Interpretable noninvasive diagnosis of tuberculous pleural effusion using LGBM and SHAP: development and clinical application of a machine learning model

Interpretable noninvasive diagnosis of tuberculous pleural effusion using LGBM and SHAP: development and clinical application of a machine learning model

Background Tuberculous pleural effusion (TPE) is a prevalent tuberculosis complication, with diagnosis presenting considerable challenges. Timely and precise identification of TPE is vital for effective patient management and prognosis, yet existing diagnostic methods tend to be invasive, lengthy, a...

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Bibliographic Details
Main Authors: Bihua Yao, Xingyu Yu, Liannv Qiu, Er-min Gu, Siyu Mao, Lei Jiang, Jijun Tong, Jianguo Wu
Format: Article
Language:English
Published: PeerJ Inc. 2025-05-01
Series:PeerJ
Subjects:
Tuberculous pleural effusion
Machine learning
Light gradient boosting machine
Predictive model
Shapley value
Model interpretability
Online Access:https://peerj.com/articles/19411.pdf
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