When Regina Barzilay was diagnosed with breast cancer in 2014, it upended her life and shifted the direction of her research. Already an accomplished computer scientist specializing in natural language processing, her experience as a patient shed light on the possibility of new applications for machine learning and revealed a stark disconnect between technology’s promise and its implementation in health care. “It was upsetting to see that all these great technologies are not translated into patient care,” she recalls. “I wanted to change it.” After going through her own treatment, Barzilay’s work took on an urgent new focus: could the very technologies she used in her research predict who might be at risk for breast cancer? Learn more
During my seven years as president and CEO of Susan G. Komen, I’ve witnessed the impact of innovation in our mission to end breast cancer for good. Over the past four decades, we’ve seen a 44% reduction in breast cancer mortality, thanks to early detection and better treatments. AI is now accelerating this progress with its capacity to analyze vast datasets, discover new patterns and enhance diagnostic accuracy.
Take, for example, the groundbreaking work of Komen scholar Dr. Regina Barzilay. Using her own mammograms in her research at MIT, Dr. Barzilay demonstrated how AI could have detected her breast cancer much earlier, potentially improving her prognosis. Studies show that incorporating AI into mammogram analysis boosts cancer detection rates by 20%, without increasing false positives. This is a significant leap forward, as early detection is key to a better chance at positive outcomes and survival. Learn more
Can we harness the power of artificial intelligence to solve the world’s most challenging problems without creating an uncontrollable force that ultimately destroys us? ChatGPT and other new A.I. tools can now answer complex questions, write essays, and generate realistic-looking images in a matter of seconds. They can even pass a lawyer’s bar exam. Should we celebrate? Or worry? Or both? Correspondent Miles O’Brien investigates how researchers are trying to transform the world using A.I., hunting for big solutions in fields from medicine to climate change. (Premiering March 27 at 9 pm on PBS)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