The role of artificial intelligence and machine learning in predicting and combating antimicrobial resistance
Jiangxi Provincial Cancer Hospital · Shantou University · +6 more institutions
Abstract
Antimicrobial resistance (AMR) is a major threat to global public health. The current review synthesizes to address the possible role of Artificial Intelligence and Machine Learning (AI/ML) in mitigating AMR. Supervised learning, unsupervised learning, deep learning, reinforcement learning, and natural language processing are some of the main tools used in this domain. AI/ML models can use various data sources, such as clinical information, genomic sequences, microbiome insights, and epidemiological data for predicting AMR outbreaks. Although AI/ML are relatively new fields, numerous case studies offer substantial evidence of their successful application in predicting AMR outbreaks with greater accuracy. These…
Citation impact
- FWCI
- 61.85
- Percentile
- 100%
- References
- 190
Authors
10- HBHazrat BilalCorresponding
Jiangxi Provincial Cancer Hospital
- MNMuhammad Nadeem Khan
Shantou University, Shantou University Medical College
- SKSabir Khan
Shantou University, Second Affiliated Hospital of Shantou University Medical College
- MSMuhammad Shafiq
Shantou University, Shantou University Medical College
- WFWenjie Fang
Second Military Medical University
Topics & keywords
- Antimicrobial
- Artificial intelligence
- Machine learning
- Antibiotic resistance
- Computer science
- Biochemical engineering
- Biology
- Engineering