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@article{195120,
        author = {PUDI BHEEMESWARA RAO and KONTYANA SAI SANKAR RAO and PINNINTI MADHURI and PEDDINTI RAJU},
        title = {Drug Recommendation System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {6816-6818},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=195120},
        abstract = {The rapid advancement of healthcare technologies has created a demand for intelligent systems that assist us-ers in selecting appropriate medicines. This project pro-poses a Drug Recommendation System that suggests alternative medicines based on a given drug using ma-chine learning techniques. The system utilizes TF-IDF vectorization and cosine similarity to analyze drug data and identify similar medicines. Additionally, the system integrates online pharmacy links, enabling users to di-rectly purchase recommended drugs. The implementa-tion is carried out using Python and Streamlit, provid-ing an interactive and user-friendly interface. The pro-posed system improves accessibility, reduces manual effort, and enhances user convenience. Overall, it demonstrates an efficient and practical approach to intelligent drug recommendation in modern healthcare applications.},
        keywords = {Drug Recommendation, Machine Learning, TF-IDF, Cosine Similarity, Streamlit, Healthcare System},
        month = {March},
        }