Machine learning in CTEPH: predicting the efficacy of BPA based on clinical and echocardiographic features

Machine learning in CTEPH: predicting the efficacy of BPA based on clinical and echocardiographic features

Abstract Background This study aims to develop a machine learning (ML)-based predictive model for evaluating the efficacy of percutaneous pulmonary balloon angioplasty (BPA) in patients with chronic thromboembolic pulmonary hypertension (CTEPH) by integrating clinical and echocardiographic parameter...

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Bibliographic Details
Main Authors: Qiumeng Xi, Juanni Gong, Jianfeng Wang, Xiaojuan Guo, Yuanhua Yang, Xiuzhang lv, Suqiao Yang, Yidan Li
Format: Article
Language:English
Published: BMC 2025-08-01
Series:BMC Medical Imaging
Subjects:
Chronic thromboembolic pulmonary hypertension
Pulmonary balloon angioplasty
Machine learning
Echocardiography
Online Access:https://doi.org/10.1186/s12880-025-01870-3
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https://doi.org/10.1186/s12880-025-01870-3

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