Hyperglycemia identification using ECG in deep learning era
A growing number of smart wearable biosensors are operating in the medical IoT
environment and those that capture physiological signals have received special attention …
environment and those that capture physiological signals have received special attention …
[HTML][HTML] HD-MVCNN: High-density ECG signal based diabetic prediction and classification using multi-view convolutional neural network
D Santhakumar, KD Shree, M Buvanesvari… - Egyptian Informatics …, 2024 - Elsevier
Diabetes mellitus, also known as diabetes, is a medical condition marked by high blood
sugar levels and impacts a large population worldwide. Treating diabetes is not feasible. It …
sugar levels and impacts a large population worldwide. Treating diabetes is not feasible. It …
Machine learning methods in the classification of the athletes dehydration
A Alvarez, E Severeyn, J Velásquez… - 2019 IEEE Fourth …, 2019 - ieeexplore.ieee.org
Regular physical activity brings improvement in health and quality of life. It is associated with
reduced risk of several diseases such as cardiovascular disease and type 2 diabetes …
reduced risk of several diseases such as cardiovascular disease and type 2 diabetes …
Analysis of ECG segments for non-invasive blood glucose monitoring
Continuous blood glucose (BG) monitoring is necessary to avoid the deadly health
complications from diabetes mellitus. The conventional method of measuring and monitoring …
complications from diabetes mellitus. The conventional method of measuring and monitoring …
HOMA-IR Assessment for impaired glucose tolerance, impaired fasting glucose and insulin resistance diagnosis
Impaired glucose tolerance (IGT), impaired fasting glucose (IFG) and insulin resistance (IR)
are prediabetic conditions diagnosed by glucose and insulin values measured by oral …
are prediabetic conditions diagnosed by glucose and insulin values measured by oral …
Assessment of Anthropometric Measurements for Obesity and Abnormal Body Fat Percentage Diagnosis Using k-means as Clustering Technique
The increased prevalence of overweight and obesity has become a major factor in public
spending in countries around the world. The diagnosis of overweight and obesity is based …
spending in countries around the world. The diagnosis of overweight and obesity is based …
Analysis of Anthropometric Measurements Using Receiver Operating Characteristic Curve for Impaired Waist to Height Ratio Detection
Metabolic dysfunctions such as obesity, insulin resistance, metabolic syndrome, and
glucose tolerance are strongly related to each other. The presence of any of them in a …
glucose tolerance are strongly related to each other. The presence of any of them in a …
Classification of Impaired Waist to Height Ratio Using Machine Learning Technique
Metabolic dysfunctions are a set of metabolic risk factors that include abdominal obesity,
dyslipidemia, insulin resistance, among others. Individuals with any of these metabolic …
dyslipidemia, insulin resistance, among others. Individuals with any of these metabolic …
Prediction of abnormal body fat percentage by anthropometrics parameters using receiver operating characteristic curve
The World Health Organization has defined obesity" as the abnormal or excessive fat
accumulation that represents a risk to health". Although obesity is characterized by an …
accumulation that represents a risk to health". Although obesity is characterized by an …
Assessment of Anthropometric Measurements for Obesity and Abnormal Body Fat Percentage Diagnosis Using k-means as Clustering Technique
The increased prevalence of overweight and obesity has become a major factor in public
spending in countries around the world. The diagnosis of overweight and obesity is based …
spending in countries around the world. The diagnosis of overweight and obesity is based …