Kidney Research and Clinical Practice

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Original Articles

Predicting long-term mortality of patients with postoperative acute kidney injury following noncardiac general anesthesia surgery using machine learning: Bo Yeon Choi, Wona Choi, Jiwon Min et al.; Received April 12, 2024 Accepted July 1, 2024 Published online September 26, 2024; [Epub ahead of print]; Full text PubReader ePub PDF Supplementary Material

Review Articles

Artificial intelligence and machine learning’s role in sepsis-associated acute kidney injury: Wisit Cheungpasitporn, Charat Thongprayoon, Kianoush B. Kashani; Kidney Res Clin Pract. 2024;43(4):417-432. Published online June 20, 2024; DOI: https://doi.org/10.23876/j.krcp.23.298
Web of Science 2 Cited By 3; Full text PubReader ePub PDF

Original Articles

A machine learning-based approach for predicting renal function recovery in general ward patients with acute kidney injury: Nam-Jun Cho, Inyong Jeong, Yeongmin Kim et al.; Kidney Res Clin Pract. 2024;43(4):538-547. Published online June 17, 2024; DOI: https://doi.org/10.23876/j.krcp.23.330; Full text PubReader ePub PDF Supplementary Material

Machine learning-based 2-year risk prediction tool in immunoglobulin A nephropathy: Yujeong Kim, Jong Hyun Jhee, Chan Min Park et al.; Kidney Res Clin Pract. 2024;43(6):739-752. Published online October 27, 2023; DOI: https://doi.org/10.23876/j.krcp.23.076
Cited By 1; Full text PubReader ePub PDF Supplementary Material

Volume 43, No. 6

Kidney Research
and
Clinical Practice

Print ISSN: 2211-9132
Online ISSN: 2211-9140

Impact Factor

2.9

MOST VIEWED MOST CITED

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Cited By 33	GLP-1 receptor agonists in diabetic kidney disease: current evidence and future directions
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