Why the study?
Machine learning prediction models often outperform conventional statistical methods, but their application to determine risk factors and predict in-hospital mortality after prosthetic valve replacement surgery needed assessment.
What are the risk factors and the best machine learning prediction models for in-hospital mortality among patients undergoing prosthetic valve replacement surgery?
What are the risk factors and the best machine learning prediction models for in-hospital mortality among patients undergoing prosthetic valve replacement surgery?
This study aims to identify the best machine learning models for predicting in-hospital mortality after prosthetic valve replacement.
Background & Objective: Machine learning and artificial intelligence are useful tools to analyze data with multiple variables. It has been shown that the prediction models obtained by Machine learning have better performance than the conventional statistical methods. This study was aimed to assess the risk factors and determine the best machine learning prediction model/s for in-hospital mortality among patients who underwent prosthetic valve replacement surgery.
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Shojaeifard et al. (2023) studied this question.
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