Abstract: The recent years have witnessed a surge of interests on AI technologies which have already impacted a variety of aspects in our life, including medicine. Trained as an AI researcher, I have been focusing on the research of how AI can help with medicine for nearly 10 years. In this talk, I will give an overview of the research projects in my group currently. On methodology side, we do lots of research on traditional machine learning models with complex inputs and outputs, especially in the form of tensors. Another focus of my team is deep learning models, especially on how to inject knowledge into deep learning models and how to distill the knowledge out from deep learning models. On the medicine side, we have been trying to develop and apply those models in the problems of predictive modeling of clinical risks (hospital readmission, disease onset, morality, etc.), disease subtyping (especially Parkinson's disease), medication heterogeneous response analysis (e.g., Metformin for T2D patients), computational drug development (e.g., de-novo drug design and pharmacovigilance), as well as knowledge discovery from medical literatures. I will also point out the considerations, pitfalls, challenges and recent trends on the topic of AI in medicine.
Dr. Fei Wang is an Assistant Professor in Division of Health Informatics, Department of Healthcare Policy and Research, Weill Cornell Medicine, Cornell University. His major research interest is data mining, machine learning and their applications in health data science. He has published more than 200 papers on the top journals and conferences of related areas. His papers have received over 7,400 citations so far with an H-index 46. His (or his students’) papers won 6 best paper awards in international academic conference. He also won the NIPS/Kaggle Challenge on Classification of Clinically Actionable Genetic Mutations in 2017 and Parkinson's Progression Markers' Initiative data challenge organized by Michael J. Fox Foundation in 2016. Dr. Wang is the recipient of the NSF CAREER Award. He is also the chair of the KDDM working group in AMIA. Dr. Wang is the general co-chair of ICHI 2018 track chair for Medinfo 2017 and program co-chair for CHASE 2018 and ICHI 2015. Dr. Wang's research has been supported by NSF, NIH, ONR, NMRC, PCORI, MJFF, AHA and industries such as Amazon. Dr. Wang is an action editor of the journal Data Mining and Knowledge Discovery, an associate editor of IEEE Transactions on Neural Networks and Learning Systems, Journal of Health Informatics Research, Smart Health, Pattern Recognition, Knowledge and Information Systems. Dr. Wang has applied more than 40 US patents, among which 15 are granted.
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Monday, March 4, 2019 at 2:00pm to 3:00pm
Department of Healthcare Policy and Research, 3rd Floor Conference Room 425 East 61st Street