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

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 groundbreaking study published on January 18, 2024, in Cancer Discovery, scientists at University of California San Diego School of Medicine leveraged a machine learning algorithm to tackle ...

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 ...

She said we should think of “AI” as an umbrella term. “AI is much more broader, all-encompassing, compared to only machine learning or algorithms,” Susarla said.

Over at the Massachusetts Institute of Technology, they point out that machine learning and AI are often used interchangeably because these days, most AI includes some amount of machine learning.