UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Volume 11 | Issue 5 | May 2024

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Published in:

Volume 11 Issue 5
May-2024
eISSN: 2349-5162

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

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Published Paper ID:
JETIR2405796


Registration ID:
540533

Page Number

h762-h768

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Title

Disease Prediction Based On Symptoms

Abstract

Amidst the growing demand for efficient healthcare solutions and the challenge of limited doctor accessibility, there's been a surge in the development of disease prediction systems. These systems utilize Machine Learning to analyze user-entered symptoms, providing trustworthy findings swiftly. Even when there's no immediate danger, users seeking insight into their ailments benefit from this technology. The diversity of diseases and the low doctor-patient ratio have further fueled the adoption of such prediction technologies. Our focus is on delivering instant and accurate disease prognosis, considering both the symptoms entered and the projected severity of the condition. Our system not only offers the best algorithms but also more information that the person is suffering from. Various machine learning techniques are employed to ensure both speed and reliability in predicting illnesses..

Key Words

Machine Learning, Disease Prediction

Cite This Article

"Disease Prediction Based On Symptoms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.h762-h768, May-2024, Available :http://www.jetir.org/papers/JETIR2405796.pdf

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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

"Disease Prediction Based On Symptoms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. pph762-h768, May-2024, Available at : http://www.jetir.org/papers/JETIR2405796.pdf

Publication Details

Published Paper ID: JETIR2405796
Registration ID: 540533
Published In: Volume 11 | Issue 5 | Year May-2024
DOI (Digital Object Identifier):
Page No: h762-h768
Country: Bengaluru North, Karnataka, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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