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Article

Targeting tumor heterogeneity: multiplex-detection-based multiple instance learning for whole slide image classification.

Bioinformatics (Oxford, England) - 1 Mar 2023

Wang Zhikang, Bi Yue, Pan Tong, Wang Xiaoyu, Bain Chris, Bassed Richard, Imoto Seiya, Yao Jianhua, Daly Roger J, Song Jiangning

Abstract excerpt

MOTIVATION: Multiple instance learning (MIL) is a powerful technique to classify whole slide images (WSIs) for diagnostic pathology. The key challenge of MIL on WSI classification is to discover the critical instances that trigger the bag label. However, tumor heterogeneity significantly hinders the algorithm's performance. RESULTS: Here, we propose a novel multiplex-detection-based multiple instance learning...

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PMID: 36864612
DOI: 10.1093/bioinformatics/btad114
PMCID: PMC10023223

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