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CSE Faculty Seminar: Jenna Wiens, PhD
November 23, 2015 @ 12:00 pm - 1:00 pm
Title: Increasing the Utility of Machine Learning in Clinical Care Abstract: In recent years, the availability of clinically relevant datasets has rapidly grown. This has led to the investigation of machine learning (ML) techniques for improving clinical decision making. However, for data-driven systems to become widely and safely adopted in clinical care, there remain several key research challenges that the ML community must address: i) poor adaptability, current solutions do not readily adapt to complex changes in clinical data, ii) insufficient intelligibility, existing tradeoffs between accuracy and interpretability often result in highly accurate but uninterpretable models, and iii) absence of actionability, the present focus is on accurate predictions rather than on both accurate and actionable predictions. In this talk, I’ll present/motivate these challenges in the context of several clinical applications and discuss new and ongoing research directions in ML that aim to tackle these issues. Bio: Jenna Wiens is an Assistant Professor in Computer Science and Engineering (CSE) at the University of Michigan. Her primary research interests lie at the intersection of machine learning and healthcare. The overarching goal of her research agenda is to develop the computational methods needed to help organize, process, and transform clinical data into actionable knowledge.