14.45 – 15.25 Ulysses Balis - The challenge of making encoded data clinically actionable
While application of machine learning techniques to histological images and, more recently, libraries of histological images, holds the promise to augment the contemporary diagnostic paradigm in digital WSI use for conventional surgical pathology, there yet exist substantial barriers between simply having available a computational pipeline capable of generating medically actionable knowledge and implementing a robust clinical solution intended for direct use by busy surgical pathologists. To address this challenge, the Pathology Informatics Division at the University of Michigan has been involved in the long-term development of a generalizable model by which both anatomic and clinical pathology computational pipelines can be deployed at scale, and in a fashion that is immediately accessible to pathologists, who might not otherwise possess specific machine vision or programming skills. This presentation will focus specifically on a panel of mage-based analytical tools and computational pipelines that have been developed by the Michigan team, in specific support of actual surgical pathology workflow challenges in the setting of a busy, high volume practice. Example applications will include: generalizable image-based search, automated annotation, and automated segmentation tools.
CV Dr Balis is professor of Pathology at the University of Michigan and currently serves as the director of the Division of Pathology Informatics, in the Department of Pathology. He is a board-certified Pathology Informaticist, with longstanding interest in the intersection of computational approaches and the practice of medicine. This division he directs is noteworthy for being one of the few such academic information technology divisions operating in support of pathology while being housed wholly within the pathology department itself. He has active, NIH R01-supported research initiatives in several areas of pathology and medical informatics, including machine learning and use of encoded data, image-based analytics, machine vision tools for histopathology, image-based search algorithms and federated enterprise data architectures, with all of these areas serving as rich training substrate for a growing and thriving pathology informatics fellowship â€“ one of only five such programs in the U.S. Dr. Balis has had a longstanding interest in pathology informatics education, and currently serves as a standing member on the Clinical Informatics Subspecialty Boards Exam Committee. Dr. Balis is the author of over 100 publications, multiple patents, numerous book chapters and is co-editor of a contemporary text on the topic of Pathology Informatics (along with Drs. Mark Tuthill and Liron Pantanowitz). He has delivered over 180 invited presentations, nationally and internationally, on various topics related to: pathology informatics, image analysis, data analytics and automation.