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Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association
In this white paper, experts from the Digital Pathology Association (DPA) define terminology and concepts in the emerging field of computational pathology, with a focus on its application to histology images analyzed together with their associated patient data to extract information. This review off...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Ltd
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6852275/ https://www.ncbi.nlm.nih.gov/pubmed/31355445 http://dx.doi.org/10.1002/path.5331 |
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author | Abels, Esther Pantanowitz, Liron Aeffner, Famke Zarella, Mark D van der Laak, Jeroen Bui, Marilyn M Vemuri, Venkata NP Parwani, Anil V Gibbs, Jeff Agosto‐Arroyo, Emmanuel Beck, Andrew H Kozlowski, Cleopatra |
author_facet | Abels, Esther Pantanowitz, Liron Aeffner, Famke Zarella, Mark D van der Laak, Jeroen Bui, Marilyn M Vemuri, Venkata NP Parwani, Anil V Gibbs, Jeff Agosto‐Arroyo, Emmanuel Beck, Andrew H Kozlowski, Cleopatra |
author_sort | Abels, Esther |
collection | PubMed |
description | In this white paper, experts from the Digital Pathology Association (DPA) define terminology and concepts in the emerging field of computational pathology, with a focus on its application to histology images analyzed together with their associated patient data to extract information. This review offers a historical perspective and describes the potential clinical benefits from research and applications in this field, as well as significant obstacles to adoption. Best practices for implementing computational pathology workflows are presented. These include infrastructure considerations, acquisition of training data, quality assessments, as well as regulatory, ethical, and cyber‐security concerns. Recommendations are provided for regulators, vendors, and computational pathology practitioners in order to facilitate progress in the field. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland. |
format | Online Article Text |
id | pubmed-6852275 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley & Sons, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-68522752019-11-22 Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association Abels, Esther Pantanowitz, Liron Aeffner, Famke Zarella, Mark D van der Laak, Jeroen Bui, Marilyn M Vemuri, Venkata NP Parwani, Anil V Gibbs, Jeff Agosto‐Arroyo, Emmanuel Beck, Andrew H Kozlowski, Cleopatra J Pathol Review In this white paper, experts from the Digital Pathology Association (DPA) define terminology and concepts in the emerging field of computational pathology, with a focus on its application to histology images analyzed together with their associated patient data to extract information. This review offers a historical perspective and describes the potential clinical benefits from research and applications in this field, as well as significant obstacles to adoption. Best practices for implementing computational pathology workflows are presented. These include infrastructure considerations, acquisition of training data, quality assessments, as well as regulatory, ethical, and cyber‐security concerns. Recommendations are provided for regulators, vendors, and computational pathology practitioners in order to facilitate progress in the field. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland. John Wiley & Sons, Ltd 2019-09-03 2019-11 /pmc/articles/PMC6852275/ /pubmed/31355445 http://dx.doi.org/10.1002/path.5331 Text en © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Abels, Esther Pantanowitz, Liron Aeffner, Famke Zarella, Mark D van der Laak, Jeroen Bui, Marilyn M Vemuri, Venkata NP Parwani, Anil V Gibbs, Jeff Agosto‐Arroyo, Emmanuel Beck, Andrew H Kozlowski, Cleopatra Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association |
title | Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association |
title_full | Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association |
title_fullStr | Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association |
title_full_unstemmed | Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association |
title_short | Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association |
title_sort | computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the digital pathology association |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6852275/ https://www.ncbi.nlm.nih.gov/pubmed/31355445 http://dx.doi.org/10.1002/path.5331 |
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