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Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association.

Authors :
Abels E
Pantanowitz L
Aeffner F
Zarella MD
van der Laak J
Bui MM
Vemuri VN
Parwani AV
Gibbs J
Agosto-Arroyo E
Beck AH
Kozlowski C
Source :
The Journal of pathology [J Pathol] 2019 Nov; Vol. 249 (3), pp. 286-294. Date of Electronic Publication: 2019 Sep 03.
Publication Year :
2019

Abstract

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.<br /> (© 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.)

Details

Language :
English
ISSN :
1096-9896
Volume :
249
Issue :
3
Database :
MEDLINE
Journal :
The Journal of pathology
Publication Type :
Academic Journal
Accession number :
31355445
Full Text :
https://doi.org/10.1002/path.5331