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Nationwide longitudinal evaluation of a machine learning approach for enhanced interpretation of Xpert MTB/RIF ultra rifampicin-resistance results in low bacterial load tuberculosis specimens.

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Title: Nationwide longitudinal evaluation of a machine learning approach for enhanced interpretation of Xpert MTB/RIF ultra rifampicin-resistance results in low bacterial load tuberculosis specimens.
Authors: Lin TH; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC., Chung HY; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC; Graduate Institute of Medical Science, National Defense Medical University, Taipei, Taiwan, ROC., Jian MJ; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC., Chang CK; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC., Lai YW; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC., Perng CL; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC., Chang FY; Division of Infectious Diseases and Tropical Medicine, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC., Chen YH; Department of Neurological Surgery, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC., Shang HS; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC. Electronic address: iamkeith@mail.ndmctsgh.edu.tw.
Source: Journal of infection and public health [J Infect Public Health] 2026 Feb; Vol. 19 (2), pp. 103064. Date of Electronic Publication: 2025 Nov 21.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: England NLM ID: 101487384 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1876-035X (Electronic) Linking ISSN: 18760341 NLM ISO Abbreviation: J Infect Public Health Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Nationwide longitudinal evaluation of a machine learning approach for enhanced interpretation of Xpert MTB/RIF ultra rifampicin-resistance results in low bacterial load tuberculosis specimens.
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  Data: <searchLink fieldCode="AU" term="%22Lin+TH%22">Lin TH</searchLink>; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC.<br /><searchLink fieldCode="AU" term="%22Chung+HY%22">Chung HY</searchLink>; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC; Graduate Institute of Medical Science, National Defense Medical University, Taipei, Taiwan, ROC.<br /><searchLink fieldCode="AU" term="%22Jian+MJ%22">Jian MJ</searchLink>; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC.<br /><searchLink fieldCode="AU" term="%22Chang+CK%22">Chang CK</searchLink>; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC.<br /><searchLink fieldCode="AU" term="%22Lai+YW%22">Lai YW</searchLink>; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC.<br /><searchLink fieldCode="AU" term="%22Perng+CL%22">Perng CL</searchLink>; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC.<br /><searchLink fieldCode="AU" term="%22Chang+FY%22">Chang FY</searchLink>; Division of Infectious Diseases and Tropical Medicine, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC.<br /><searchLink fieldCode="AU" term="%22Chen+YH%22">Chen YH</searchLink>; Department of Neurological Surgery, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC.<br /><searchLink fieldCode="AU" term="%22Shang+HS%22">Shang HS</searchLink>; Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC. Electronic address: iamkeith@mail.ndmctsgh.edu.tw.
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  Data: <searchLink fieldCode="JN" term="%22101487384%22">Journal of infection and public health</searchLink> [J Infect Public Health] 2026 Feb; Vol. 19 (2), pp. 103064. <i>Date of Electronic Publication: </i>2025 Nov 21.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier%22">Elsevier </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101487384 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1876-035X (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2218760341%22">18760341 </searchLink><i>NLM ISO Abbreviation: </i>J Infect Public Health <i>Subsets: </i>MEDLINE
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        Value: 10.1016/j.jiph.2025.103064
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      – Code: eng
        Text: English
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      – TitleFull: Nationwide longitudinal evaluation of a machine learning approach for enhanced interpretation of Xpert MTB/RIF ultra rifampicin-resistance results in low bacterial load tuberculosis specimens.
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              Text: 2026 Feb
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