Carolyn Glass, MD, PhD, presented a talk titled “Machine Learning (ML) and Computational Pathology in Non-Imaging Pathology Applications” at the College of American Pathologists (CAP) Artificial Intelligence (AI) Committee in San Diego, CA, on Sept. 17th. As Chair of the AI Products Working Group, Glass oversees topics that guide discussion and policy on development of products that monitor AI/ML model performance not only prior to clinical adoption but also on an ongoing basis.
In her talk, she reviewed high impact, non-image, clinical pathology use-cases which included machine learning applied to hematologic/lymphoproliferative disorders (flow cytometry), infectious diseases (MALDI-TOF-MS), molecular analysis (high-throughput sequencing data) and clinical chemistry.
The CAP AI Committee, chaired by Duke Pathology Professor Rajesh Dash, MD, was established in 2019 to serve as a focal point for AI and ML related inquiries and activities for the CAP from internal and external sources. Committee activities include, but are not limited to, creation and maintenance of an AI strategy; service as a consultant to councils and committees in relation to AI-related projects and programs; and collaboration with the Council on Government and Professional Affairs (CGPA) and other appropriate councils and committees to ensure coordination of discussions with regulatory agencies, such as the U.S. Food & Drug Administration (FDA). Committees members include experts in the field of computational pathology, digital pathology and informatics across leading academic institutions and private practices.