Welcome to the Healthcare Operational Research (HCOR) special interest group website!

Canadian Healthcare Optimization Workshop (CHOW) 2025:

The Health Care Operational Research Special Interest Group (HCOR SIG) of the Canadian Operational Research Society (CORS) is proud to host the Canadian Healthcare Optimization Workshop (CHOW). This workshop provides a forum for researchers with a common interest in healthcare optimization to share the latest advances with other researchers and practitioners in the field. The workshop also connects researchers with practitioners to discuss innovative solutions and best practices that help improve the effectiveness of the healthcare system. This year’s program includes presentations by researchers and practitioners, as well as roundtable discussions.

CHOW will be held on Sunday, June 8 (the day before the start of the CORS Conference) in Edmonton. The event will take place at the University of Alberta campus (easily accessible with public transit from the conference hotel). More info on the event and the program to come. Registration will be available on the conference website soon.

CORS Micro-Event (online): 1-2pm EST, January 21, 2025

This micro-event will be an online zoom seminar co-presented by Dr. Tinglong Dai and Dr. Risa Wolf. You are cordially invited to attend this event by registering at https://bit.ly/MedAI25 A zoom link will be sent to the registered emails before the event date. Please refer to the following for details about the online seminar.

Title: Medical A.I. Revolution: Research Opportunities for OR/MS Scholars

Abstract: Artificial intelligence (AI) is set to revolutionize healthcare delivery globally, offering unprecedented opportunities for operations research and management science (OR/MS) researchers. As AI becomes embedded in healthcare workflows, it will not only reshape how care is delivered but also challenge the traditional models used to analyze healthcare systems. This talk, featuring Dr. Michael Abramoff, inventor of the first FDA-cleared autonomous AI system, and Dr. Tinglong Dai, a leading Johns Hopkins expert in medical AI, will explore the emerging research opportunities for OR/MS scholars in response to AI’s integration into healthcare. We will highlight the need for new models that can guide the rapid evolution of healthcare practices, assess productivity improvements, and address disparities in access to care. Also, AI’s potential to learn and adapt presents opportunities to develop models for real-time decision-making, but these systems must undergo rigorous development, validation, and approval processes. We will also discuss the regulatory and reimbursement challenges that AI in healthcare faces, opening the door for OR/MS researchers to contribute solutions to these key barriers.

Bio of Speakers:

Tinglong Dai, PhD, is Ferrari Professor of Business at Johns Hopkins University, where he co-directs the Bloomberg Distinguished Professor Cluster on Global Advances in Medical Artificial Intelligence. Named one of the World’s Top 40-Under-40 Business School Professors by Poets & Quants, Dr. Dai is a sought-after expert featured in major media outlets, including Bloomberg, CNN, NPR, The Wall Street Journal, and The New York Times. Dr. Dai serves as Vice President of Marketing, Communication, and Outreach for INFORMS. He is an Associate Editor for Management Science, MSOM, POM, and npj Digital Medicine, etc.

Risa Wolf, MD, is an Associate Professor of Pediatric Endocrinology and Director of the Pediatric Diabetes Center at Johns Hopkins School of Medicine. A leading expert in AI-driven healthcare innovation, she focuses on diabetes management and early detection. Dr. Wolf pioneered the use of autonomous AI for diabetic retinopathy screening in children, demonstrating its safety, efficacy, and equity through groundbreaking randomized controlled trials. She serves as Medical Director of Camp Charm City. Along with Dr. Tinglong Dai, she co-chairs the Johns Hopkins Workgroup on AI and Healthcare and leads multiple research initiatives integrating AI into healthcare workflows.