Analysis of Accuracy Metric of Machine Learning Algorithms in Predicting Heart Disease
Introduction: Heart disease is, for the most part, alluding to conditions that include limited or blocked veins that can prompt a heart attack, chest torment or stroke. Earlier identification of heart disease may reduce the death rate. The cost of medical diagnosis makes it perverse to cure it for t...
Main Authors: | Sajad Yousefi, Maryam Poornajaf |
---|---|
Format: | Article |
Language: | English |
Published: |
Hamara Afzar
2023-04-01
|
Series: | Frontiers in Health Informatics |
Subjects: | |
Online Access: | http://ijmi.ir/index.php/IJMI/article/view/402 |
Similar Items
-
Improvement of the Performance of Machine Learning Algorithms in Predicting Breast Cancer
by: Maryam Poornajaf, et al.
Published: (2023-03-01) -
Common Problems With the Usage of F-Measure and Accuracy Metrics in Medical Research
by: Luigi Lavazza, et al.
Published: (2023-01-01) -
Forecasting Coronary Heart Disease Risk With a 2-Step Hybrid Ensemble Learning Method and Forward Feature Selection Algorithm
by: Sushree Chinmayee Patra, et al.
Published: (2023-01-01) -
The index of prediction accuracy: an intuitive measure useful for evaluating risk prediction models
by: Michael W. Kattan, et al.
Published: (2018-05-01) -
EAGA-MLP—An Enhanced and Adaptive Hybrid Classification Model for Diabetes Diagnosis
by: Sushruta Mishra, et al.
Published: (2020-07-01)