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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| Vydáno v: | The Journal of pathology Ročník 249; číslo 2; s. 143 - 150 |
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| Hlavní autoři: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Chichester, UK
John Wiley & Sons, Ltd
01.10.2019
Wiley Subscription Services, Inc |
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| ISSN: | 0022-3417, 1096-9896, 1096-9896 |
| On-line přístup: | Získat plný text |
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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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| AbstractList | 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. 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.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. |
| Author | Colling, Richard Craig, Clare Karling, Johanna Sackville, Tony Oien, Karin Snead, David Bachtiar, Velicia Rajpoot, Nasir da Silva, Maria Freitas Mozolowski, Guy Verrill, Clare Carragher, Fiona Gosling, Daniel Wing, Charlotte O'Connor, Daniel Wright, Corrina Collins, Graeme Lawler, Darragh Sumner, Alan Jacobs, Jaco Kajland‐Wilén, Lena Miller, Keith Macklin, Philip Bull, Joshua Lee, Stephen Bryant, Alyson Pitman, Helen Rahbek, Mikkel White, Kieron Nicholson, Richard Bury, Jonathan Vossen, Dirk Booth, Richard |
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| Contributor | Colling, Richard Craig, Clare Karling, Johanna Bachtiar, Velicia Rajpoot, Nasir Kajland-Wilén, Lena da Silva, Maria Freitas Mozolowski, Guy Carragher, Fiona Gosling, Daniel Wing, Charlotte O'Connor, Daniel Wright, Corrina Collins, Graeme Lawler, Darragh Sumner, Alan Jacobs, Jaco Miller, Keith Macklin, Philip Bull, Joshua Lee, Stephen Bryant, Alyson Rahbek, Mikkel White, Kieron Nicholson, Richard Bury, Jonathan Vossen, Dirk Booth, Richard |
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| Copyright | 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2019 Pathological Society of Great Britain and Ireland |
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| Keywords | digital image artificial pathology analysis evidence-based intelligence |
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| PublicationTitle | The Journal of pathology |
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| SubjectTerms | 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 |
| Title | Artificial intelligence in digital pathology: a roadmap to routine use in clinical practice |
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