Pioneering Klebsiella Pneumoniae Antibiotic Resistance Prediction With Artificial Intelligence-Clinical Decision Support System–Enhanced Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry: Retrospective Study
This investigation highlights the synergy between MALDI-TOF MS and ML as a beacon of hope against the escalating threat of antibiotic resistance. The advent of AI-CDSS heralds a new era in clinical diagnostics, promising a future in which rapid and accurate resistance prediction becomes a cornerstone in combating infectious diseases. Through this innovative approach, we answered the challenge posed by KP and other multidrug-resistant pathogens, marking a significant milestone in our journey toward global health security.
Authors
- Hung‐Sheng Shang (ORCID: https://orcid.org/0000-0002-4831-1866)
- Cherng‐Lih Perng (ORCID: https://orcid.org/0000-0001-7182-1031)
- Ming‐Jr Jian (ORCID: https://orcid.org/0000-0002-4902-4447)
- Hsing‐Yi Chung (ORCID: https://orcid.org/0000-0002-7870-8354)
- Tai‐Han Lin (ORCID: https://orcid.org/0000-0002-6100-3120)
- Chih-Kai Chang
- Feng‐Yee Chang (ORCID: https://orcid.org/0000-0001-8941-1129)
Institutions
- Tri-Service General Hospital (TW)
- National Defense Medical Center (TW)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2024-11-07
- DOI
- https://doi.org/10.2196/58039
- Citations
- 12
- Primary Topic
- Bacterial Identification and Susceptibility Testing
- Type
- article
- Field-Weighted Citation Impact
- 4.57