Wednesday, December 9, 2020 1:00 pm ET - 3:00 pm ET:
Artificial Intelligence and Machine Learning in Pathology
Moderator: Thomas Durant, MD, Yale School of Medicine
Talk 1: Machine Learning 101 - David McClintock, MD, PhD, Michigan Medicine
Talk 2 : Artificial Intelligence in Pathology Practice - Toby Cornish, MD, PhD, University of Colorado School of Medicine
- Understand the fundamentals of machine learning (ML), including supervised, unsupervised, and deep learning
- Recognize how ML is used within artificial intelligence AI), including how to apply AI and ML to the practice of pathology
- Recognize the technical, operational, cost, and human barriers affecting the adoption of AI & ML within Anatomic Pathology and how to overcome/mitigate them
CME ACCREDITATION STATEMENT: This activity has been planned and implemented in accordance with the accreditation requirements and policies of the Accreditation Council for Continuing Medical Education (ACCME) through the joint providership of the University of Michigan Medical School and Association for Pathology Informatics. The University of Michigan Medical School is accredited by the ACCME to provide continuing medical education for physicians.
The University of Michigan Medical School designates this Live Activity for a maximum of TWO (2) AMA PRA Category 1 Credit(s). Physicians should claim only the credit commensurate with the extent of their participation in the activity.
David McClintock, MD, PhD
Associate CMIO, Michigan Medicine
Director, Digital Pathology
Associate Director, Pathology Informatics
Associate Professor, Dept. of Pathology
Michigan Medicine/University of Michigan
Ann Arbor, MI
David McClintock is an Associate CMIO of Michigan Medicine (Pathology Informatics), Director of Digital Pathology, and Associate Professor at the University of Michigan. Dr. McClintock‘s primary clinical interests comprise of operational pathology and clinical laboratory informatics including workflow analysis, Laboratory Information System (LIS) optimization, and improved integration of pathology and clinical laboratory data within the EHR and clinical research data warehouses. His research interests include understanding the role and effects of whole slide imaging and digital pathology within the clinical laboratories, the effects of computational pathology and machine learning on diagnostics testing and patient outcomes, and how to enable laboratory data analytics in order to provide both pathologists and clinicians opportunities to better optimize patient care and clinical decision-making.
Toby C. Cornish, MD, PhD
Medical Director of Informatics, Associate Professor
University of Colorado School of Medicine
Dr. Cornish is an Associate Professor of Pathology at The University of Colorado School of Medicine where he practices gastrointestinal pathology and serves as the Medical Director of Informatics for the department of pathology and Medical Director of the LIS for the UCHealth system. His interests include histologic image analysis, digital pathology in education and clinical practice, computational pathology and mobile applications for pathology education. Dr. Cornish has co-developed software packages for biomarker quantitation including TMAJ/FrIDA, PIP, and HPASubC. Dr. Cornish is the co-author of several educational apps for the iPad: The Johns Hopkins Atlas of Pancreatic Pathology, The Johns Hopkins Atlas of Pancreatic Cytopathology, The Johns Hopkins Flashcards App and the iCarebook for Pancreatic Cancer, and he is a series editor for the ongoing Johns Hopkins Atlases of Pathology series of apps. He was named to The Pathologist magazine's Power List 2020 for Big Breakthroughs, serves on the Editorial Board for Modern Pathology and is an Associate Editor for the American Journal of Clinical Pathology.