MIT researchers at MIT have developed a microfluidic chip-based model of liver tissue that “allows researchers to understand the biological mechanisms underlying liver tissue regeneration and points to several molecules that may promote the process,” reports William A. Haseltine for Forbes. "These results mark significant progress in our understanding of the human body’s regenerative properties," writes Haseltine.
Researchers from MIT and Massachusetts General Hospital have developed “Sybil,” an AI tool that can detect the risk of a patient developing lung cancer within six years, reports Mary Kekatos for ABC News. “Sybil was trained on low-dose chest computer tomography scans, which is recommended for those between ages 50 and 80 who either have a significant history of smoking or currently smoke,” explains Kekatos.
Institute Prof. Bob Langer speaks with Curiosity podcast hosts Immad Akhynd and Raj Suri about his work in the field of biotechnology, delving into how he has co-founded 40 companies. “I wanted to get out and do some good in the world,” says Langer. “That's where patents come in and that's where companies come in. And I think the challenge of the company is very different because you have what I call a platform technology.”
Prof. Regina Barzilay speaks with Nicole Estephan of WCVB-TV’s Chronicle about her work developing new AI systems that could be used to help diagnose breast and lung cancer before the cancers are detectable to the human eye.
Soledad O’Brien spotlights how researchers from MIT and Massachusetts General Hospital developed a new artificial intelligence tool, called Sybil, that an accurately predict a patient’s risk of developing lung cancer. “Sybil predicted with 86 to 94 percent accuracy whether a patient would develop lung cancer within a year,” says O’Brien.
Research from MIT and elsewhere have developed a mobile app that uses computer-vision techniques and AI to detect post-surgery signs of infection as part of an effort to help community workers in Kirehe, a district in Rwanda’s Eastern province, reports Shefali Malhotra for Science. “The researchers are now improving the app so it can be used across more diverse populations such as in Ghana and parts of South America,” writes Malhotra.
Researchers at MIT have developed a new nanoparticle sensor that can detect cancerous proteins through a simple urine test. “The researchers designed the tests to be done on a strip of paper, similar to the at-home COVID tests everyone became familiar with during the pandemic,” writes Lambert. “They hope to make it as affordable and accessible to as many patients as possible.”
NBC News highlights how researchers from MIT and MGH have developed a new AI tool, called Sybil, that can “accurately predict whether a person will develop lung cancer in the next year 86% to 94% of the time.” NBC News notes that according to experts, the tool "could be a leap forward in the early detection of lung cancer.”
Prof. Marzyeh Ghassemi speaks with WBUR reporter Geoff Brumfiel about her research studying the use of artificial intelligence in healthcare. “When you take state-of-the-art machine learning methods and systems and then evaluate them on different patient groups, they do not perform equally,” says Ghassemi.
Prof. Marzyeh Ghassemi speaks with Scientific American reporter Sara Reardon about the impact of AI chatbots on medical care. “Ghassemi is particularly concerned that chatbots will perpetuate the racism, sexism and other types of prejudice that persist in medicine—and across the Internet,” writes Reardon. “Scrubbing racism from the Internet is impossible, but Ghassemi says developers may be able to do preemptive audits to see where a chatbot gives biased answers and tell it to stop or to identify common biases that pop up in its conversations with users.”
Principal Research Scientist Leo Anthony Celi co-authored a study that found “a lack of racial and gender diversity could be hindering the efforts of researchers working to improve the fairness of artificial intelligence (AI) tools in health care,” reports Carissa Wong for Nature.
Researchers at MIT developed a system that uses artificial intelligence to help predict future risk of developing breast cancer, reports Poppy Harlow for CNN. What this work does “is identifies risk. It can tell a woman that you’re at high risk for developing breast cancer before you develop breast cancer,” says Larry Norton, medical director of the Lauder Breast Center at the Memorial Sloan Kettering Cancer Center.
Fast Company reporter Amelia Hemphill spotlights the work of Alicia Chong Rodriguez SM ’17, SM ’18, and her startup Bloomer Tech, which is “dedicated to transforming women’s underwear into a healthcare device.” “Our big goal is to generate digital biomarkers,” says Chong Rodriguez. “Digital biomarkers work more like a video, so it will definitely allow a more personalized care from the physician to their patient.”
Researchers at MIT and elsewhere are analyzing patients’ speech patterns to see if they can detect Lou Gehrig’s disease in its early stages, reports Ben Leonard, Ruth Reader, Carmen Paun and Erin Schumaker for Politico. “Catching it early and beginning treatment can improve patients’ quality of life and delay symptom onset,” they write.
Researchers at MIT and Massachusetts General Hospital have developed “Sybil” – an artificial intelligence tool that can predict the risk of a patient developing lung cancer within six years, reports Mallika Marshall for CBS Boston.