Performance of externally validated machine learning models based on histopathology images for the diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer: A systematic review

Performance of externally validated machine learning models based on histopathology images for the diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer: A systematic review

Numerous machine learning (ML) models have been developed for breast cancer using various types of data. Successful external validation (EV) of ML models is important evidence of their generalizability. The aim of this systematic review was to assess the performance of externally validated ML models...

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Bibliographic Details
Main Authors: Ricardo Gonzalez, Peyman Nejat, Ashirbani Saha, Clinton J.V. Campbell, Andrew P. Norgan, Cynthia Lokker
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Journal of Pathology Informatics
Subjects:
Breast neoplasms
Pathology
Validation studies
Machine learning
Systematic review
Online Access:http://www.sciencedirect.com/science/article/pii/S2153353923001621

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http://www.sciencedirect.com/science/article/pii/S2153353923001621

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