AI Health Invited Talk Series

AI Health Invited Talk Series

Sponsored by: Mary R. Boyvey Dean's Excellence Fund and Suit Endowment Fund
School of Information, University of Texas at Austin

Seminar: Fighting against COVID-19: Clinical Research, Drug Discovery, and Literature Mining

jointly organized by School of Information and Dell Medical School, UT Austin

When: noon-3PM, April 23, 2020
Location: Zoom
Recording: 3 hour long video at youtube

12:05-12:20: Making Flutter apps in the COVID-19 era (John Manning: Assistant Professor/Director of Clinical Informatics, Atrium Health's Carolinas Medical Center, Emergency Department)
12:20-12:45: COVID-19 Patient Analysis (Benjamin Glicksberg, Assistant Professor, Jessica De Freitas, PhD student, Icahn School of Medicine at Mount Sinai)
12:45-1:10: CDS and Data Standards for COVID-19 (Justin Rousseau, Assistant Professor, Dell Med, UT Austin)
1:10-1:35: Automatic Named Entity Recognition and Evidence Mining in COVID-19 Literature (Xuan Wang, Graduate student, Jiawei Han, Professor, University of Illinois at Urbana-Champaign)
1:35-2:00: Reversal of Infected Host Gene Expression Identifies Repurposed Drug Candidates for COVID-19 (Bin Chen, Assistant Professor, Jing Xing, research associate, Michigan State University)
2:00-2:25: An academic perspective on drug discovery & repositioning for COVID-19 (Tudor Oprea, Professor and Chief, Jeremy Yang, Senior Researcher, Translational Informatics Division, U of New Mexico)
2:25-2:40: COVID-19 publications: Innovation and Collaboration (Meijun Liu, University of Hong Kong & National Bureau Of Economic Research)
2:40-3:00: Q&A

Title: Advancing Biomedical Research in a Data-driven World through Informatics Innovation

jointly organized by School of Information and Dell Medical School, UT Austin

When: 3:30-4:40PM, Jan 29, 2020
Location: Health Learning Building, Room 1.111. The address for the HLB is 1501 Red River St, Austin, TX 78712
Speaker: Guo-Qiang ZHANG, Vice President and Chief Data Scientist, The University of Texas Health Science Center at Houston

Abstract: In this presentation, Dr. Zhang will provide an overview of a range of data science use cases in the health and clinical research setting. In addition, he will focus on a central linkage for human-data interaction: query and exploration tools for accessing data resources. He will review use cases and informatics tools developed recently in his group. An active research program is to repurpose existing ontologies by transforming them into nested facet systems (NFS) to support human-data interaction. Dr. Zhang will introduce the concept of NFS and outline opportunities involved in using ontologies as NFS for querying and exploring data, especially in the biomedical domain.

Bio: Dr. Zhang is Vice President and Chief Data Scientist for The University of Texas Health Science Center at Houston (UTHealth). He is a Professor in Medicine, Biomedical Informatics and Public Health, and Co-Director, Texas Institute for Restorative Neurotechnologies. Prior to joining UTHealth, he was Professor of Internal Medicine and Computer Science at the University of Kentucky, where he also served as the university's inaugural Director for the Institute for Biomedical Informatics, and Associate Director for the Center for Clinical and Translational Science. His longest career stretch has been spent at Case Western Reserve University, where his role included Division Chief of Medical Informatics, Co-Director of Biomedical Research Information Management Core of the Case Western CTSA, and Associate Director for Case Comprehensive Cancer Center. Dr. Zhang received his PhD from the University of Cambridge. His earlier research interests included theoretical computer science and semantics of programming languages. In the last decade, his research has revolved around Human-Data Interaction (HDI), achieved through the development of innovative software and web-based applications spanning the biomedical data lifecycle. Software tools include query interface for clinical research, data management software for clinical trials and biomedical research, and tools for multi-site data integration. He led the development of data infrastructures and manages data resources, following the vision of NIH Data Commons, for the National Sleep Research Resource and for Center for Sudden Unexpected Death in Epilepsy Research, a largest and comprehensive, well-annotated clinical data sets in the two disease areas. He also has a track record of research in biomedical metadata including ontologies and terminology systems, to bring them to bear on HDI. Dr. Zhang effectively brings cutting-edge computer science and informatics methodology to addressing biomedical data/big data challenges through the translation of theory, algorithms, methods and best practices to functional and usable tools impacting the clinical research data lifecycle.

Title: Can Policy Affect Initiation of Addictive Substance Use? Evidence from Opioid Prescribing

jointly organized by School of Information and Dell Medical School, UT Austin

When: 3-4PM, Sept 24, 2019
Location: UTA, 5th floor, 5.522, School of Information, UT Austin
Speaker: Kosali Simon, Herman Wells Professor, Associate Vice Provost for Health Sciences at Indiana University Bloomington

Abstract: Drug control policy can have unintended consequences by pushing existing users to alternative, possibly more dangerous substances. Policies that target only new users may therefore be especially promising. Using commercial insurance claims data, we provide the first evidence on a set of new policies intended to reduce opioid initiation in the form of limits on initial prescription length. We also provide the first evidence on the impact of must-access prescription drug monitoring programs (MA-PDMPs), laws that do not target new users, on initial opioid use. Although initial limit policies reduce the average length of initial prescriptions, they do so primarily by raising the frequency of short prescriptions, resulting in increases in opioids dispensed to new users. In contrast, we find that MA-PDMPs reduce opioids dispensed to new users, even though they do not explicitly set out to do so. Neither policy significantly affects extreme use such as doctor shopping among new patients, because such behavior is very rare. Paper is availalbe at:

Bio: Kosali Simon is a health economist whose conducts research on health insurance and health care policy. She mainly focuses on the impact of health insurance reform on healthcare and labor market outcomes, and on the causes and consequences of the opioid crisis. She is the Herman Wells Professor, and Associate Vice Provost for Health Sciences at Indiana University Bloomington, O'Neill School of Public and Environmental Affairs. She is also Editor of Journal of Health Economics and Co-Editor of Journal of Human Resources.