Multimedia Artificial Intelligence in Precision Medicine
Multimedia Artificial Intelligence in Precision Medicine


This talk is about the development of the next generation of AI and machine learning tools in medicine. The new machine learning tools can teach computers to understand medical images, patient charts and lab tests, facial and motion videos, audios, and to read complex documents, and integrate and model extracted features and values of these multimedia, multimodal patient data to allow physicians to make more accurate and timely diagnosis and treatments. We will illustrate the multimedia AI tools implemented with two clinical case studies in cancer overdiagnosis and stroke detection.


Stephen Wong is the John S. Dunn Sr. Presidential Distinguished Chair and Chief Research Information Officer at Houston Methodist; Associate Director of Bioinformatics and Biostatistics Cores and Chair of Systems Medicine and Bioengineering Department at Houston Methodist Cancer Center; Director of T.T. and W.F. Chao Center for BRAIN and Director of Advanced Cellular and Tissue Microscopy Core at Houston Methodist Research Institute; and a Professor of Radiology, Neurosciences, Pathology and Laboratory Medicine of Cornell University. His research covers drug discovery, systems biology, biomedical imaging, and digital health for combating cancer and neurologic disorders. Previously, he was a professor at UCSF and Harvard University, handling major medical information and imaging system design and implementation at UCSF, Harvard Medical School, and the Brigham and Women’s Hospital. Stephen has served in technical and executive roles in other major technology-driven companies including HP, AT&T Bell Labs, Philips Healthcare, and Charles Schwab, where his group developed one of the first and largest web trading platforms. He received his Ph.D. and M.Sc. in Computer Science (AI) from Lehigh University, B.Eng. in Electrical Engineering (hons) from the University of Western Australia, and senior executive education from Stanford Graduate School of Business, MIT Sloan School of Management, and Columbia Business School. He reviews research grants regularly for NIH, DOD, research foundations and federal agencies of other countries and serves on advisory boards on several non-profit foundations and organizations. His research has been consistently funded by NIH for 25 years. He is a fellow of IEEE and a registered professional engineer.

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