Integrating Artificial Intelligence into Microbiology: Emerging Horizons for Precision Medicine and Antimicrobial Stewardship
DOI:
https://doi.org/10.70411/MJHAS.3.1.2026291Keywords:
Artificial Intelligence, Microbiology, Microbial Genomics, Antimicrobial Resistance, AI-powered DiagnosticsAbstract
The latest developments in artificial intelligence (AI) have altered the sphere of microbiological investigation very rapidly by expanding the scope of studying microbial systems, accurate diagnostics on the basis of genomes, and the discovery of new drugs. This review introduces a specific synopsis of AI use in microbiology that covers three areas, namely early detection of diseases, surveillance of antimicrobial resistance (AMR), and progress in therapeutics. AI is used to enhance the process of pathogen identification and bring about the formulation of specific therapies through the use of machine learning models and vast microbial data sets that will eventually lead to quorum-sensing inhibitors and microbiome-based treatment of diseases. Other than these developments, there is still a challenge with data quality, algorithm transparency, and ethical implementation. To overcome these problems, the cooperation of microbiologists with computational scientists and policymakers is needed. In the present paper, the authors offer a comprehensive framework on which future studies could base their findings, focusing on the role of AI in sustainable healthcare and agricultural solutions, as well as environmental support.
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