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E2EFP-MIL: End-to-end and high-generalizability weakly supervised deep convolutional network for lung cancer classification from whole slide image

Lei Cao, Jie Wang, Yuanyuan Zhang, Zhiwei Rong, Meng Wang, Liuying Wang, Jianxin Ji, Youhui Qian, Liuchao Zhang, Hao Wu, Jiali Song, Zheng Liu, Wenjie Wang, Shuang Li, Peiyu Wang, Zhenyi Xu, Jingyuan Zhang, Liang Zhao, Hang Wang, Mengting Sun, Xing Huang, Rong Yin, Yuhong Lü, Ziqian Liu, Kui Deng, Gongwei Wang, Mantang Qiu, Kang Li, Jun Wang, Yan Hou

2023Medical Image Analysis37 citationsDOI

Topics & Concepts

Generalizability theoryDiscriminative modelArtificial intelligencePyramid (geometry)Computer scienceEnd-to-end principleDeep learningFeature (linguistics)Pattern recognition (psychology)Convolutional neural networkMachine learningMathematicsStatisticsLinguisticsGeometryPhilosophyAI in cancer detectionRadiomics and Machine Learning in Medical ImagingColorectal Cancer Screening and Detection
E2EFP-MIL: End-to-end and high-generalizability weakly supervised deep convolutional network for lung cancer classification from whole slide image | Litcius