International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.

AI-Based Medical Chatbot for Disease Prediction

Author(s) Ashish Zagade, Vedant Killedar, Onkar Mane, Ganesh Nitalikar, Smita Bhosale
Country India
Abstract This research paper presents the development and implementation of an AI-based medical Chatbots leverage machine learning and artificial intelligence technology, use natural language processing (NLP) to understand user queries and provide accurate information, guidance and assistance for various purposes. Motivated by the global pandemic and the need for practical medical assistance, this article provides an overview of the chatbot's purpose, algorithm design, dataset description and implementation. The algorithm involves taking user input, extracting symptoms, classifying diseases, and recommending prevention. This file was created in JSON format to facilitate training and knowledge of the model. The chatbot interface is accessible through the platform and provides information about symptoms, preventive measures, hospitalization and medication options. Overall, the study highlights the potential of AI-based chatbots to revolutionize access to healthcare and self-diagnosis, thereby bridging the gap between users and treatment.
Keywords Organ Donation, Blockchain Technology, Decentralization, Transparency, Smart Contracts, Healthcare Innovation.
Field Engineering
Published In Volume 6, Issue 3, May-June 2024
Published On 2024-06-02
Cite This AI-Based Medical Chatbot for Disease Prediction - Ashish Zagade, Vedant Killedar, Onkar Mane, Ganesh Nitalikar, Smita Bhosale - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.21865
DOI https://doi.org/10.36948/ijfmr.2024.v06i03.21865
Short DOI https://doi.org/gtxrpm

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