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February 27, 2022SHILAP Revista de lepidopterología224 citationsOpen Access

Machine Learning Technology-Based Heart Disease Detection Models

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Why the study?

Do machine learning models improve the accuracy of early heart disease detection?

Population

Patients evaluated for heart disease and heart failure

Comparison

Machine learning models for heart disease… vs Comparison among different machine learning models

Design

Other

Authors

UNUmarani NagavelliVeterinary Biological and Research InstituteDSDebabrata SamantaIndian Institute of Technology KharagpurPCPartha ChakrabortyAmerican University

Discussion

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Member takes

Overview

ML models warrant further testing for heart disease detection; leaves open any clinical benefit pending prospective validation.

Structured PICO

Do machine learning models improve the accuracy of early heart disease detection?

P
Population
Patients evaluated for heart disease and heart failure
I
Intervention
Machine learning models (Naïve Bayes, SVM, XGBoost, DBSCAN, SMOTE-ENN) for heart disease detection
C
Comparator
Comparison among different machine learning models
O
Outcome
Diagnostic performance (precision, accuracy, f1-measure, and recall)surrogate

Machine learning models, particularly those utilizing XGBoost and SVM, offer potential tools for clinicians to improve the early detection and diagnosis of heart disease.

Cite This Study

Nagavelli et al. (2022) studied this question.

synapsesocial.com/papers/69de595c210a0977fce93d9dhttps://doi.org/10.1155/2022/7351061
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