Researchers are studying a machine learning-powered warning system for breast cancer. It works by detecting subtle changes in a mammogram that humans can't spot, but could soon become cancer.

An artificial intelligence (AI) tool built by the U.S. National Science Foundation National Center for Atmospheric Research ...

Researchers used AI to analyze whole-body MRI scans from more than 66,000 participants to create the most detailed reference ...

Researchers use machine learning and genetic analysis to uncover type 1 diabetes risk factors, improving prediction accuracy ...

OBSCORE is a data-driven tool that identifies high-risk individuals for obesity-related diseases, enhancing treatment ...

Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...

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 ...

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 ...

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 ...