Predicting cancer outcomes from whole slide images via hybrid supervision learning-Reference-Cited by-同舟云学术

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Predicting cancer outcomes from whole slide images via hybrid supervision learning

Published:2023-11 Issue: Volume:557 Page:126736
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

He Xianying,Li Jiahui,Yan Fang,Wang Linlin,Chen Wen,Huang Xiaodi,Hu Zhiqiang,Duan Qi,Li Hongsheng,Zhang Shaoting,Zhao Jie

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference81 articles.

1. Deep learning-based classification of kidney transplant pathology: a retrospective, multicentre, proof-of-concept study;Kers;Lancet Digit. Health,2022

2. Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology;Laleh;Med. Image Anal.,2022

3. Spatially aware graph neural networks and cross-level molecular profile prediction in colon cancer histopathology: a retrospective multi-cohort study;Ding;Lancet Digit. Health,2022

4. Artificial intelligence in lung cancer pathology image analysis;Wang;Cancers,2019

5. ResGANet: Residual group attention network for medical image classification and segmentation;Cheng;Med. Image Anal.,2022

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1. Multi-scale multi-instance contrastive learning for whole slide image classification;Engineering Applications of Artificial Intelligence;2024-12

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