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@article{180599,
        author = {Sandhya P and Anirudh Joshi K and Hanumanthachar Joshi},
        title = {Machine Learning in Pharmacy and Health Care: Revolutionizing Patient Outcomes},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {2719-2722},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180599},
        abstract = {Machine learning (ML), a subfield of artificial intelligence (AI), is transforming the landscape of pharmacy and health care. By leveraging large datasets and sophisticated algorithms, ML enables improved decision-making, enhances patient outcomes, accelerates drug discovery, and optimizes operational efficiency. From drug discovery to personalized medicine and clinical decision support, ML offers enhanced data-driven capabilities. In other words, the learning model learns based on samples, whereas explicit programming follows rules or a limited hypothesis. ML improves efficiency and reliability and reduces costs in computational processes. Moreover, it can accurately and rapidly generate models through data analysis. Machine learning presents tools that can process a large amount of data, the volume of which is far beyond human understanding. This review explores the current applications of ML in pharmacy and healthcare highlighting its potential, challenges, and future directions.},
        keywords = {Machine Learning, Pharmaceuticals, Artificial Intelligence, Healthcare},
        month = {June},
        }