Paper Title

Healthcare Chatbot System

Article Identifiers

Registration ID: IJNRD_209449

Published ID: IJNRD2403146

DOI: Click Here to Get

Authors

MD ISTIYAK ALAM ANSARI , Mark Lawrence , Mohd Aman , Dr.Saurabh Kumar

Keywords

Health care chatbot , python , Disease Prediction , Personalized solution , Machine learning , user trust , pandas, sk-learn.

Abstract

This paper presents the development and implementation of an AI-powered healthcare chatbot system designed to offer efficient and personalized medical assistance. Employing Python in PyCharm IDE and Flask framework, the system facilitates user login, symptom input, accurate disease predictions, tailored solutions, and doctor recommendations. Leveraging Pandas, NumPy, Sklearn, and gensim libraries, machine learning algorithms drive disease prediction and solution recommendation functionalities. Evaluation results demonstrate commendable accuracy in disease prediction and relevance in solution provision. Ethical considerations, encompassing data privacy and user trust, are meticulously addressed, marking a significant advancement in enhancing healthcare accessibility and paving the way for future developments in AI-driven healthcare services.

How To Cite (APA)

MD ISTIYAK ALAM ANSARI, Mark Lawrence, Mohd Aman, & Dr.Saurabh Kumar (March-2024). Healthcare Chatbot System. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(3), b403-b407. https://ijnrd.org/papers/IJNRD2403146.pdf

Issue

Volume 9 Issue 3, March-2024

Pages : b403-b407

Other Publication Details

Paper Reg. ID: IJNRD_209449

Published Paper Id: IJNRD2403146

Downloads: 000121995

Research Area: Computer Science & Technology 

Country: Greater Noida/ Gautum Budh Nagar, uttar pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2403146.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403146

About Publisher

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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Call For Paper

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

The INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to advance applied, theoretical, and experimental research across diverse fields. Its goal is to promote global scientific information exchange among researchers, developers, engineers, academicians, and practitioners. IJNRD serves as a platform where educators and professionals can share research evidence, models of best practice, and innovative ideas, contributing to academic growth and industry relevance.

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How to submit the paper?

Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: IJNRD is an International Peer-reviewed, Refereed, and Open Access Journal with Transparent Peer Review as per the new UGC CARE 2025 guidelines, offering low-cost multidisciplinary publication with Crossref DOI and global indexing.

Subject Category: Research Area

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