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With AI, researchers predict the location of virtually any protein within a human cell

Trained with a joint understanding of protein and cell behavior, the model could help with diagnosing disease and developing new drugs.

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Study shows vision-language models can’t handle queries with negation words

Words like “no” and “not” can cause this popular class of AI models to fail unexpectedly in high-stakes settings, such as medical diagnosis.

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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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MIT spinout maps the body’s metabolites to uncover the hidden drivers of disease

ReviveMed uses AI to gather large-scale data on metabolites — molecules like lipids, cholesterol, and sugar — to match patients with therapeutics.

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3 Questions: Should we label AI systems like we do prescription drugs?

Researchers argue that in health care settings, “responsible use” labels could ensure AI systems are deployed appropriately.

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AI model identifies certain breast tumor stages likely to progress to invasive cancer

The model could help clinicians assess breast cancer stage and ultimately help in reducing overtreatment.

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Symposium highlights scale of mental health crisis and novel methods of diagnosis and treatment

Co-hosted by the McGovern Institute, MIT Open Learning, and others, the symposium stressed emerging technologies in advancing understanding of mental health and neurological conditions.

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MIT Generative AI Week fosters dialogue across disciplines

During the last week of November, MIT hosted symposia and events aimed at examining the implications and possibilities of generative AI.

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A pose-mapping technique could remotely evaluate patients with cerebral palsy

The machine-learning method works on most mobile devices and could be expanded to assess other motor disorders outside of the doctor’s office.

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How to help high schoolers prepare for the rise of artificial intelligence

A one-week summer program aims to foster a deeper understanding of machine-learning approaches in health among curious young minds.