Artificial intelligence in digital pathology: a roadmap to routine use in clinical practice

The use of artificial intelligence will transform clinical practice over the next decade and the early impact of this will likely be the integration of image analysis and machine learning into routine histopathology. In the UK and around the world, a digital revolution is transforming the reporting...

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Bibliographic Details
Published in:	The Journal of pathology Vol. 249; no. 2; pp. 143 - 150
Main Authors:	Colling, Richard, Pitman, Helen, Oien, Karin, Rajpoot, Nasir, Macklin, Philip, Bachtiar, Velicia, Booth, Richard, Bryant, Alyson, Bull, Joshua, Bury, Jonathan, Carragher, Fiona, Collins, Graeme, Craig, Clare, da Silva, Maria Freitas, Gosling, Daniel, Jacobs, Jaco, Kajland‐Wilén, Lena, Karling, Johanna, Lawler, Darragh, Lee, Stephen, Miller, Keith, Mozolowski, Guy, Nicholson, Richard, O'Connor, Daniel, Rahbek, Mikkel, Sumner, Alan, Vossen, Dirk, White, Kieron, Wing, Charlotte, Wright, Corrina, Snead, David, Sackville, Tony, Verrill, Clare
Format:	Journal Article
Language:	English
Published:	Chichester, UK John Wiley & Sons, Ltd 01.10.2019 Wiley Subscription Services, Inc
Subjects:	analysis artificial Artificial intelligence Artificial Intelligence - standards Artificial Intelligence - trends Clinical medicine Computer programs Diagnosis, Computer-Assisted - standards Diagnosis, Computer-Assisted - trends Diffusion of Innovation digital evidence‐based Forecasting Histopathology Humans Image Interpretation, Computer-Assisted - standards Image processing intelligence Learning algorithms Pathology Pathology - standards Pathology - trends Predictive Value of Tests Regulatory approval Reproducibility of Results Workflow United Kingdom > UK digital image artificial pathology analysis evidence-based intelligence
ISSN:	0022-3417, 1096-9896, 1096-9896
Online Access:	Get full text
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