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.
Saved in:
| 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 |
Be the first to leave a comment!
