Interpretable multi-scale deep learning to detect malignancy in cell blocks and cytological smears of pleural effusion and identify aggressive endometrial cancer.

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Bibliographic Details
Title: Interpretable multi-scale deep learning to detect malignancy in cell blocks and cytological smears of pleural effusion and identify aggressive endometrial cancer.
Authors: Wang CW; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, 10607, Taiwan. Electronic address: cweiwang@mail.ntust.edu.tw., Muzakky H; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, 10607, Taiwan., Chung YP; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, 10607, Taiwan., Lai PJ; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, 10607, Taiwan., Chao TK; Department of Pathology, Tri-Service General Hospital, Taipei, 114202, Taiwan; Institute of Pathology and Parasitology, National Defense Medical University, Taipei, 11490, Taiwan. Electronic address: chaotai.kuang@msa.hinet.net.
Source: Medical image analysis [Med Image Anal] 2025 Dec; Vol. 106, pp. 103742. Date of Electronic Publication: 2025 Aug 05.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 9713490 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1361-8423 (Electronic) Linking ISSN: 13618415 NLM ISO Abbreviation: Med Image Anal Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1361-8423
DOI:10.1016/j.media.2025.103742