Deep learning for liver cancer histopathology image analysis: A comprehensive survey-Reference-Cited by-同舟云学术

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Deep learning for liver cancer histopathology image analysis: A comprehensive survey

Published:2024-07 Issue: Volume:133 Page:108436
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Jiang Haoyang,Yin Yimin,Zhang Jinghua^ORCID,Deng Wanxia,Li Chen

Funder

China Scholarship Council

Scientific Research Foundation of Hunan Provincial Education Department

Education Department of Hunan Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference123 articles.

1. LiverNet: efficient and robust deep learning model for automatic diagnosis of sub-types of liver hepatocellular carcinoma cancer from H&E stained liver histopathology images;Aatresh;Int. J. Comput. Assist. Radiol. Surg.,2021

2. Representation learning-based unsupervised domain adaptation for classification of breast cancer histopathology images;Alirezazadeh;Biocybern. Biomed. Eng.,2018

3. Adversarial stain transfer for histopathology image analysis;BenTaieb;IEEE Trans. Med. Imaging,2017

4. The c-index is not proper for the evaluation of-year predicted risks;Blanche;Biostatistics,2019

5. Deep learning-based phenotyping reclassifies combined hepatocellular-cholangiocarcinoma;Calderaro;Nat. Commun.,2023

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