Development and validation of a hierarchical machine learning method using MALDI-TOF mass spectrometry for rapid SCCmec typing and PVL detection in MRSA: a multi-centre study.
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| Title: | Development and validation of a hierarchical machine learning method using MALDI-TOF mass spectrometry for rapid SCCmec typing and PVL detection in MRSA: a multi-centre study. |
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| Authors: | Lin TH; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC., Jian MJ; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC., Mitsumoto-Kaseida F; Department of Laboratory Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan., Kaku N; Department of Laboratory Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan., Chung HY; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC.; Graduate Institute of Medical Science, National Defense Medical Center, Taipei, Taiwan, ROC., Chang CK; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC., Perng CL; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC., Wang YC; Division of Infectious Diseases and Tropical Medicine, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC., Wang CC; Department of Pediatrics, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC., Chen YH; Department of Neurological Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC., Yanagihara K; Department of Laboratory Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan., Shang HS; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC. |
| Source: | Emerging microbes & infections [Emerg Microbes Infect] 2025 Dec; Vol. 14 (1), pp. 2525264. Date of Electronic Publication: 2025 Jul 17. |
| Publication Type: | Journal Article; Multicenter Study; Validation Study |
| Journal Info: | Publisher: Taylor & Francis Country of Publication: United States NLM ID: 101594885 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2222-1751 (Electronic) Linking ISSN: 22221751 NLM ISO Abbreviation: Emerg Microbes Infect Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2222-1751 |
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| DOI: | 10.1080/22221751.2025.2525264 |
