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Next generation pathology: artificial intelligence enhances histopathology practice
Author(s) -
Acs Balazs,
Hartman Johan
Publication year - 2020
Publication title -
the journal of pathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.964
H-Index - 184
eISSN - 1096-9896
pISSN - 0022-3417
DOI - 10.1002/path.5343
Subject(s) - context (archaeology) , digital pathology , histopathology , pathology , pathological , artificial intelligence , risk stratification , computer science , perspective (graphical) , medicine , history , archaeology
Deep learning algorithms have shown benefits for pathology in the context of risk stratification of tumors. Although the results are promising, several steps have to be made to confirm clinical utility. In a recent issue of The Journal of Pathology , Colling et al present a perspective manuscript providing a roadmap to routine use of artificial intelligence in histopathology. In this commentary, we aimed to put these key points in the context of recent findings of AI and digital image analysis studies. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.