On April 8, the CDAC Discovery Challenge program awarded funding to four new interdisciplinary projects that will develop and utilize computational tools. Three of these four projects are co-led by BSD faculty:


  • Machine Learning to Improve Targeted Cancer Therapy proposes the use of AI to recommend treatment based in part on genomic data. This project is a collaboration between Alexander Pearson, MD, PhD, Robert Grossman, PhD, faculty from molecular engineering and computer science, and researchers at Argonne National Laboratory.


  • ADVancing the SOCiome For SociAl and HealTh Equity (ADVOCATE) aims to use social, environmental, behavioral and psychological data—the “sociome”—along with biological data to influence health outcomes. This project’s collaborative team includes faculty physicians Samuel Volchenboum, Stacy Lindau, David Meltzer, Doriane Miller, Lainie Ross, Julian Solway and Dana Suskind.


  • AI-Driven Tutorials for Radiology Student Training, co-led by Aytekin Oto, MD, MBA, Maryellen Giger, PhD, and Aritrick Chatterjee, PhD, will develop an “AI teacher” to help train students on AI-aided diagnoses of radiological images such as MRIs and X-rays.
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