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@article{206768,
        author = {Raveesh R and Shruthi V S and Rohan Rao G H and Vaishnavi K and Varnna Balakrishnan},
        title = {AI-Powered Symptoms-Based Disease Detection and Medicinal Plant Identification System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {380-385},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206768},
        abstract = {In today's fast-paced world, people often rush to modern healthcare for even minor health issues, leading to rising costs and the slow fading of traditional healing knowledge passed down through generations. This project addresses that growing concern by offering a simple yet intelligent approach to early disease detection and natural treatment guidance.
What we built is a web platform that approaches the problem from two angles. First, it takes the symptoms a user describes, and runs them through machine learning classifiers to suggest possible conditions, along with a few precautions the person can take right away. Second, it also lets people photograph a plant and then get an identification back, but paired with details on how that same plant has been used in medicinal ways. And a chatbot sits on top of both parts, asking follow up questions in plain language so the whole output never feels like you are reading a diagnostic report, not even a little. The goal was never to replace a doctor, it was more like to give people a kind of starting point, you know, something that helps them figure out if a situation really needs professional attention or if it can reasonably be handled at home, at the same time as keeping traditional healing knowledge reachable for anyone who is curious enough to look.},
        keywords = {Disease prediction, medicinal plants, machine learning, deep learning, CNN, health care systems, symptom analysis, chatbot.},
        month = {July},
        }