Machine Learning Working Group virtual meeting, May 10, 11am-12pm ET

Sunday, May 2, 2021 - 15:36

Please join us for a virtual Machine Learning Working Group Meeting on May 10th, from 11am-12pm EST. Amber Simpson, PhD, Associate Professor / Canada Research Chair (Tier 2) in Biomedical Computing and Informatics at Queen's University, presents, “Solving fundamental cancer problems with artificial intelligence”.
 
Abstract: 
Precision medicine is an approach to patient care that considers individual differences in a patient’s genetic and molecular makeup to predict disease progression and optimize treatment response – and one of the greatest opportunities, and challenges, in modern cancer care. There is currently no known method to predict the metastatic potential of any cancer at early stages. We propose to address this critical barrier by creating a cancer digital twin, a digital replica of a cancer patient using state-of-the-art artificial intelligence (AI) techniques applied to 900,000 abdominal CT scans from a high-volume cancer center. Predicting metastatic progression at early stages would radically transform our approach to cancer treatment, but promises substantial implications for patients and society that must be considered. For example, would you want to know a dismal prognosis predicted by your digital twin? How would you act on this information – would you regard the choice as yours, or your fate as given by your twin? In a world where AI is increasingly biased, how do we ensure that AI doesn’t create further inequities? Dr. Simpson will present new work on the development of a cancer twin for predicting metastatic progression as well as provide some discussion of the social ramifications of such technology.

If you would like to attend this month’s session, please reach out to James Hale - jsh171@case.edu