The models are designed to predict someone’s risk of diabetes or stroke. A few might already have been used on patients.

A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD than traditional tools.

In a future perhaps not too far away, artificial intelligence and its subfield of machine learning (ML) tools and models, ...

A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...

Alumna, author and machine learning expert Vivienne Ming explains why the best defense against AI's downsides is investing in ...

A machine learning model predicts low-density lipoprotein cholesterol from routine lab data, offering a low-cost way to ...

Azillah Binti Othman, IAEA Department of Nuclear Sciences and Applications Ayhan Evrensel, IAEA Department of Nuclear Sciences and Applications The IAEA is inviting research organizations to join a ...

The next major advance in medical AI may lie not in analyzing more data, but in understanding how health data change over time. A recent editorial in Intelligent Medicine argues that dynamics-driven ...

Mount Sinai researchers have created an analytic tool using machine learning that can predict cardiovascular disease risk in patients with obstructive sleep apnea ...

A novel glioblastoma therapy developed by Rosalind Franklin University Helix 51 incubator company UP Oncolytics showed encouraging preclinical results in two studies presented at the American ...

In A Nutshell AI tools that track how the body’s molecular networks change over time may detect diseases like cancer, ...