Machine learning-driven prediction of medical expenses in triple-vessel PCI patients using feature selection.

ABSTRACT: Revascularization therapies, such as percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG), alleviate symptoms and treat myocardial ischemia. Patients with multivessel disease, particularly those undergoing 3-vessel PCI, are more susceptible to procedural complications, which can increase healthcare costs. Developing efficient strategies for resource allocation has become a paramount concern due to tightening healthcare budgets and the escalating costs of treating heart conditions. Therefore, it is essential to develop an evaluation model to estimate the costs of PCI surgeries and identify the key factors influencing these costs to enhance healthcare quality. This study utilized the National Health Insurance Research Database (NHIRD), encompassing data from mu

SUBMITTER: Chen KY 

PROVIDER: S-EPMC11744989 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature