellitus

Diabetes is a category of metabolic disease commonly known as a chronic illness. It causes the body to generate less insulin and raises blood sugar levels, leading to various issues and disrupting the functioning of organs, including the retinal, kidney and nerves. To prevent this, people with chronic illnesses require lifetime access to treatment. As a result, early diabetes detection is essential and might save many lives. Diagnosis of people at high risk of developing diabetes is utilized for preventing the disease in various aspects. This article presents a chronic illness prediction prototype based on a person's risk feature data to provide an early prediction for diabetes with Fuzzy Entropy random vectors that regulate the development of each tree in the Random Forest. The proposed prototype consists of data imputation, data sampling, feature selection, and various techniques to predict the disease, such as Fuzzy Entropy, Synthetic Minority Oversampling Technique (SMOTE), Convolutional Neural Network (CNN) with Stochastic Gradient Descent with Momentum (SGDM), Support Vector Machines (SVM), Classification and Regression Tree (CART), K-Nearest Neighbor (KNN), and Naïve Bayes (NB). This study uses the existing Pima Indian Diabetes (PID) dataset for diabetic disease prediction. The predictions' true/false positive/negative rate is investigated using the confusion matrix and the receiver operating characteristic area under the curve (ROCAUC). Findings on a PID dataset are compared with machine learning algorithms revealing that the proposed Random Forest Fuzzy Entropy (RFFE) is a valuable approach for diabetes prediction, with an accuracy of 98 percent

Detection and diabetic retinopathy grading using digital retinal images

Diabetic Retinopathy is an eye disorder that affects people suffering from diabetes. Higher sugar levels in blood leads to damage of blood vessels in eyes and may even cause blindness. Diabetic retinopathy is identified by red spots known as microanuerysms and bright yellow lesions called exudates. It has been observed that early detection of exudates and microaneurysms may save the patient’s vision and this paper proposes a simple and effective technique for diabetic retinopathy. Both publicly available and real time datasets of colored images captured by fundus camera have been used for the empirical analysis. In the proposed work, grading has been done to know the severity of diabetic retinopathy i.e. whether it is mild, moderate or severe using exudates and micro aneurysms in the fundus images. An automated approach that uses image processing, features extraction and machine learning models to predict accurately the presence of the exudates and micro aneurysms which can be used for grading has been proposed. The research is carried out in two segments; one for exudates and another for micro aneurysms. The grading via exudates is done based upon their distance from macula whereas grading via micro aneurysms is done by calculating their count. For grading using exudates, support vector machine and K-Nearest neighbor show the highest accuracy of 92.1% and for grading using micro aneurysms, decision tree shows the highest accuracy of 99.9% in prediction of severity levels of the disease

Analysis of Tongue Color-Associated Features among Patients with PCR-Confirmed COVID-19 Infection in Ukraine

Objective: To evaluate and systematize tongue color-related manifestations among patients with PCR-confirmed COVID-19 infection. Material and Methods: This retrospective study included analysis of tongue images obtained from patients with PCR-confirmed COVID-19 infection. Evaluation of coronavirus disease severity (mild, moderate, severe, critical) was provided, considering clinical symptomatology and results of laboratorial and instrumental diagnostic methods. Each picture was analyzed considering the parameters of color of the tongue and color of the tongue plaque by two dental specialists. Cochran-Armitage test for trend was used to evaluate associations between the tongue color and tongue plaque color, and coronavirus disease severity. Results: The most prevalent tongue colors were pale pink, red and dark red (burgundy color). A total of 64.29% of patients with mild disease demonstrated pale pink color of the tongue. Patients with moderate coronavirus disease were characterized with the adverse trend: 62.35% of them presented with red-colored tongue, while in 37.64% of cases, the tongue was pale pink. Severe COVID-19 patients, almost in 90% of the cases, had either red or burgundy color of the tongue. Conclusion: SARS-COV-2 infection is not manifested by tongue-targeted or tongue-specific signs and features; however, coronavirus disease itself provokes changes within the tongue color and tongue plaque color similar to those registered during other internal pathologies

Visual Impairment and Blindness

Blindness and vision impairment affect at least 2.2 billion people worldwide with most individuals having a preventable vision impairment. The majority of people with vision impairment are older than 50 years, however, vision loss can affect people of all ages. Reduced eyesight can have major and long-lasting effects on all aspects of life, including daily personal activities, interacting with the community, school and work opportunities, and the ability to access public services. This book provides an overview of the effects of blindness and visual impairment in the context of the most common causes of blindness in older adults as well as children, including retinal disorders, cataracts, glaucoma, and macular or corneal degeneration

Lectures on internal medicine propaedeutics

Курс лекцій для студентів третіх курсів медичних факультетів з пропедевтики внутрішньої медицини за англійською формою навчання на англійській мові. Розглядаються підхід, методи обстеження та основні клінічні синдроми пацієнтів з захворюваннями дихальної, серцево-судинної, травної, видільної, кістково-м’язової, сполучної, кров’яної та ендокринної систем.Lecture 1 Propaedeutics as an introduction to the clinic of internal medicine Lecture 2 Approach to the patient Lecture 3 Approach to the patient with disease of the respiratory system Lecture 4 Approach to the patient with disease of the cardiovascular system Lecture 5 Approach to the patient with gastrointestinal tract diseases Lecture 6 Approach to the Patient with diseases of the hepatobiliary tract and pancreas Lecture 7 Approach to the patient with affection and disease of the kidneys Lecture 8 Approach to the patient with affection and disease of the musculoskeletal system and connective tissue Lecture 9 Approach to the patient with affection and disease of the blood Lecture 10 Approach to the patient with affection and disease of the endocrine system Lecture 11 Syndromes of respiratory system diseases Lecture 12 Syndromes of cardiovascular system diseases Lecture 13 Syndromes of gastrointestinal tract diseases Lecture 14 Syndromes of hepatobiliary tract and exocrine pancreas diseases Lecture 15 Syndromes of kidneys diseases Lecture 16 Syndromes of the musculoskeletal system and connective tissue diseases Lecture 17 Syndromes of the blood system diseases Lecture 18 Syndromes of the endocrine system disease