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-Reference-Cited by-同舟云学术

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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

Published:2024-12 Issue: Volume:15 Page:100348
ISSN:2153-3539
Container-title:Journal of Pathology Informatics
language:en
Short-container-title:Journal of Pathology Informatics

Author:

Gonzalez Ricardo,Nejat Peyman,Saha Ashirbani,Campbell Clinton J.V.,Norgan Andrew P.,Lokker Cynthia

Publisher

Elsevier BV

Subject

Computer Science Applications,Health Informatics,Pathology and Forensic Medicine

Reference89 articles.

1. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries;Sung;CA Cancer J Clin.,2021

2. A generalized deep learning framework for whole-slide image segmentation and analysis;Khened;Sci Rep.,2021

3. The changing role of pathology in breast cancer diagnosis and treatment;Leong;Pathobiol J Immunopathol Mol Cell Biol.,2011

4. Introduction to digital pathology and computer-aided pathology;Nam;J Pathol Transl Med.,2020

5. Barriers and facilitators to the introduction of digital pathology for diagnostic work;Randell;Stud Health Technol Inform.,2015

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1. The Impact of Artificial Intelligence and Machine Learning in Medical Imaging;Advances in Medical Technologies and Clinical Practice;2024-04-15

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