Clinical Considerations in Implementing AI Solutions for Healthcare
AI solutions developed for healthcare are often driven by considerations around maximizing technical performance. Technical performance is a necessary but far-from-sufficient consideration in evaluating the clinical utility of AI solutions. The Data Science and AI team at Partners Healthcare Pivot Labs invests a great deal of time thinking about the right questions, working out potential pitfalls and developing best practices in evaluating AI solutions for healthcare. This presentation will share insights obtained from real projects.
Dr. Kakarmath is a digital health scientist at Partners Healthcare Pivot Labs and an Instructor at Harvard Medical School. His research is focused on the evaluation of the clinical utility of digital health solutions, including machine learning and artificial intelligence-based products. Dr. Kakarmath's team works closely with technology innovators from academia, startups and industry giants to guide the ideation, design, prototyping, validation, and deployment of digital health solutions. His work has been published in prestigious journals and showcased at major academic conferences such as those of the American Academy of Neurology, the American Medical Informatics Association, the International Society for Pharmacoeconomics and Outcomes Research, the Connected Health Conference, Precision Medicine Summit and HIMSS.