Carolyn Glass, MD, PhD, co-director of the Duke Division of Artificial Intelligence (AI) and Computational Pathology and division chief of Duke Cardiovascular Pathology, was invited to chair and moderate the Generative AI for Healthcare Summit held on Nov. 14th, 2023 in Cambridge, Massachusetts. The summit gathered health care academic, industry, and business leaders to discuss the biggest long-term impacts of generative AI in the healthcare space.
Generative AI, a subset of AI, has shown tremendous potential in reshaping industries, and is the type capable of generating text, images, code or other types of content, often in response to a prompt entered by a user.
Some of the distinguished speakers and panelists included:
- Steven Lin, MD, founder and executive director, Stanford Healthcare AI Applied Research Team; vice chief for Technology Innovation, Division of Primary Care and Population Health (Primary Care Physician)
- Sandy Aronson, ALM, MA, executive director of Information Technology, Mass General Brigham Personalized Medicine (Information Technologist)
- Sumeet Chugh, director, Division of Artificial Intelligence in Medicine, Cedars Sinai Health System (Cardiologist)
- Aalpen A. Patel, MD, MBA, director for Artificial Intelligence, Geisinger and Steele Institute for Health Innovation; medical director for Artificial Intelligence; Chair, Department of Radiology (Radiologist)
- Jana Gunn, MS, senior director of Advanced Analytics and Data Science, Blue Cross Blue Shield of Minnesota (Finance)
Glass, who has spent the last 30 years in healthcare, discussed her perspective of the healthcare industry. In her first 20 years, she served primarily as a patient-facing clinician focused on treating diseases. She spent her first decade as a physician assistant in neurology/neurodegenerative disorders and international health/primary care; and her second decade as a vascular surgeon. She has spent the last ten years on the diagnostic side of healthcare as a cardiothoracic pathologist.
“I’ve come to appreciate both the diagnostic and treatment sides of medicine as well as the pain points of them both,” noted Glass. “In our field of diagnostic pathology, we have seen a rapid rise in interest in digitization of visual data and many potential use cases for machine learning algorithm development, some which integrate the use of generative AI. I look forward to solving problems through multi-disciplinary initiatives that harness the positives of innovation.”
