UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 11 Issue 4
April-2024
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2404G13


Registration ID:
538867

Page Number

p102-p107

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Title

HealthCare Chatbot For Symptom Analysis

Abstract

A person's life is greatly impacted by medical services. In any event, consulting an expert for every medical issue is a very difficult task. We intend to create an AI-powered healthcare chatbot system that can recognise an illness and deliver basic information about it before a patient speaks with a doctor. Innovative approaches to resolving issues in conventional healthcare systems have emerged from the nexus of artificial intelligence and healthcare. Using natural language dialogue, the chatbot converses with users to learn about their symptoms, medical histories, and other relevant details before providing some first analysis and suggestions.The abstract explores the fundamental software and hardware requirements needed for peak performance. Using natural language dialogue, the chatbot converses with users to learn about their symptoms, medical histories, and other relevant details before providing some first analysis and suggestions. The technology offers text-text support for easy-to-use communication with the bot. Based on the user's symptoms, the chatbot also suggests treatments that may be able to cure the illness. Chatbot categorises the ailment as either a serious or insignificant health issue based on the symptoms. In the event of a serious health issue, the user will be referred to a physician for optimal care; in the event of a minor illness, medical help will be provided. For health issues, the chatbot can even prescribe medication for you. In addition to prescription drugs, the Chatbot can provide you Homoeopathic and Ayurvedic remedies for associated health issues. The chatbot keeps all its information in a database, which it uses to determine which keywords to use and whether to respond to users.

Key Words

Healthcare chatbot, Symptom analysis, Machine learning, Decision Tree, Support Vector Machine, Artificial intelligence.

Cite This Article

"HealthCare Chatbot For Symptom Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.p102-p107, April-2024, Available :http://www.jetir.org/papers/JETIR2404G13.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"HealthCare Chatbot For Symptom Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppp102-p107, April-2024, Available at : http://www.jetir.org/papers/JETIR2404G13.pdf

Publication Details

Published Paper ID: JETIR2404G13
Registration ID: 538867
Published In: Volume 11 | Issue 4 | Year April-2024
DOI (Digital Object Identifier):
Page No: p102-p107
Country: Mohali, Punjab, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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