Machine learning in predicting antimicrobial resistance: a systematic review and meta-analysis

  02 November 2022

Antimicrobial resistance (AMR) is a global health threat, rapid and timely identification of AMR improves patient prognosis and reduces inappropriate antibiotic use. We systematically searched relevant literature in PubMed, Web of Science, Embase and Institute of Electrical and Electronics Engineers prior to Sep 28, 2021. The study that deployed machine learning or risk score as tool to predict AMR was included in the final review. 

ML might be a potential technology for AMR prediction. However, retrospective methodology for model development, nonstandard data processing and scarcity of validation in a randomized controlled trial or real-world study limit the application of these models in clinical practice.

Author(s): Rui Tang et al
Smart Innovations  


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Antimicrobial Resistance Fighter Coalition

Bangalore Bioinnovation Centre


JSS University


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