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Diabetes self-management relies on the blood glucose prediction as it allows taking suitable actions to prevent low or high blood glucose level. In this paper, we propose a deep learning neural network model for blood glucose prediction. The model is a sequential one using a Long- Short-Term Memory (LSTM) layer with two fully connected layers. Several experiments were carried out over data of 10 diabetic...
UF-EMG test, in which non-invasive uroflowmetry (UF) and electromyography (EMG) signals are simultaneously recorded, is frequently used in children diagnosed with lower urinary tract dysfunction disease (AUSD) and its treatment. In the literature, independent (single) UF signals and integrated (dual) UF-EMG signals are graded many times but there is no classification study of UF-EMG integrated signals...
Heart disease is a deadly disease that large population of people around the world suffers from. When considering death rates and large number of people who suffers from heart disease, it is revealed how important early diagnosis of heart disease. Traditional way of diagnosis is not sufficient for such an illness. Developing a medical diagnosis system based on machine learning for prediction of heart...
Every organism emits energy around it which comprises UV-radiation, EM-radiation, infrared and thermal radiation. This energy around human body represents health condition of the subject under study. These energy fields are called as aura of the body under consideration. Several types of equipments are there to capture such energy. Kirlian camera captures the distribution of energy radiation around...
This research describes skin disease recognition by using neural network which based on the texture analysis. There are many skin diseases which have a lot of similarities in their symptoms, such as Measles (rubeola), German measles (rubella), and Chickenpox etc. In general, these diseases have similarities in pattern of infection and symptoms such as redness and rash. Diagnosis and recognition of...
Automated, efficient and accurate classification of skin diseases using digital images of skin is very important for bio-medical image analysis. Various techniques have already been developed by many researchers. In this work, a technique based on meta-heuristic supported artificial neural network has been proposed to classify images. Here 3 common skin diseases have been considered namely angioma,...
A stroke occurs when the blood supply to a person's brain is interrupted or reduced. The stroke deprives person's brain of oxygen and nutrients, which can cause brain cells to die. Numerous works have been carried out for predicting various diseases by comparing the performance of predictive data mining technologies. In this work, we compare different methods with our approach for stroke prediction...
This work describes the application of portable Raman spectroscopy coupled with Artificial Neural Networks (ANN), to discern between diabetic patients and healthy controls, with a high degree of accuracy (Acc=89.7±6.6%). This technique is relatively low-cost, simple and comfortable for the patient, yielding rapid diagnosis. These features make our method a promising screening tool for identifying...
Diabetes is one of the most common metabolic diseases and the statistics show that one in eleven adults has diabetes, but one in two adults with diabetes is undiagnosed, and in 2040 one in 10 adults will have diabetes. In this paper is proposed a hybrid Adaptive Neuro-Fuzzy Inference System (ANFIS) model for classifying patients with diabetes based on data sets with diabetic patients (Pima Indians...
Medical decision-making can be a difficult task even for human experts. They can be helped by some automatic tools that are developed to offer suggestions when a decision has to be made. The system presented here uses artificial neural networks (ANN) in order to make predictions regarding the risk of Cerebrovascular Accident (CVA). The aim of this paper is to show that these intelligent (but artificial)...
Chronic kidney failure (chronic kidney disease ‘CKD’) is a serious disease that related to the gradual loss of kidney function. It is considered one of the health threats in the developing and undeveloped countries At early stages, few symptoms can be detected, where the CKD may not become obvious until significant kidney function impaired occur. CKD treatment focuses on reducing the kidney damage...
In the present work a Cuckoo Search (CS) trained Neural Network (NN) or NN-CS based model has been proposed to detect Chronic Kidney Disease (CKD) which has become one of the newest threats to the developing and undeveloped countries. Studies and surveys in different parts of India have suggested that CKD is becoming a major concern day by day. The financial burden of the treatment and future consequences...
Coughing is one of the important signs of several diseases in dogs. There are two types of dog cough: dry cough and productive cough. The latter is most often associated with an infectious condition. It is difficult to differentiate between the two types even by experienced practitioners. In this paper, an automatic cough sound classification using neural network is introduced. A discrete wavelet...
Diseases resulting from prolonged smoking are the most common preventable causes of death in the world today. Automated identification of smoking gestures can help to initiate the appropriate intervention method and prevent relapses in smoking. In previous work, we investigated the success of utilizing accelerometer sensors in smart watches to identify smoking gestures. Our experiments have indicated...
Drug-Drug Interactions (DDI) is a cause of treatment inefficacy and toxicity. The most DDI involve drug metabolism which related to enzyme and transporter protein. Drug-enzyme actions that alter the metabolism of other drugs consist of substrate, inhibitor and inducer. Non-communicable diseases (NCDs) are the leading cause of death, drugs that are used in NCDs can increase interaction probability...
Grape constitutes one of the most widely grown fruit crop in the India. Manual observation of experts is used in practice for detection of leaf diseases, which takes more time for further control action. Without accurate disease diagnosis, proper control actions cannot be taken at appropriate time. This is where modern agriculture technique is required to detect and prevent the leaf from different...
In this paper, the various technologies of data mining (DM) models for forecast of heart disease are discussed. Data mining plays an important role in building an intelligent model for medical systems to detect heart disease (HD) using data sets of the patients, which involves risk factor associated with heart disease. Medical practitioners can help the patients by predicting the heart disease before...
The advent of Optical Coherence Tomography (OCT) imaging has engendered a quantum leap in ophthalmological disease diagnosis. Specifically, in relation to various retinal disorders, OCT has facilitated visualization of minute structural changes in retinal and choroid layers. However, due to dearth of ophthalmologists, and time and effort required in manual analysis, a large number of patients fail...
Acute myocardial infarction is the main cause of death worldwide, it is part of the acute coronary syndromes (ACS) which are characterized by an acute obstruction of the blood flow in the arteries of the heart. ACS diagnosis poses a highly complex problem where the use of intelligent systems represents an opportunity for the optimization of the diagnosis. The objective of the present work is to perform...
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