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

Authors :
Famke Aeffner
Anil V. Parwani
Andrew H. Beck
Jeroen van der Laak
Emmanuel Agosto-Arroyo
Cleopatra Kozlowski
Jeff Gibbs
Esther Abels
Liron Pantanowitz
Marilyn M. Bui
Venkata N. P. Vemuri
Mark D. Zarella
Source :
Journal of Pathology Informatics, 286-294, The Journal of Pathology
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.

Details

ISSN :
21533539
Database :
OpenAIRE
Journal :
Journal of Pathology Informatics, 286-294, The Journal of Pathology
Accession number :
edsair.doi.dedup.....2637d2cbf05021c336db813105f7cedf