Published July 30, 2024 | Version CC-BY-NC-ND 4.0
Journal article Open

Medibuddy- A Healthcare Chatbot using AI

Creators

  • 1. Department of AIML, Dayananda Sagar Academyof Technology and Management, Bangalore (Karnataka), India.

Contributors

Contact person:

  • 1. Department of AIML, Dayananda Sagar Academyof Technology and Management, Bangalore (Karnataka), India.
  • 2. Department of AIML, Dayananda Sagar Academy of Technology and Management, Bangalore (Karnataka), India.

Description

Abstract: This paper presents the development of a Flask-based web application designed to predict diseases based on user-reported symptoms and provide relevant health information. Leveraging machine learning techniques, the system utilizes a dataset of diseases and their associated symptoms to generate predictions through cosine similarity and a pre-trained Random Forest model. The application features a user- friendly interface for registration, login, and symptom reporting. Additionally, it integrates the DuckDuckGo search API to fetch detailed information about predicted diseases, enhancing the user experience with comprehensive health insights. The application also includes an interactive chatbot to guide users through the symptom input process, ensuring accurate data collection for reliable disease prediction. The system is built with Python, utilizing libraries such as pandas, numpy, and scikit-learn for data processing and model deployment, and is powered by SQLAlchemy for database management. This work aims to provide an accessible tool for preliminary health assessment, potentially aiding in early diagnosis and prompt medical.

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Additional details

Identifiers

DOI
10.35940/ijsce.G9902.14030724
EISSN
2231-2307

Dates

Accepted
2024-07-15
Manuscript received on 23 May 2024 | Revised Manuscript received on 29 June 2024 | Manuscript Accepted on 15 July 2024 | Manuscript published on 30 July 2024.

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