Application of Artificial Intelligence in Clinical Microbiology: From Research to Practice
ABSTRACT With the continuous development of technologies such as big data, the internet, and deep learning, artificial intelligence (AI) has become widely used in many fields of laboratory medicine, including clinical microbiology, where it has shown great potential in clinical practice. AI significantly improves the efficiency of microbial identification and diagnosis, and also assists in antibiotic resistance monitoring, treatment guidance, and antibiotic development. By automating daily tasks and optimizing laboratory workflows, AI can improve overall laboratory management. AI also plays an important role in infection monitoring, along with epidemic prevention and control. AI integration with clinical microbiology is reshaping the field and driving advancements for more accurate, efficient, and predictive healthcare solutions. This article thoroughly discusses AI applications in clinical microbiology and explores its opportunities and challenges, aiming to provide a reference for future AI expansion in this field.
Authors
- Yi‐Wei Tang (ORCID: https://orcid.org/0000-0003-4888-6771)
- Ting Ding (ORCID: https://orcid.org/0000-0003-2000-1775)
- Xiaoke Hao (ORCID: https://orcid.org/0009-0004-9569-4638)
Institutions
- Danaher (United States) (US)
- Northwest University (CN)
- Second Affiliated Hospital of Xi'an Jiaotong University (CN)
- China XD Group (China) (CN)
- Chongqing Public Health Medical Center (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- iLABMED
- Published
- 2025-09-26
- DOI
- https://doi.org/10.1002/ila2.70033
- Citations
- 2
- Primary Topic
- Bacterial Identification and Susceptibility Testing
- Type
- article
- Field-Weighted Citation Impact
- 2.64