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@article{163886,
        author = {VENNELA HIMABINDU and TILOTTAMA  SAHUKARI and MADDALA HARSHA  MANI RAM and P.ABHISHEK MANOHAR and S.MOHAMMAD FIROZ and J.S.V.S.Hari Priyanka},
        title = {Medicine Recommendation System},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {11},
        pages = {2198-2203},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=163886},
        abstract = {Technological developments in healthcare have made it possible to provide customised treatment to each patient according to their particular traits. In this project, we suggest a mobile app-based solution that uses test result data to provide patients with personalised medication and health advice. Users of the software have the option to easily scan and upload their test reports for automated analysis, or they can manually enter these numbers. The project's goal is to develop a simple, user-friendly mobile app interface that will enable patients to quickly enter test report results or, in the case of physical reports, scan them using the smartphone's camera and image processing technologies alone. The main function of the application is to interpret the provided test report values by applying sophisticated machine learning and data analysis algorithms. Using a large database of medical knowledge, the system will link these values to produce suggestions for personalised therapy. Patients won't have to wait long to hear about their treatment alternatives thanks to the app's real-time recommendations. For medical circumstances where time is of the essence, this prompt response is extremely important.},
        keywords = {Personalized Medicine, Mobile Application, Test Report Analysis, Machine Learning, Health Data Security},
        month = {},
        }