Our 2025 Thanksgiving message

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2025’s Fiercest Women in Life Sciences

The life sciences mission of Najat Khan, Ph.D., was forged in hospital hallways.
Her parents, a trauma surgeon and a gynecologist-turned-radiologist, “didn't believe in babysitters,” she joked in an interview. The extensive time she therefore spent in hospitals throughout her childhood showed Khan the life-changing impact of innovative medicines and set her on the path to the C-suites of Johnson & Johnson and Recursion Pharmaceuticals. Learn more

Marketwatch25: She survived breast cancer. Now her AI tool could help you skip annual mammograms.

As an MIT computer-science professor, Regina Barzilay was used to living on the bleeding edge of innovation, teaching computers to understand words in the nascent field of natural language processing. But when she was diagnosed with breast cancer in 2014, she was thrust into a different and, as she describes it, “really backwards” technological world. Learn more

MIT Jameel Clinic invited to the 1st Pan Arab Congress of Thoracic Surgery

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AI steps in to detect the world’s deadliest infectious disease

As a professor and computer scientist at MIT, Regina Barzilay has spent years building AI models to detect breast cancer and lung cancer. Then, when a hospital in Sri Lanka told her it couldn't afford to buy off-the-shelf AI models for TB screenings, she agreed to build one for them.

As she got to work this past year, she says, she immediately understood why TB is at the vanguard of the global health challenges with AI solutions.

"You can see TB. TB is visual. You have an x-ray. You have a label which says whether they have it or not — and you just train the model," Barzilay says, adding that it only took her a few months and less than $50,000 to make her model. "It's straightforward, very cheap, very fast to develop." Learn more

Introducing BoltzGen: Toward Universal Binder Design

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Two from MIT Jameel Clinic elected to the National Academy of Medicine Class of 2025

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AI maps how a new antibiotic targets gut bacteria

“This discovery speaks to a central challenge in antibiotic development,” says Jon Stokes, senior author of a new paper on the work, assistant professor of biochemistry and biomedical sciences at McMaster, and research affiliate at MIT’s Abdul Latif Jameel Clinic for Machine Learning in Health. “The problem isn’t finding molecules that kill bacteria in a dish — we’ve been able to do that for a long time. A major hurdle is figuring out what those molecules actually do inside bacteria. Without that detailed understanding, you can’t develop these early-stage antibiotics into safe and effective therapies for patients.” Learn more

AI medical tools downplay symptoms in women and ethnic minorities

Research by the MIT’s Jameel Clinic in June found that AI models, such as OpenAI’s GPT-4, Meta’s Llama 3 and Palmyra-Med — a healthcare- focused LLM — recommended a much lower level of care for female patients, and suggested some patients self-treat at home instead of seeking help.

A separate study by the MIT team showed that OpenAI’s GPT-4 and other models also displayed answers that had less compassion towards Black and Asian people seeking support for mental health problems.

That suggested “some patients could receive much less supportive guidance based purely on their perceived race by the model”, said Marzyeh Ghassemi, associate professor at MIT’s Jameel Clinic.  Learn more

MIT researchers develop AI tool to improve flu vaccine strain selection

Every year, global health experts are faced with a high-stakes decision: Which influenza strains should go into the next seasonal vaccine? The choice must be made months in advance, long before flu season even begins, and it can often feel like a race against the clock. If the selected strains match those that circulate, the vaccine will likely be highly effective. But if the prediction is off, protection can drop significantly, leading to (potentially preventable) illness and strain on health care systems. Learn more
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