An inconspicuous box sits beside the Wi-Fi router, silently humming its own much-lower-energy radio waves through the house. The patient—who has a family history of Parkinson’s disease—makes dinner, watches TV, and falls asleep. Nothing amiss. Learn more
Although computer scientists may initially treat data bias and error as a nuisance, researchers argue it’s a hidden treasure trove for reflecting societal values.
Learn more
How AI is changing the manner in which cardiovascular illness is diagnosed. And the future is unfolding before us with new predictive analytics, remote monitoring and precision medicine. Dr. Stultz is both a Ph.D. in Computer Science as well as a Cardiologist and brings both fields of practice together in a unique fashion. Learn more
In a large study of thousands of mammograms, AI algorithms outperformed the standard clinical risk model for predicting the five-year risk for breast cancer. The results of the study were published in Radiology.
A woman’s risk of breast cancer is typically calculated using clinical models such as the Breast Cancer Surveillance Consortium (BCSC) risk model, which uses self-reported and other information on the patient—including age, family history of the disease, whether she has given birth, and whether she has dense breasts—to calculate a risk score. Learn more
With the artificial intelligence conversation now mainstream, the 2023 MIT-MGB AI Cures conference saw attendance double from previous years.
Learn more
President Yoon Suk Yeol of South Korea visited MIT on Friday, participating in a roundtable discussion with Institute leaders and faculty about biomedical research and discussing the fundamentals of technology-driven innovation clusters. Learn more
Researchers in Boston are on the verge of what they say is a major advancement in lung cancer screening: Artificial intelligence that can detect early signs of the disease years before doctors would find it on a CT scan.
The new AI tool, called Sybil, was developed by scientists at the Mass General Cancer Center and the Massachusetts Institute of Technology in Cambridge. In one study, it was shown to accurately predict whether a person will develop lung cancer in the next year 86% to 94% of the time. Learn more
