Crossref DOIMemberCiteFactoropen accessissn
SJIF Impact Factor 8.659 | ISSN: 2582-3930
IJSREM Logo

International Journal of Scientific Research in Engineering and Management

(Gateway to Global Scholars - An International, Scholarly, Multi-Disciplinary, Open Access Journal)

Peer-Reviewed Journal Designed to Meet UGC's Quality Parameters

HomeCurrent IssuePast IssuesPay OnlineConferencesEditorial BoardAbout UsContact Us
IJSREM

Loading article...

Follow Us

  • Google Scholar
  • ResearchGate
  • Academia.edu
  • Mendeley
  • LinkedIn
  • Facebook
  • Instagram

Journal Policies

  • Peer Review Policy
  • Publication Ethics
  • Copyright Infringement
  • Refund & Cancellation Policy
  • Terms and Conditions
  • Privacy Policy

Journal Identifiers & Licenses

  • ISSN Verified: 2582-3930ISSN Verified: 2582-3930
  • Crossref DOI: 10.55041Crossref DOI: 10.55041
  • SJIF Ranking: 08.659SJIF Ranking: 08.659
  • Licensed under CC BY 4.0Licensed under CC BY 4.0
  • ISO Certification: 9001:2015ISO Certification: 9001:2015
  • Indexed & Cited In: Google ScholarIndexed & Cited In: Google Scholar

Contact Us

International Journal of Scientific Research in Engineering and Management (IJSREM)

#62/1, New No 7, 1st Cross, 2nd Main, Ganganagar, R T Nagar, Bangalore North, Bangalore, Karnataka, India – 560032
[email protected]+91 93911 67991
logos
logos
Working Hours

Mon – Sat: 9:00 AM – 6:00 PM

Sunday: 10:00 AM – 4:00 PM

+91 93911 67991

© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

DisclaimerPrivacy PolicyTerms and Conditions
ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM23708

Predicting Heart Disease at Early Stages Using Machine Learning

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM23708

Volume:

7 |

6 |

Jun 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Share this article:

Authors

MAB

Miss. Apeksha Barhate

MRP

Mr. Ravindra Pandit

DUP

Dr. Umesh Pawar

MRD

Mr. Ramesh Daund

Author Services & Downloads

Full Articles

Abstract

Predicting and area of coronary sickness has persistently been an essential and testing task for clinical consideration trained professionals. Clinical facilities and various focuses are offering exorbitant medicines and exercises to treat heart contaminations. Subsequently, expecting coronary disease toward the starting stages will be useful to people all around the planet so they will take major actions already quitting any funny business. Coronary disease is a basic issue in later times; the major legitimization behind this sickness is the confirmation of alcohol, tobacco, and nonappearance of real action. All through the long haul, AI shows reasonable results in basically choosing and assumptions from the wide plan of data made by the prosperity care industry. A part of the controlled AI techniques used in this assumption for coronary disease are fake decision tree (DT), support vector machine (SVM), Naive Bayes (NB) and k closest neighbor estimation. Moreover, the shows of these estimations are summarized..

KEYWORDS

Machine learning supervised learning health care services heart disease.

Cite This Article

Miss. Apeksha Barhate, Mr. Ravindra Pandit, Dr. Umesh Pawar, Mr. Ramesh Daund, "Predicting Heart Disease at Early Stages Using Machine Learning," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 6, Jun 2023. https://doi.org/10.55041/IJSREM23708

Full Article/Conclusion

References

Editorial & Review Transparency

Publication Date

6/17/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

Documents

Review Report (Confidential)
Copyright Form (Office)

Article Metrics & Impact

Article Views

0

Total views since publication

PDF Downloads

1

Total downloads since publication

Geographic Reach

5

Indexing, Archiving & Preservation

Google Scholar
Academia
ResearchGate
Crossref
SSRN
Semantic Scholar
Thomson Reuters
WorldCat
Mendeley
OpenAlex
EBSCO
Zenodo

Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.

Ethics, Compliance & Transparency

Plagiarism Screening

This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.

Conflict of Interest

The authors declare no conflict of interest related to this research work.

Funding Information

No funding information available for this research.

Similar & Recommended Articles

Similar Articles by Topic

Related research in the same subject area

Loading similar articles...