The goal of the NextGen Precision Health & Neuroscience Science Seminar is to highlight transdisciplinary precision research taking place in the field, provide opportunities for collaboration among researchers to build their own research efforts and promote clinical/researcher activity across the University of Missouri System and our partners.
For questions about this event, please reach out to Veronica Lemme at firstname.lastname@example.org.
“Precision Health Discovery with eXplainable and Actionable Artificial Intelligence (X2AI): Unraveling Subgroup Cohorts for Enhanced Clinical Insights in Autism Protective Mechanisms and Precision Cancer Drug Repositioning”
Presented by: Chi-Ren Shyu, Ph.D. FAMIA, Director Institute for Data Science and Informatics, Paul K. & Dianne Shumaker Professor, College of Engineering, University of Missouri
Date: Nov. 20, 2023, 4-5 p.m.
Location: Tom and Linda Atkins Family Seminar Room, Roy Blunt NextGen Precision Health Building
Precision health care relies on effectively stratifying clinical trial participants to optimize treatment outcomes. While modern artificial intelligence (AI) and machine learning (ML) approaches have provided valuable support, they often fall short in explaining the intricate physiological mechanisms or suggesting actionable interventions. In this presentation, Dr. Shyu will introduce two innovative Mizzou-developed X2AI solutions: the Adaptive Complexity Deep Neural Network (ACD-NN) to address small sample size issues in clinical research, and Exploratory Cohort Knowledge Discovery in Database (EC-KDD) to expedite patient stratification, saving both time and resources. The talk addresses three critical questions through these AI/ML innovations: (1) What novel hypotheses can be tested to yield clinically relevant findings? (2) How can we unravel the intricate and multifaceted relationships that distinguish patient subgroups from the general population? (3) Which patient cohorts stand to benefit from efficient and actionable interventions for successful treatment outcomes? Dr. Shyu will discuss case studies that have inspired the development of trustworthy and transparent X2AI tools in understanding protective mechanisms in autism and drug repositioning research for cancers.
Chi-Ren Shyu is a Paul K. and Dianne Shumaker Professor for Biomedical Informatics of Engineering and serves as the Director of MU Institute for Data Science and Informatics, where 68 core faculty members from 27 departments collaborate extensively on data science/AI research and provide comprehensive training for over 50 Ph.D. students in Informatics and 90 M.S. students in Data Science & Analytics. Chi-Ren is an elected Fellow of American Medical Informatics Association and American College of Medical Informatics.