Deep learning captures selective features for discrimination of microsatellite instability from pathologic tissue slides of gastric cancer-Reference-Cited by-同舟云学术

Deep learning captures selective features for discrimination of microsatellite instability from pathologic tissue slides of gastric cancer

Published:2022-08-27 Issue:2 Volume:152 Page:298-307
ISSN:0020-7136
Container-title:International Journal of Cancer
language:en
Short-container-title:Intl Journal of Cancer

Author:

Lee Sung Hak¹,Lee Yujin²,Jang Hyun‐Jong³^ORCID

Affiliation:

1. Department of Hospital Pathology Seoul St. Mary's Hospital Seoul South Korea

2. Department of Hospital Pathology St. Vincent's Hospital Suwon South Korea

3. Catholic Big Data Integration Center, Department of Physiology, College of Medicine The Catholic University of Korea Seoul South Korea

Funder

National Research Foundation of Korea

Publisher

Wiley

Subject

Cancer Research,Oncology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ijc.34251

Reference35 articles.

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2. Targeted therapies for gastric cancer: failures and hopes from clinical trials

3. The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more “personalized” approach to cancer staging

4. Microsatellite instability and mismatch repair deficiency in the era of precision immuno-oncology

5. Clinical characteristics and responses to chemotherapy and immune checkpoint inhibitor treatment for microsatellite instability gastric cancer;Yang G;Am J Cancer Res,2020

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