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@article{178238,
        author = {Sujit Layek and Upasana Chattopadhyay and Snehal Bhowmick and Ranjana Ray and Madhura Chakraborty},
        title = {Swasthya Bandhu: A Web-Based Dual-Function Health Assistant Integrating Conversational AI and Disease Prediction},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {3195-3201},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178238},
        abstract = {Artificial intelligence's use into healthcare in recent years has created new opportunities for easily accessible and individualized medical support. A conversational chatbot for general health-related inquiries and a machine learning-based disease prediction tool are the two main features of the web-based health assistant system Swasthya Bandhu, which is intended to give users immediate health help. Through a straightforward interface, users can enter symptoms, and the disease prediction engine uses a trained classification algorithm to analyze symptom patterns and recommend potential illnesses. The chatbot improves user interaction and accessibility by conversing with users in natural language while providing basic guidance and health recommendations. Constructed with scikit-learn, Python (Flask), and common web technologies, the system guarantees real-time prediction, responsiveness, and ease of use. This initiative intends to function as an awareness-raising and initial diagnosis tool, particularly helpful in underserved or distant areas where it might not be possible to obtain a medical consultation right away. The outcomes show the system's potential as a helpful tool in digital healthcare ecosystems by showcasing its capacity to produce predictions that are reasonably accurate and to encourage interesting user participation.},
        keywords = {Artificial Intelligence, Health Chatbot, Disease Prediction, Machine Learning, Web-Based Application, Symptom Analysis, Healthcare Assistant, Flask Framework, scikit-learn, Digital Health.},
        month = {May},
        }