AI Medical Compendium Topic

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Diabetes Mellitus, Type 2

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Machine learning-based glucose prediction with use of continuous glucose and physical activity monitoring data: The Maastricht Study.

PloS one
BACKGROUND: Closed-loop insulin delivery systems, which integrate continuous glucose monitoring (CGM) and algorithms that continuously guide insulin dosing, have been shown to improve glycaemic control. The ability to predict future glucose values ca...

Modern computational intelligence based drug repurposing for diabetes epidemic.

Diabetes & metabolic syndrome
BACKGROUND AND AIM: Objectives are to explore recent advances in discovery of new antidiabetic agents using repurposing strategies and to discuss modern technologies used for drug repurposing highlighting diabetic specific web portal.

A deep learning system for detecting diabetic retinopathy across the disease spectrum.

Nature communications
Retinal screening contributes to early detection of diabetic retinopathy and timely treatment. To facilitate the screening process, we develop a deep learning system, named DeepDR, that can detect early-to-late stages of diabetic retinopathy. DeepDR ...

Predicting youth diabetes risk using NHANES data and machine learning.

Scientific reports
Prediabetes and diabetes mellitus (preDM/DM) have become alarmingly prevalent among youth in recent years. However, simple questionnaire-based screening tools to reliably assess diabetes risk are only available for adults, not youth. As a first step ...

Classification and Prediction on the Effects of Nutritional Intake on Overweight/Obesity, Dyslipidemia, Hypertension and Type 2 Diabetes Mellitus Using Deep Learning Model: 4-7th Korea National Health and Nutrition Examination Survey.

International journal of environmental research and public health
Few studies have been conducted to classify and predict the influence of nutritional intake on overweight/obesity, dyslipidemia, hypertension and type 2 diabetes mellitus (T2DM) based on deep learning such as deep neural network (DNN). The present st...

Artificial Intelligence-Based Diagnosis of Diabetes Mellitus: Combining Fundus Photography with Traditional Chinese Medicine Diagnostic Methodology.

BioMed research international
In this study, we propose a technique for diagnosing both type 1 and type 2 diabetes in a quick, noninvasive way by using equipment that is easy to transport. Diabetes mellitus is a chronic disease that affects public health globally. Although diabet...

Eye-color and Type-2 diabetes phenotype prediction from genotype data using deep learning methods.

BMC bioinformatics
BACKGROUND: Genotype-phenotype predictions are of great importance in genetics. These predictions can help to find genetic mutations causing variations in human beings. There are many approaches for finding the association which can be broadly catego...

Geographically weighted machine learning model for untangling spatial heterogeneity of type 2 diabetes mellitus (T2D) prevalence in the USA.

Scientific reports
Type 2 diabetes mellitus (T2D) prevalence in the United States varies substantially across spatial and temporal scales, attributable to variations of socioeconomic and lifestyle risk factors. Understanding these variations in risk factors contributio...