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@article{182566,
        author = {Magimai Rufus A.J and Deepa S and Deepa C.Philip and Bharathi B},
        title = {Artificial Intelligence in Microbiology: Transforming Diagnostics, Antimicrobial Resistance and Public Health: A Review},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {2},
        pages = {2556-2560},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=182566},
        abstract = {The new technologies based on AI are changing microbiology for the better by improving diagnostics, fighting against antimicrobial resistance (AMR), and even improving public health surveillance. The use of machine learning algorithms along with predictive modeling tools and neural networks has made it easier to identify different microorganisms and patterns in genomic data as well as predict future outbreaks. This review aims to analyze the application of AI in modern microbiological diagnostics, AI-powered research in smart antibiotics, and epidemiological interventions while also considering subsequent trends and outcome.},
        keywords = {Artificial intelligence, machine learning, antimicrobial resistance, predictive modeling, neural networks, genomic data analysis, smart antibiotics, public health surveillance, AI-powered research, healthcare},
        month = {July},
        }