New method assesses and improves the reliability of radiologists’ diagnostic reports
The framework helps clinicians choose phrases that more accurately reflect the likelihood that certain conditions are present in X-rays.
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The framework helps clinicians choose phrases that more accurately reflect the likelihood that certain conditions are present in X-rays.
A deep neural network called CHAIS may soon replace invasive procedures like catheterization as the new gold standard for monitoring heart health.
Starting with a single frame in a simulation, a new system uses generative AI to emulate the dynamics of molecules, connecting static molecular structures and developing blurry pictures into videos.
Using this model, researchers may be able to identify antibody drugs that can target a variety of infectious diseases.
With models like AlphaFold3 limited to academic research, the team built an equivalent alternative, to encourage innovation more broadly.
Researchers at MIT, NYU, and UCLA develop an approach to help evaluate whether large language models like GPT-4 are equitable enough to be clinically viable for mental health support.
Five MIT faculty members and two additional alumni are honored with fellowships to advance research on beneficial AI.
In a recent commentary, a team from MIT, Equality AI, and Boston University highlights the gaps in regulation for AI models and non-AI algorithms in health care.
The program focused on AI in health care, drawing on Takeda’s R&D experience in drug development and MIT’s deep expertise in AI.
Joining three teams backed by a total of $75 million, MIT researchers will tackle some of cancer’s toughest challenges.