David N Louis1, Michael Feldman, Alexis B Carter, Anand S Dighe, John D Pfeifer, Lynn Bry, Jonas S Almeida, Joel Saltz, Jonathan Braun, John E Tomaszewski, John R Gilbertson, John H Sinard, Georg K Gerber, Stephen J Galli, Jeffrey A Golden, Michael J Becich. 1. From the Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston (Drs Louis, Dighe, and Gilbertson); the Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia (Dr Feldman); the Department of Pathology and Laboratory Medicine, Emory University, Atlanta, Georgia (Dr Carter); the Department of Pathology and Immunology, Washington University School of Medicine, St Louis, Missouri (Dr Pfeifer); the Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts (Drs Bry, Gerber, and Golden); the Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York (Drs Almeida and Saltz); the Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles (Dr Braun); the Department of Pathology and Anatomical Science, State University of New York at Buffalo (Dr Tomaszewski); the Department of Pathology, Yale Medical School, New Haven, Connecticut (Dr Sinard); the Department of Pathology and Laboratory Medicine, Stanford University, Palo Alto, California (Dr Galli); and the Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania (Dr Becich).
Abstract
CONTEXT: We define the scope and needs within the new discipline of computational pathology, a discipline critical to the future of both the practice of pathology and, more broadly, medical practice in general. OBJECTIVE: To define the scope and needs of computational pathology. DATA SOURCES: A meeting was convened in Boston, Massachusetts, in July 2014 prior to the annual Association of Pathology Chairs meeting, and it was attended by a variety of pathologists, including individuals highly invested in pathology informatics as well as chairs of pathology departments. CONCLUSIONS: The meeting made recommendations to promote computational pathology, including clearly defining the field and articulating its value propositions; asserting that the value propositions for health care systems must include means to incorporate robust computational approaches to implement data-driven methods that aid in guiding individual and population health care; leveraging computational pathology as a center for data interpretation in modern health care systems; stating that realizing the value proposition will require working with institutional administrations, other departments, and pathology colleagues; declaring that a robust pipeline should be fostered that trains and develops future computational pathologists, for those with both pathology and nonpathology backgrounds; and deciding that computational pathology should serve as a hub for data-related research in health care systems. The dissemination of these recommendations to pathology and bioinformatics departments should help facilitate the development of computational pathology.
CONTEXT: We define the scope and needs within the new discipline of computational pathology, a discipline critical to the future of both the practice of pathology and, more broadly, medical practice in general. OBJECTIVE: To define the scope and needs of computational pathology. DATA SOURCES: A meeting was convened in Boston, Massachusetts, in July 2014 prior to the annual Association of Pathology Chairs meeting, and it was attended by a variety of pathologists, including individuals highly invested in pathology informatics as well as chairs of pathology departments. CONCLUSIONS: The meeting made recommendations to promote computational pathology, including clearly defining the field and articulating its value propositions; asserting that the value propositions for health care systems must include means to incorporate robust computational approaches to implement data-driven methods that aid in guiding individual and population health care; leveraging computational pathology as a center for data interpretation in modern health care systems; stating that realizing the value proposition will require working with institutional administrations, other departments, and pathology colleagues; declaring that a robust pipeline should be fostered that trains and develops future computational pathologists, for those with both pathology and nonpathology backgrounds; and deciding that computational pathology should serve as a hub for data-related research in health care systems. The dissemination of these recommendations to pathology and bioinformatics departments should help facilitate the development of computational pathology.
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