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@article{174180,
        author = {Mrs. T. Kavitha Anbazhagan and Naveenasri G and Ranjani P and Subasri D},
        title = {Mediflora Detector for Homo Sapiens},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {4633-4638},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174180},
        abstract = {An inventive web-based tool called the Mediflora Detector for Homo Sapiens was created to offer comprehensive information about medicinal plants.  The system retrieves information about a plant's potential to treat chronic illnesses, dosage variations depending on personal circumstances, and suggested modes of consumption when a user scans the plant.  In order to increase public awareness of the medicinal applications of plants and support individualized healthcare, this paper examines the idea, architecture, and operation of the Mediflora Detector.  With its extensive medicinal plant database, machine learning, and cutting-edge plant recognition technology, Mediflora looks to be a useful resource for both medical professionals and those looking for natural cure},
        keywords = {The integration of machine learning in herbal medicine enhances medicinal plant identification through AI-powered recognition and deep learning. Image processing and computer vision improve accuracy, while adaptive dosage prediction ensures personalized treatment. Health informatics bridges traditional medicine with AI, making herbal remedies safer and more effective. The digitalization of herbal medicine enables smart systems for precise dosage recommendations. This approach advances human-centered AI in natural healthcare solutions.},
        month = {April},
        }