Machine Learning Prediction Models for Myocardial Injury After Non-cardiac Surgery: A Scoping Review

Key Points

• The aim is to review existing machine learning models that predict myocardial injury following non-cardiac surgeries.
• Conducted a scoping review of relevant literature on machine learning applications.
• Analyzed models focusing on their predictive accuracy and methodologies.
• Included various studies that developed or validated predictive models for myocardial injury.
• Identified multiple machine learning models with varying effectiveness in predicting myocardial injury.
• Most models utilize preoperative clinical data to assess risk.
• Findings indicate the potential for improvement in postoperative care using predictive analytics.