Download RSS feed: News Articles / In the Media / Audio
Researchers from MIT and McMaster University used a machine-learning algorithm to identify a new antibiotic that can treat a bacteria that causes deadly infections, reports Maya Yang for The Guardian. The researchers used an “AI algorithm to screen thousands of antibacterial molecules in an attempt to predict new structural classes. As a result of the AI screening, researchers were able to identify a new antibacterial compound which they named abaucin,” writes Yang.
Prof. Marzyeh Ghassemi speaks with NPR host Kate Wells about a decision by the National Eating Disorders Associations to replace their helpline with a chatbot. “I think it's very alienating to have an interactive system present you with irrelevant or what can feel like tangential information,” says Ghassemi.
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.”
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.
Callie Gade and Nate Bonham of CNN’s Discovery Daily Podcast spotlight how researchers from MIT developed a 3D printed replica of the human heart that can help doctors customize treatments for patients before conducting open heart surgery or other intrusive procedures. “These more patient-specific heart replicas can help future researchers develop and identify treatments for people with unique health problems,” says Gade.
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.
Dr. Akshay Syal, a medical fellow for NBC News, discusses how MIT researchers have developed a new technique to 3D print custom replicas of the human heart.
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.
Bloomberg reporter Tanaz Meghjani writes that MIT researchers created a new system to 3D print a customized replica of the human heart, which could help improve replacement valve procedures. The new system “mimics blood flow and pressure in individual diseased hearts, suggesting a way to predict the effects of various replacements and select the best fit, avoiding potential leakage and failure,” Meghjani writes.
MIT engineers have developed a new technique for 3D printing a soft, flexible, custom-designed replica of a patient’s heart, report Gabrielle Emanuel and Amy Sokolow for WBUR. The goal of the research is to “provide realistic models so that doctors, researchers and medical device manufacturers can use them in testing therapies for different types of heart disease,” Emanuel and Sokolow explain.
Writing for Fortune, Prof. Elazer R. Edelman and Mike Mussallem of Edwards Lifesciences write that the backlog of deferred medical treatments caused by the Covid-19 pandemic and resulting long-term health consequences could impact public health for years. Edelman and Mussallem emphasize that “it is incumbent upon us to identify timely real-world evidence to elucidate the effects of policy changes so they can be adaptive and agile enough to provide access to critical interventions and procedures.”
A review led Prof. Marzyeh Ghassemi has found that a major issue in health-related machine learning models “is the relative scarcity of publicly available data sets in medicine,” reports Emily Sohn for Nature.
Researchers at MIT have found indoor humidity levels can influence the transmission of Covid-19, reports Dennis Thompson for US News & World Report. “We found that even when considering countries with very strong versus very weak Covid-19 mitigation policies, or wildly different outdoor conditions, indoor — rather than outdoor — relative humidity maintains an underlying strong and robust link with Covid-19 outcomes,” explains Prof. Lydia Bourouiba.
MIT researchers have found that relative humidity “may be an important metric in influencing the transmission of Covid-19,” reports Sophie Mellor for Fortune, “Maintaining an indoor relative humidity between 40% and 60% – a Goldilocks climate, not too humid, not too dry – is associated with relatively lower rates of Covid-19 infections and deaths,” writes Mellor.