Artificial driven  Personalized Nutrition Guidance for Optimizing Individual Health

Author(s)	Nihal K
Country	India
Abstract	Antibiotic resistance (AMR) poses a severe global health threat, undermining the efficacy of existing treatments and demanding innovative solutions. Artificial Intelligence (AI) offers transformative potential in managing AMR by accelerating drug discovery, enhancing diagnostics, optimizing treatment, and improving surveillance. This review explores how AI technologies—including machine learning, deep learning, and natural language processing—are revolutionizing resistance detection, prediction of antimicrobial susceptibility, and identification of resistance genes from genomic data. AI-driven platforms also enable rapid screening of compounds for antibiotic properties and support drug repurposing strategies. In clinical practice, AI facilitates personalized medicine by integrating patient data to guide targeted therapy. Despite these advances, ethical and regulatory challenges persist, including data privacy, algorithmic bias, and implementation hurdles. Addressing these issues through collaborative, multidisciplinary efforts is essential. This review underscores AI's critical role in reshaping infectious disease management and highlights its promise in mitigating the growing burden of AMR through precision-driven healthcare innovations.
Field	Medical / Pharmacy
Published In	Volume 7, Issue 2, March-April 2025
Published On	2025-04-14
DOI	https://doi.org/10.36948/ijfmr.2025.v07i02.41438
Short DOI	https://doi.org/g9fm3f

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International Journal For Multidisciplinary Research