Comparing the Performance of Machine Learning Models and Conventional Risk Scores for Predicting Major Adverse Cardiovascular Cerebrovascular Events After Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction: Systematic Review and Meta-Analysis
Abstract BackgroundMachine learning (ML) models may offer greater clinical utility than conventional risk scores, such as the Thrombolysis in Myocardial Infarction (TIMI) and Global Registry of Acute Coronary Events (GRACE) risk scores. However, there is a lack of knowledge on...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2025-07-01
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| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2025/1/e76215 |
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