Medical Device and Diagnostic Industry (MD+DI)

AI-Powered Atrial Fibrillation Detection: How Machine Learning Is Transforming Cardiac Care Through ECG Analysis

At HRS 2026, Dr. Song Zuo presented evidence that AI can detect atrial fibrillation with over 90% sensitivity, ...
CNETOpinion

From Tea Leaves to AI: Why Today's High-Tech Predictions Are So Dangerous

For centuries, humans looked to seers and astrologers to determine fate. Today, we look to algorithms, and the loss of agency ...
European Medical Journal

Explainable AI Predicts Parkinson’s Disease with 93% Accuracy

Discover how explainable AI enhances Parkinson’s disease prediction with improved accuracy and clinical interpretability.
The Lancet

Detection of young-onset type 2 diabetes using deep learning across primary and secondary care: a nationwide, retrospective cohort study

aNovo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, ...
The American Journal of Managed Care

Machine Learning–Based Tools Predict MS Progression

Two complementary predictors (DAAE-M and ELIE) estimate individualized 5-year progression risk using routine clinical data, ...
IEEE

Random Forest Algorithm for the Prediction of Diabetes

Abstract: Diabetes is taken into account together of the deadliest and chronic disease that causes a rise in glucose. Polygenic disease is that the kind wherever the exocrine gland doesn't manufacture ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

This paper proposes a hybrid machine learning framework for early diabetes prediction tailored to Sierra Leone, where locally representative datasets are scarce. The framework integrates Random Forest ...
The New York Times

48 Hours Without A.I.

It’s everywhere, as the author learned the hard way while making as little contact as possible with machine learning and generative artificial intelligence. It’s everywhere, as the author learned the ...
Frontiers

Evaluating machine learning models for stroke prediction based on clinical variables

Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as the Framingham ...