A deep learning system for bacterial identification and resistance prediction from MALDI-TOF data.

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Title: A deep learning system for bacterial identification and resistance prediction from MALDI-TOF data.
Authors: Wang CH; Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan.; Department of Emergency Medicine, National Taiwan University Hospital Yunlin Branch, Douliu, Taiwan.; Department of Emergency Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan., Tsao SY; Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan., Hsieh YC; Department of Laboratory Medicine, National Taiwan University Hospital Yunlin Branch, Douliou, Taiwan., Liao PC; Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan., Pan YC; College of Medicine, National Taiwan University, Taipei, Taiwan., Ma MH; Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan.; Department of Emergency Medicine, National Taiwan University Hospital Yunlin Branch, Douliu, Taiwan.; Department of Emergency Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan., Sheng WH; School of Medicine, National Taiwan University College of Medicine, Taipei, Taiwan.; Department of Internal Medicine, National Taiwan University Hospital, Hsin-Chu Branch, Hsinchu, Taiwan., Chen LY; National Health Insurance Administration, Ministry and Health and Welfare, Taipei, Taiwan.; Graduate Institute of Clinical Medicine, National Chung Hsing University, Taichung, Taiwan., Lee CC; Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan. hit3transparency@gmail.com.; Department of Emergency Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan. hit3transparency@gmail.com.; Department of Information Management, Ministry of Health and Welfare, Taipei, Taiwan. hit3transparency@gmail.com.
Source: NPJ digital medicine [NPJ Digit Med] 2026 Jun 08. Date of Electronic Publication: 2026 Jun 08.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101731738 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2398-6352 (Electronic) Linking ISSN: 23986352 NLM ISO Abbreviation: NPJ Digit Med
Database: MEDLINE Ultimate
Description
ISSN:2398-6352
DOI:10.1038/s41746-026-02879-w