Application of group LASSO regression based Bayesian networks in risk factors exploration and disease prediction for acute kidney injury in hospitalized patients with hematologic malignancies

Application of group LASSO regression based Bayesian networks in risk factors exploration and disease prediction for acute kidney injury in hospitalized patients with hematologic malignancies

Abstract Background Patients who were diagnosed with hematologic malignancies (HM) had a higher risk of acute kidney injury (AKI). This study applies the Bayesian networks (BNs) to investigate the interrelationships between AKI and its risk factors among HM patients, and to evaluate the predictive a...

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Bibliographic Details
Main Authors: Yang Li, Xiaohong Chen, Yimei Wang, Jiachang Hu, Ziyan Shen, Xiaoqiang Ding
Format: Article
Language:English
Published: BMC 2020-05-01
Series:BMC Nephrology
Subjects:
Acute kidney injury
Hematologic malignancy
Bayesian networks
Disease prediction
Clinical epidemiology
Online Access:http://link.springer.com/article/10.1186/s12882-020-01786-w

Internet

http://link.springer.com/article/10.1186/s12882-020-01786-w

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