New York City-based Icahn School of Medicine at Mount Sinai has developed a machine learning model to estimate disease risk from rare genetic variants using routine clinical data. The model was ...

Weill Cornell Medicine researchers are using machine learning, a form of artificial intelligence, to shed light on genetic mutations associated with spina bifida.

Aug. 26 (UPI) --New artificial intelligence models can yield much more nuanced and detailed assessments of genetic risks for ...

EPFL researchers have developed Systema, a new tool to evaluate how well AI models work when predicting the effects of genetic perturbations.

Gynecological cancers, including breast, ovarian, and cervical malignancies, account for a significant global health burden among women. The review outlines how a spectrum of machine learning (ML) ...

This research roundup explores the role of sugar molecules in brain degeneration, a machine learning algorithm to detect diseases and a generative AI tool that can generate original genetic code.

Layered within these actions are additional information, such as gait pattern, velocity, distance traveled and locations visited. Using machine learning, they evaluated this information and identified ...

In a small study, they successfully trained a machine learning algorithm to predict, in hindsight, which patients with melanoma would respond to treatment and which would not respond.

These data were then used to train a machine learning algorithm to help researchers design the best fix for a given genetic flaw, which promises to speed up efforts to bring prime editing into the ...

Machine learning is great at finding patterns but doesn’t know what those patterns mean. Combine it with knowledge gained from genetic research and you have a powerful view into the workings of ...