Soft multiclass feature augmented deep learning to predict tumor origins using cytology or histology whole slide images.

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Bibliographic Details
Title: Soft multiclass feature augmented deep learning to predict tumor origins using cytology or histology whole slide images.
Authors: Wang CW; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC. cweiwang@mail.ntust.edu.tw., Lai PJ; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC., Chu TC; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC., Wu TK; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC., Liang CH; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC., Chao TK; Department of Pathology, Tri-Service General Hospital, Taipei, Taiwan, ROC. chaotai.kuang@msa.hinet.net.; Graduate Institute of Pathology and Parasitology, National Defense Medical University, Taipei, Taiwan, ROC. chaotai.kuang@msa.hinet.net.
Source: NPJ digital medicine [NPJ Digit Med] 2026 Apr 13; Vol. 9 (1). Date of Electronic Publication: 2026 Apr 13.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101731738 Publication Model: Electronic Cited Medium: Internet ISSN: 2398-6352 (Electronic) Linking ISSN: 23986352 NLM ISO Abbreviation: NPJ Digit Med Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2398-6352
DOI:10.1038/s41746-026-02604-7