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.

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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
Controls
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article

Application of Artificial Intelligence in Clinical Microbiology: From Research to Practice

Yi‐Wei Tang, Ting Ding, Xiaoke Hao
2 citations
iLABMED
Bacterial Identification and Susceptibility Testing
2.64
article

Application of Artificial Intelligence in Clinical Microbiology: From Research to Practice

Yi‐Wei Tang, Ting Ding, Xiaoke Hao
article en
2 citations

Abstract

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.

iLABMEDVol. 3(4)
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)
Openalex Percentile: Top 9%
Bacterial Identification and Susceptibility Testing
2.64
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