Health sciences and technology

Prof. Pat Pataranutaporn speaks with The Guardian reporter Andrew Gregory about the lack of safety warnings and disclaimers in AI overviews, specifically in AI-generated health materials. “The absence of disclaimers when users are initially served medical information creates several critical dangers,” says Pataranutaporn. “Disclaimers serve as a crucial intervention point. They disrupt this automatic trust and prompt users to engage more critically with the information they receive.”

Prof. Angela Belcher and Prof. Sangeeta Bhatia chat with Edgar B. Herwick III of GBH’s The Curiosity Desk about their efforts aimed at improving diagnostics for ovarian cancer. “We now know that ovarian cancer doesn’t originate in the ovaries. About 80% of the time, ovarian cancer starts in the fallopian tubes, but it can sit there as this precancerous lesion,” explains Belcher. “There’s new technologies that can be invented and developed to detect it much earlier, because if it’s detected earlier…there’s such an opportunity to make an impact.”  

Researchers at MIT and elsewhere have developed a compact magnetic mixer to prevent clogs and uneven tissue in 3D bioprinting, reports Aamir Khollam for Interesting Engineering. The device called “MagMix,” works to “keep bio-inks uniform throughout the entire printing process,” writes Khollam. 

Prof. Marzyeh Ghassemi and Monica Agrawal PhD '23 speak with Boston Globe reporter Hiawatha Bray about the risks on relying solely on AI for medical information. “What I’m really, really worried about is economically disadvantaged communities,” says Ghassemi. “You might not have access to a health care professional who you can quickly call and say, ‘Hey… Should I listen to this?’”  

Reporting for FOX News, Kurt Knuttson highlights how MIT researchers have developed a new light-based scanner that can read blood sugar without a single prick. “A handheld or watch-sized glucose scanner would mark a major shift in diabetes care,” writes Knuttson. “MIT's work brings that future closer with a design that reads your chemistry through light.”

Researchers at MIT have developed a device that can measure blood glucose levels through the skin. The team used “Raman spectroscopy to measure blood glucose because of the method’s ability to identify the chemical composition of samples noninvasively,” writes Sneha Khedkar for The Scientist. “The approach involves shining monochromatic light on samples and analyzing how the light scatters.” 

Researchers at MIT have developed a noninvasive, light-based blood-glucose monitoring system capable of replacing finger pricks and under-the-skin sensors used by patients with diabetes, reports Andrew Paul for Popular Science. The approach could “even fit on a device the size of a watch,” explains Paul. “Each measurement scan takes slightly more than 30 seconds to complete. The device also shows an accuracy comparable to two commercially available, wearable glucose monitors.” 

Nature reporter James Mitchell Crow spotlights Prof. Leonard Guarente’s work studying the impact of calorie restriction in life expectancy. Guarente’s research points to “the importance of a set of genes and associated proteins called sirtuins.” Guarente says: “If you make them more active, you extend the lifespan.”  

Prof. Linda Griffith speaks with Science Friday host Flora Lichtman about her work studying endometriosis. “I did a lot of things in the regenerative medicine space. But I had an epiphany that there’s so many chronic and inflammatory disease that we don’t know how to treat so I started building models of human organs and tissues in the lab using what we called microfluidic chips,” Griffith explains. “When I got asked about endometriosis, it was actually a perfect application for this kind of approach because we really need to study the lesions very carefully in the lab in ways that is very hard to study in patients.” 

MIT researchers have developed a new AI tool, dubbed “DrugReflector,” aimed at speeding up the drug discovery process, reports William A. Haseltine for Forbes. The researchers used DrugReflector to test tested almost 9,600 drugs in different human cell types.“This system was 17 times more accurate than older computational methods and improved as it used honest lab feedback,” writes Haseltine. 

The MIT Health and Life Sciences Collaborative (MIT HEALS) launched the Fairbairn Menstruation Science Fund earlier this year as part of an effort aimed at improving women’s health, reports Zoë Corbyn for The Guardian. “This is frontier science,” says Prof. Linda Griffith. Corbyn also spotlights how Ridhi Tariyal MS '10 has co-founded NextGen Jane, a women’s healthcare startup that aims to gain better insight into women’s reproductive health by studying menstruation.

Prof. Alex Shalek and his colleagues developed a deep-learning model called DrugReflector aimed at speeding up the process of drug discovery, reports Heidi Ledford for Nature. “They used DrugReflector to find chemicals that can affect the generation of platelets and red blood cells — a characteristic that could be useful in treating some blood conditions,” explains Ledford. The researchers found that “DrugReflector was up to 17 times more effective at finding relevant compounds than standard, brute-force drug screening that depends on randomly selecting compounds from a chemical library.”

Prof. Linda Griffith and her colleagues have “developed a model of the human gut to study how the organ’s microbes interact with immune cells and regulate inflammation,” reports Gemma Conroy for Nature. Griffith and her team “have also created models for endometriosis and pancreatic cancer,” writes Conroy. 

Prof. Deblina Sarkar speaks with Bloomberg Businessweek Daily reporters Carol Massar and David Gura about her work using microscopic technology to treat and identify health issues. We are building “tiny nanoelectronics chips which can seamlessly integrate with our body and brain,” says Sarkar. “This can diagnose disease or treat diseases which even drugs cannot fix.” 

Writing for Forbes, Senior Lecturer Guadalupe Hayes-Mota '08, SM '16, MBA '16 emphasizes the importance of implementing ethical frameworks when developing AI systems designed for use in healthcare. “The future of AI in healthcare not only needs to be intelligent,” writes Hayes-Mota. “It needs to be trusted. And in healthcare, trust is the ultimate competitive edge.”