Connecting you to content on EBSCOhost

Works by Zhang, Buyao

Results: 5

1

Machine Learning for Predicting Risk and Prognosis of Acute Kidney Disease in Critically Ill Elderly Patients During Hospitalization: Internet-Based and Interpretable Model Study.

Published in:

Journal of Medical Internet Research, 2024, v. 26, p. 1, doi. 10.2196/51354

By:

Li, Mingxia;
Han, Shuzhe;
Liang, Fang;
Hu, Chenghuan;
Zhang, Buyao;
Hou, Qinlan;
Zhao, Shuangping

Publication type:

Article

2

Development and deployment of interpretable machine-learning model for predicting in-hospital mortality in elderly patients with acute kidney disease.

Published in:

Renal Failure, 2022, v. 44, n. 1, p. 1896, doi. 10.1080/0886022X.2022.2142139

By:

Li, Mingxia;
Zhuang, Qinghe;
Zhao, Shuangping;
Huang, Li;
Hu, Chenghuan;
Zhang, Buyao;
Hou, Qinlan

Publication type:

Article

3

Nomogram to predict the risk of septic acute kidney injury in the first 24 h of admission: an analysis of intensive care unit data.

Published in:

Renal Failure, 2020, v. 42, n. 1, p. 428, doi. 10.1080/0886022X.2020.1761832

By:

Deng, Fuxing;
Peng, Milin;
Li, Jing;
Chen, Yana;
Zhang, Buyao;
Zhao, Shuangping

Publication type:

Article

4

Establishment and external validation of an online dynamic nomogram for predicting in-hospital death risk in sepsis-associated acute kidney disease.

Published in:

Current Medical Research & Opinion, 2022, v. 38, n. 10, p. 1705, doi. 10.1080/03007995.2022.2101818

By:

Li, Mingxia;
Zhao, Shuangping;
Huang, Li;
Hu, Chenghuan;
Zhang, Buyao;
Hou, Qinlan

Publication type:

Article

5

Exosomal microRNA-342-5p secreted from adipose-derived mesenchymal stem cells mitigates acute kidney injury in sepsis mice by inhibiting TLR9.

Published in:

Biological Procedures Online, 2023, v. 25, n. 1, p. 1, doi. 10.1186/s12575-023-00198-y

By:

Liu, Wei;
Hu, Chenghuan;
Zhang, Buyao;
Li, Mingxia;
Deng, Fuxing;
Zhao, Shuangping

Publication type:

Article