A novel post-percutaneous nephrolithotomy sepsis prediction model using machine learning.
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Full Title: BMC Urol
Abbreviation: BMC Urol
Country: Unknown
Publisher: Unknown
Language: N/A
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"Declarations Ethics approval and consent to participateThis retrospective study was in accordance with the ethical standards of Helsinki Declaration and its later amendments and was approved by the Ethics Committee of Changhai Hospital. Informed written consent was also obtained from all the patients in this study. Consent for publicationNot applicable. Competing interestsThe authors declare no competing interests. Competing interests The authors declare no competing interests."
"Funding This study was supported by Shanghai Science and Technology Support Project in Biomedicine (17441900800, Yonghan Peng)."
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Last Updated: Aug 05, 2025