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@article{200481,
        author = {Payal and Nisha and Niharika Rai and Devendra Sharma},
        title = {AI-Based Intelligent Medical Diagnosis Assistance System Using Voice Processing and Gemini API},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {4403-4409},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200481},
        abstract = {The integration of Artificial Intelligence in healthcare has significantly improved diagnostic processes and patient interaction systems. This paper presents an AIbased intelligent medical diagnosis assistance system that utilizes voice input, natural language processing, and machine intelligence to assist users in identifying possible medical conditions. The system converts speech into text, summarizes patient symptoms, predicts diagnoses, and recommends medicines. The Google Gemini API is used for AI processing, while Selenium-based web scraping is used to build a medicine dataset. The system aims to provide an accessible, efficient, and semi-automated
healthcare support solution.
By integrating natural language understanding and machine learning capabilities, the system ensures accurate interpretation of user inputs while enhancing accessibility for individuals with limited technical or
medical knowledge. The proposed solution aims to reduce diagnostic delays, improve early detection of diseases, and support healthcare professionals by offering data-
driven insights. Additionally, it promotes inclusivity by enabling hands-free interaction, making healthcare guidance more accessible in remote and underserved areas.
This intelligent framework demonstrates the potential of combining voice technology with advanced AI models to create scalable, efficient, and patient-centric healthcare solutions.},
        keywords = {},
        month = {May},
        }