Histopathological whole slide image dataset for classification of treatment effectiveness to ovarian cancer

Ching-Wei Wang; Cheng-Chang Chang; Muhammad Adil Khalil; Yi-Jia Lin; Yi-An Liou; Po-Chao Hsu; Yu-Ching Lee; Chih-Hung Wang; Tai-Kuang Chao

doi:10.1038/s41597-022-01127-6

Scientific Data (Jan 2022)

Histopathological whole slide image dataset for classification of treatment effectiveness to ovarian cancer

Ching-Wei Wang,
Cheng-Chang Chang,
Muhammad Adil Khalil,
Yi-Jia Lin,
Yi-An Liou,
Po-Chao Hsu,
Yu-Ching Lee,
Chih-Hung Wang,
Tai-Kuang Chao

Affiliations

Ching-Wei Wang: Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology
Cheng-Chang Chang: Department of Gynecology and Obstetrics, Tri-Service General Hospital
Muhammad Adil Khalil: Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology
Yi-Jia Lin: Department of Pathology, Tri-Service General Hospital
Yi-An Liou: Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology
Po-Chao Hsu: Department of Gynecology and Obstetrics, Tri-Service General Hospital
Yu-Ching Lee: Graduate Institute of Applied Science and Technology, National Taiwan University of Science and Technology
Chih-Hung Wang: Department of Otolaryngology-Head and Neck Surgery, Tri-Service General Hospital, National Defense Medical Center
Tai-Kuang Chao: Department of Pathology, Tri-Service General Hospital

DOI: https://doi.org/10.1038/s41597-022-01127-6
Journal volume & issue: Vol. 9, no. 1
pp. 1 – 5

Abstract

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Measurement(s) Therapeutic Effect Technology Type(s) Artificial Intelligence Factor Type(s) whole slide image Sample Characteristic - Environment pathologic primary tumor stage for ovary according to AJCC 7th edition

Published in Scientific Data

ISSN: 2052-4463 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/sdata/

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