Artificial intelligence in digital pathology: a roadmap to routine use in clinical practice |
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| Authors: | Richard Colling Helen Pitman Karin Oien Nasir Rajpoot Philip Macklin CM-Path AI in Histopathology Working Group David Snead Tony Sackville Clare Verrill |
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| Affiliation: | 1. Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford UK;2. National Cancer Research Institute, London, UK;3. Institute of Cancer Sciences, University of Glasgow, Glasgow, UK;4. Department of Computer Science, University of Warwick, Coventry, UK;5. Nuffield Department of Medicine, University of Oxford, Oxford, UK |
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| Abstract: | 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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| Keywords: | digital pathology image analysis artificial intelligence evidence-based |
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