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

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

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

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 ...

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

From Watson's $15B Jeopardy-to-medicine failure to 800+ FDA-cleared AI tools: the complete history of AI in healthcare.

Final random-forest-based models outperformed all publicly available risk scores on internal and external test sets.

A model integrating deep learning with clinical and epidemiologic data may significantly improve lung cancer risk prediction based on LDCT screening.

Older women are at an increased risk of developing diabetes, but a new study is opening the possibility of predicting who ...

A new study using an advanced "digital twin" artificial intelligence model has found that factors such as loneliness, ...

Researchers identify 4 distinct gestational diabetes phenotypes with unique risks for preeclampsia, NICU admission, and postpartum diabetes.