Jameel Clinic

Financial Times reporter Melissa Heikkilä spotlights how MIT researchers have uncovered evidence that increased use of AI tools by medical professionals risks “leading to worse health outcomes for women and ethnic minorities.” One study found that numerous AI models “recommended a much lower level of care for female patients,” writes Heikkilä. “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.” 

Prof. Regina Barzilay speaks with Newsweek reporter Katherine Fung about the how hospitals around the world around increasingly adopting new technologies. “Countries with a centralized healthcare system, or centralized healthcare records, can do a much better job because they have so much data and so much ability to monitor what AI tools are doing," says Barzilay. 

Prof. Marzyeh Ghassemi speaks with Boston Globe reporter Hiawatha Bray about her work uncovering issues with bias and trustworthiness in medical AI systems. “I love developing AI systems,” says Ghassemi. “I’m a professor at MIT for a reason. But it’s clear to me that naive deployments of these systems, that do not recognize the baggage that human data comes with, will lead to harm.”

Prof. Regina Barzilay speaks with Newsweek reporter Alexis Kayser about how new AI tools are implemented in health care settings. “You need to know how to safely bring it into the [health care] system," says Barzilay. "There is a new science, which is the science of implementation."

MIT researchers have developed Boltz-2, an AI algorithm “that unites protein folding and prediction of small-molecule binding affinity in one package,” reports Laura Howes for Chemical & Engineering News. “The researchers say their new AI model approaches the level of accuracy achieved by traditional computational chemistry—such as methods involving free-energy perturbation calculations—but much more quickly and cheaply,” explains Howes. 

Researchers at MIT and elsewhere have developed Boltz-2, an open-source generative AI model that can help researchers find new medicines faster, reports Alex Knapp for Forbes. The tool “can not only predict the structure of proteins, it can also predict its binding affinity–that is, how well a potential drug is able to interact with that protein,” explains Knapp. “This is crucial in the early stages of developing a new medicine.” 

Prof. David Sontag, Monica Agrawal PhD '23, Luke Murray SM '22, and Divya Gopinath '19, MEng '20 co-founded Layer Health - an AI healthcare startup that is applying large language models (LLMs) to help clinicians with medical chart reviews and data abstraction, reports Seth Joseph for Forbes. “The same chart review problem we’re solving with our clinical registry module is faced by clinicians at the point of care,” says Sontag. “For example, one of our next modules will focus on real-time clinical decision support to help automate clinical care pathways, leading to more reliable, high-quality care."

Writing for Forbes, Paula Schneider, CEO of Susan G. Komen, highlights Prof. Regina Barzilay’s research using AI to detect breast cancer. “Using her own mammograms in her research at MIT, Dr. Barzilay demonstrated how AI could have detected her breast cancer much earlier, potentially improving her prognosis,” writes Schneider. “Studies show that incorporating AI into mammogram analysis boosts cancer detection rates by 20%, without increasing false positives. This is a significant leap forward, as early detection is key to a better chance at positive outcomes and survival.” 

Prof. Sarah Millholland, Prof. Christian Wolf, Prof. Emil Verner, Prof. Darcy McRose, Prof. Marzyeh Ghassemi, Prof. Mohsen Ghaffari and Prof. Ariel Furst have received the 2025 Sloan Research Fellowship for “being among the most promising scientific researchers currently working in their fields,” reports Michael T. Nietzel for Forbes. “Sloan Research Fellows are chosen in seven scientific and technical fields—chemistry, computer science, Earth system science, economics, mathematics, neuroscience, and physics,” explains Nietzel. 

Prof. David Autor has been named a Senior Fellow in the Schmidt Sciences AI2050 Fellows program, and Profs. Sara Beery, Gabriele Farina, Marzyeh Ghassemi, and Yoon Kim have been named Early Career AI2050 Fellows, reports Michael T. Nietzel for Forbes. The AI2050 fellowships provide funding and resources, while challenging “researchers to imagine the year 2050, where AI has been extremely beneficial and to conduct research that helps society realize its most beneficial impacts,” explains Nietzel. 

Prof. Regina Barzilay has received the WebMD Health Heros award for her work developing a new system that uses AI to detect breast cancer up to 5 years earlier, reports WHDH. “We do have a right to know our risk and then we, together with our healthcare providers, need to manage them,” says Barzilay. 

New Yorker reporter Dhruv Khullar spotlights how researchers from across MIT are using AI to advance drug development. Khullar highlights the MIT Jameel Clinic, the Broad Institute and various faculty members for their efforts in bridging the gap between AI and drug research. “With AI, we’re getting that much more efficient at finding molecules—and in some cases creating them,” says Prof. James Collins. “The cost of the search is going down. Now we really don’t have an excuse.”

Prof. Regina Barzilay joins The Economist’s “Babbage” podcast to discuss how artificial intelligence could enable health care providers to understand and treat diseases in new ways. Host Alok Jha notes that Barzilay is determined to “overcome those challenges that are standing in the way of getting AI models to become useful in health care.” Barzilay explains: “I think we really need to change our mindset and think how we can solve the many problems for which human experts were unable to find a way forward.”  

Forbes selects innovators for the list’s Healthcare & Science category, written by senior contributor Yue Wang. On the list is MIT PhD candidate Yuzhe Yang, who studies AI and machine learning technologies capability to monitor and diagnose illnesses such as Parkinson's disease.