Illustration of a computer in a stone age setting

How an archeological approach can help leverage biased data in AI to improve medicine

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
Group of high school students posing for a group photo with MIT President Emerita Susan Hockfield

How to help high schoolers prepare for the rise of artificial intelligence

A one-week summer program aims to foster a deeper understanding of machine-learning approaches in health among curious young minds. Learn more
Two side-by-side images of an MRI that has been motion-corrupted and one that has been motion-corrected
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AI and Cardiovascular Medicine. In conversation with Professor, Dr. Collin Stultz

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

AI Outperformed Standard Risk Model for Predicting Breast Cancer

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

Is medicine ready for AI? Doctors, computer scientists, and policymakers are cautiously optimistic

With the artificial intelligence conversation now mainstream, the 2023 MIT-MGB AI Cures conference saw attendance double from previous years. Learn more
Group of MIT faculty members standing with President Yoon Suk Yeol of South Korea and his team.

President Yoon Suk Yeol of South Korea visits MIT

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

Promising new AI can detect early signs of lung cancer that doctors can’t see

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
Black and white photo of Dr. Andreas Rett.
Sybil researchers pose for a photo in front of an CT scanner

MIT researchers develop an AI model that can detect future lung cancer risk

The name Sybil has its origins in the oracles of Ancient Greece, also known as sibyls: feminine figures who were relied upon to relay divine knowledge of the unseen and the omnipotent past, present, and future. Now, the name has been excavated from antiquity and bestowed on an artificial intelligence tool for lung cancer risk assessment being developed by researchers at MIT's Abdul Latif Jameel Clinic for Machine Learning in Health, Mass General Cancer Center (MGCC), and Chang Gung Memorial Hospital (CGMH). Learn more
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