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Discovering the causes of cancer and the means of prevention

Accessible Artificial Intelligence for Cancer Research

DCEG Seminar

Jason Moore

Speaker
Jason H. Moore, Ph.D.,
Edward Rose Professor of Informatics
Director, Institute for Biomedical Informatics
Director, Division of Informatics,
Department of Biostatistics, Epidemiology, & Informatics
Senior Associate Dean for Informatics
The Perelman School of Medicine
University of Pennsylvania

Description
Artificial intelligence (AI) has finally emerged as a useful tool for big data analytics. This is due to decades of research that have provided powerful algorithms and the availability of plentiful computing resources. Despite these advances, AI is not widely accessible due to a steep learning curve and the expense and black box nature of software provided by commercial vendors such as IBM. In response to this need, we have developed an accessible, open-source, and user-friendly AI system at the University of Pennsylvania (PennAI) to bring AI and automated machine learning technology to everyone who wants to incorporate this technology into their big data analytics agenda. We will provide an overview of the system and an update on its features. We will discuss its application to cancer research.

Host
Rachael Stolzenberg-Solomon, Ph.D., M.P.H., R.D., Senior Investigator, Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, NCI

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