AI model detects prediabetes using ECG data without need for blood tests

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either ...

Machine learning can predict patients' responses to antidepressants—while disentangling drug and placebo effects

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global ...
IEEE

Improving Accuracy of Diabetes Prediction Using Machine Learning Techniques and Clinical Data

Abstract: Diabetes is a chronic condition affecting millions of people globally, requiring early and accurate prediction to mitigate associated health risks. This study employed a Kaggle dataset with ...
IEEE

Enhanced Post-Prandial Glycemic Response Prediction in Type 2 Diabetes with Microbiome Data and Deep Learning

Abstract: Nutritional intervention can improve glycemic control for type 2 diabetes mellitus (T2DM), and thus accurately predicting post-prandial glycemic responses (PPGRs) to each meal is essential.
Frontiers

Explainable machine learning model of coronary artery disease combined with diabetes: development and validation study

Background: Coronary artery disease (CAD) demonstrates a strong bidirectional association with diabetes mellitus, which not only elevates cardiovascular disease risk but also correlates with poorer ...
GitHub

Diabetes Prediction Using Machine Learning

Diabetes affects over 537 million adults globally, with early detection critical for effective treatment and management. This project develops a machine learning classification model to predict ...
GitHub

Diabetes Risk Prediction Platform

Given features such as age, glucose, insulin, and body mass index, predict whether an individual is non-diabetic, type-1-like, or type-2-like. The system must support experimentation with different ...