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@article{195577,
        author = {Devyani Patil and Ainul Shafeeque and Siddhi Pashte},
        title = {The effectiveness of herbal medicines using Artificial Intelligence in Pharmacovigilance},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {882-891},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=195577},
        abstract = {Herbal Medicines perceived safety, accessibility, and cultural acceptance have led to a significant surge in its use worldwide.  Accurately determining their efficacy and safety is still severely hampered by a lack of clinical data, in consistent quality, and under reporting of adverse events.  The large and diverse amounts of data produced by herbal goods, such as unplanned reports, books, social media, and electronic medical records, are frequently too much for traditional Pharmacovigilance (PV) systems to handle. Artificial Intelligence (AI) supported PV may effectively detect adverse event signals, identify patterns, and enhance causality evaluation for herbal products with sophisticated algorithms including Natural Language Processing (NLP), Machine Learning (ML), and deep learning.  This method facilitates the creation of evidence about therapeutic effects while simultaneously improving the precision and promptness of safety monitoring.  An innovative approach to assessing the practical efficacy of Herbal Medicines (HM), enhancing patient safety, and fortifying international health monitoring systems is the integration of AI into PV systems.  In order to guarantee the ethical, fair, and dependable application of AI technologies in HM monitoring, future advancements should concentrate on creating extensive herbal databases, enhancing algorithm transparency, and encouraging global co-operation.},
        keywords = {},
        month = {April},
        }