6th Illinois Health Data Analytics Summit

Summit Proceedings

Wednesday, April 5, 2023

Generative AI - A Promising Catalyst for Healthcare?

Please save the date of April 5, 2023 to join us at the 6th Health Data Analytics Summit. This virtual platform will bring leaders in healthcare, medicine, science, and business together to discuss the latest AI and machine learning trends in Healthcare. This year, we will focus on applications of rapidly emerging Generative Models and investigate how they can be leveraged to synthesize increasingly realistic and useful electronic health record (EHR) data, including images, sounds, and videos. We will discuss various deep generative model frameworks, their applications, and the risk of generative AI and its potential positive economic impact in accelerating healthcare-related predictive model development.

Time	Item
8:45 – 9:00 a.m.	Welcome and Opening Remarks Susan Martinis, Ph.D., Vice Chancellor for Research and Innovation, University of Illinois Urbana-Champaign (UIUC) Rashid Bashir, Ph.D., Dean, Grainger College of Engineering, University of Illinois Urbana-Champaign (UIUC) James Rehg, Ph.D., Founder Professor, Computer Science, and Industrial and Enterprise Systems Engineering, and Director, Health Care Engineering Systems Center, University of Illinois Urbana-Champaign (UIUC) Chairs of the 6^th Illinois Health Data Analytics Summit- Ilan Shomorony, Ph.D., Assistant Professor, Computer & Electrical Engineering, University of Illinois Urbana-Champaign (UIUC); Yuxiong Wang, Ph.D., Assistant Professor, Computer Science, University of Illinois Urbana-Champaign (UIUC)
9:00 – 9:45 a.m.	Keynote I \| Towards Generative Models for Analyzing Computer Tomography Scans Alan L. Yuille, Ph.D., Bloomberg Distinguished Professor of Cognitive Science and Computer Science, Johns Hopkins University Chair: Yuxiong Wang, Ph.D., Assistant Professor, Computer Science, UIUC
9:45 - 10:30 a.m.	Keynote II \| Out of Distribution Generalization Rajesh Ranganath, Ph.D., Assistant Professor, Computer Science and Data Science, Courant Institute, New York University (NYU) Chair: Ilan Shomorony, Ph.D., Assistant Professor, Electrical & Computer Engineering, UIUC
10:30 – 10:50 a.m.	Break
10:50 – 11:50 a.m.	Session I \| The Different Modalities of Generative AI Description: Discussions of different modalities of Generative AI sequence, image, text, graphs, algorithms, architectures, and their latest advancements including security and privacy. Chair: Ilan Shomorony, Ph.D., Assistant Professor, Electrical & Computer Engineering, UIUC 1. SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation Alexander Schwing, Ph.D., Associate Professor, Department of Electrical and Computer Engineering, UIUC 2. Clinically-Driven Virtual Patient Cohorts Generation: An Application to Aorta Miguel Lozano, Ph.D., Associate Professor, School of Engineering at the University of Valencia 3. Large Scale Machine Learning Models in Mobile Health James Rehg, Ph.D., Founder Professor, Computer Science, and Industrial and Enterprise Systems Engineering, and Director, Health Care Engineering Systems Center, UIUC 4. Generative language models for clinical documentation Jon Stevens, Ph.D., AI Language Capability Lead, Information Research, AbbVie 5. Mind’s Eye: Mental Hallucination for Open-World Perception Yuxiong Wang, Ph.D., Assistant Professor, Computer Science, UIUC 6. Large Language Models Encode Clinical Knowledge Vivek Natarajan, MS, AI Researcher, Google
11:50 a.m. - 12:00 p.m.	Break
12:00 – 12:45 p.m.	Keynote III \| Generative AI in Healthcare Jimeng Sun, Ph.D., Health Innovation Professor, Computer Science, and Carle Illinois College of Medicine, UIUC Chair: James Rehg, Ph.D., Founder Professor, Computer Science, and Industrial and Enterprise Systems Engineering, and Director, Health Care Engineering Systems Center, UIUC
12:45 - 2:00 p.m.	Panel \| Generative AI in Healthcare Moderators: Kapila Monga, Head of Data Science, Bon Secours Mercy Health; ChengXiang Zhai, Ph.D., Professor Computer Science, UIUC Description: This panel brings academia and industry together in one forum to discuss and assess the promise of Generative AI for healthcare. The panel will deliberate on early successes, opportunity areas, and clinical workflow integration related aspects of Generative AI. The panel will also discuss the impact of Generative AI on different types of healthcare organizations (big hospitals / small hospitals / research driven organizations / hospitals in rural areas) at the current stage of evolution. Panelists 1. Jimeng Sun, Ph.D., Health Innovation Professor, Computer Science, and Carle Illinois College of Medicine, UIUC 2. Jon Stevens, Ph.D., AI Language Capability Lead, Information Research, AbbVie 3. Brandon Nelson, Ph.D., Fellow, Division of Imaging, Diagnostics, and Software Reliability, U.S. Food & Drug Administration (FDA) 4. Alexandre Carvalho, M.D., Infectious Disease Fellow, Northwestern Memorial Hospital 5. Vivek Natarajan, MS, AI Researcher, Google
2:00 – 3:00 p.m.	Session II \| Generative Models applied in Healthcare Description: Use cases from different areas of healthcare, application/risks in medical education, issues in ethics, compliance/legal, IP. Chair: Yuxiong Wang, Ph.D., Assistant Professor, Computer Science, UIUC 1. Assessing the ability of deep generative models to learn canonical medical image statistics Varun Kelkar, Ph.D. Candidate, Computational Imaging Science Lab, Electrical & Computer Engineering, UIUC 2. Developing Generated AI Solutions for Rare Disease Care May Dongmei Wang, Ph.D., Professor, and The Wallace H. Coulter Distinguished Faculty Fellow and Director of Biomedical Big Data Initiative, Georgia Institute of Technology and Emory University 3. Synthesizing Medical Data with Privacy Guarantees: Fantasy or Plausibility? Vincent Bindschaedler, Ph.D., Assistant Professor, Computer & Information Science & Engineering, University of Florida 4. Generative Modeling for Medical Education and Training Yogatheesan Varatharajah, Ph.D., Research Assistant Professor, Bioengineering, UIUC 5. I didn’t know StyleGAN could do THAT David Forsyth, Ph.D., Fulton Watson Copp Chair in Computer Science, UIUC 6. Accelerating Pediatric Medical Device Innovation with Regulatory Science Tools (RSTs): A Case Study on Pediatric Deep Learning CT Image Reconstruction Brandon Nelson, Ph.D., Staff Fellow, Division of Imaging, Diagnostics, and Software Reliability, U.S. Food & Drug Administration (FDA)
3:00 - 3:30 p.m.	Live Demonstration \| Synthetic Data Generation Chair: Jimeng Sun, Ph.D. Live demonstration of PyHealth, a powerful library and tool set designed for both machine/deep learning researchers and medical practitioners to train, test and validate algorithms with publicly available data sets. Organized by Sunlab Students.
3:30 p.m.	Closing Remarks Summit Chairs: Yuxiong Wang, Ph.D., Ilan Shomorony, Ph.D.

Photo shows logos of summit sponsors

Alan L. Yuille
Johns Hopkins University

Dr. Alan Yuille received the BA degree in mathematics from the University of Cambridge in 1976. His PhD on theoretical physics, supervised by Prof. S.W. Hawking, was approved in 1981. He was a research scientist in the Artificial Intelligence Laboratory at MIT and the Division of Applied Sciences at Harvard University from 1982 to 1988. He served as an assistant and associate professor at Harvard until 1996. He was a senior research scientist at the Smith-Kettlewell Eye Research Institute from 1996 to 2002. He was a full professor of Statistics at the University of California, Los Angeles, as a full professor with joint appointments in computer science, psychiatry, and psychology. He moved to Johns Hopkins University in January 2016. His research interests include computational models of vision, mathematical models of cognition, medical image analysis, and artificial intelligence and neural networks.

Rajesh Ranganath
Courant Institute, NYU

Dr. Ranganath is an Assistant Professor at the Courant Institute at NYU in Computer Science and at the Center for Data Science. I am also part of the CILVR group. My research interests include causal, statistical, and probabilistic inference, out-of-distribution detection and generalization, deep generative modeling, interpretability, and machine learning for healthcare. Before joining NYU, I earned degrees in computer science; my PhD was completed at Princeton University working with Dave Blei and my undergraduate was done at Stanford University. I have also spent time as a research affiliate at MIT’s Institute for Medical Engineering and Science.

Jimeng Sun
UIUC

Dr. Sun is a Health Innovation Professor at the Computer Science Department and at Carle Illinois College of Medicine at University of Illinois Urbana-Champaign. Before University of Illinois Urbana-Champaign, he was an associate professor in College of Computing at Georgia Tech (GT) and the co-director of the Center for Health Analytics and Informatics (CHAI) at GT. His research focuses on artificial intelligence (AI) for healthcare, including deep learning for drug discovery, clinical trial optimization, computational phenotyping, clinical predictive modeling, treatment recommendation, and health monitoring. He was recognized as one of the Top 100 AI Leaders in Drug Discovery and Advanced Healthcare by Deep Knowledge Analytics. He has published over 300 papers and has 20,361 citations, h-index 73, and i10-index 196. Dr. Sun has a diverse funding portfolio with $6.25m in sponsored research funds since 2014. He also has several NSF/NIH-funded projects with leading hospitals such as MGH, Sutter Health, Vanderbilt, Northwestern, Geisinger, and Emory. Dr. Sun collaborates with the biomedical industry including IQVIA, the largest health data science company, and multiple pharmaceutical companies on health data science. He completed his B.S. and M.Phil. in computer science at Hong Kong University of Science and Technology in 2002 and 2003, respectively, and his Ph.D. in computer science at Carnegie Mellon University in 2007.

Planning Committee

George Heintz (Summit Organizer)
University of Illinois Urbana-Champaign

Ilan Shomorony (Chair)
University of Illinois Urbana-Champaign

Yuxiong Wang (Chair)
University of Illinois Urbana-Champaign

William Gropp
University of Illinois Urbana-Champaign

Jodi Schneider
University of Illinois Urbana-Champaign

Irfan Ahmad
University of Illinois Urbana-Champaign

Sridhar Seshadri
University of Illinois Urbana-Champaign

Tony Michalos

University of Illinois Urbana-Champaign

Ravi Iyer
University of Illinois Urbana-Champaign

Jimeng Sun
University of Illinois Urbana-Champaign

John Vozenilek
OSF HealthCare

Jonathan Handler
OSF HealthCare

David Liebovitz
Northwestern University

Kapila Monga
Bon Secours Mercy Health University

May Wang
Georgia Tech University

Carolyn Beck
University of Illinois Urbana-Champaign

Paul Arnold
Carle Foundation Hospital

Maria Jaromin
University of Illinois Urbana-Champaign

ChengXiang Zhai
University of Illinois Urbana-Champaign

Rajarsi Gupta
Stony Brook University

Brad Sutton
University of Illinois Urbana-Champaign

James Rehg
University of Illinois Urbana-Champaign

Nie Summing
University of Illinois Urbana-Champaign

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6th Illinois Health Data Analytics Summit

Summit Proceedings

Wednesday, April 5, 2023

Generative AI - A Promising Catalyst for Healthcare?

Planning Committee

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