Accurate Prediction of Myocardial Infarction By Comparing Logistic Regression Algorithm with CatBoost Classifier

نویسندگان

چکیده

Aim: The forecast of Myocardial Infarction for humans employing a Machine learning model by corresponding Logistic Regression Algorithm with CatBoost Classifier. accuracy is enhanced utilizing the novel LR Materials and Methods: study utilized total 20 sample iterations, 10 samples per group. Group 1 was analyzed using logistic regression algorithm, while 2 decision tree classifier. statistical power set at 80%, confidence level 95%. Results: outcome 94.61% Classifier 79.516%, both groups are statistically significant as p = 0.015 (<0.05) value in independent T-test between CB Conclusion: This research concludes that algorithm gives most accurate mortality difference 15.1%, compared to

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ژورنال

عنوان ژورنال: E3S web of conferences

سال: 2023

ISSN: ['2555-0403', '2267-1242']

DOI: https://doi.org/10.1051/e3sconf/202339904019