Predicting the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms

Predicting the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms

Abstract Background This study aimed to develop predictive models with robust generalization capabilities for assessing the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms. Methods Data were collected from two centers and categorized into development and va...

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Bibliographic Details
Main Authors: Haobo Kong, Yong Li, Ya Shen, Jingjing Pan, Min Liang, Zhi Geng, Yanbei Zhang
Format: Article
Language:English
Published: BMC 2024-12-01
Series:European Journal of Medical Research
Subjects:
Machine learning
Pulmonary embolism
Pulmonary tuberculosis
Risk prediction
Online Access:https://doi.org/10.1186/s40001-024-02218-3
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