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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Summary: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 practice of diagnostic histopathology and this has sparked a proliferation of image analysis software tools. While this is an exciting development that could discover novel predictive clinical information and potentially address international pathology workforce shortages, there is a clear need for a robust and evidence‐based framework in which to develop these new tools in a collaborative manner that meets regulatory approval. With these issues in mind, the NCRI Cellular Molecular Pathology (CM‐Path) initiative and the British In Vitro Diagnostics Association (BIVDA) have set out a roadmap to help academia, industry, and clinicians develop new software tools to the point of approved clinical use. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
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ISSN:0022-3417
1096-9896
1096-9896
DOI:10.1002/path.5310