Correction: The infection post flexible UreteroreNoscopy (I-FUN) predictive model based on machine learning: a new clinical tool to assess the risk of sepsis post retrograde intrarenal surgery for kidney stone disease.

IF 2.8 2区医学 Q2 UROLOGY & NEPHROLOGY

World Journal of Urology Pub Date : 2024-11-28 DOI:10.1007/s00345-024-05390-7

Daniele Castellani, Virgilio De Stefano, Carlo Brocca, Giorgio Mazzon, Antonio Celia, Andrea Bosio, Claudia Gozzo, Eugenio Alessandria, Luigi Cormio, Runeel Ratnayake, Andrea Vismara Fugini, Tonino Morena, Yiloren Tanidir, Tarik Emre Sener, Simon Choong, Stefania Ferretti, Andrea Pescuma, Salvatore Micali, Nicola Pavan, Alchiede Simonato, Roberto Miano, Luca Orecchia, Giacomo Maria Pirola, Angelo Naselli, Esteban Emiliani, Pedro Hernandez-Penalver, Michele Di Dio, Claudio Bisegna, Davide Campobasso, Emanuele Serafin, Alessandro Antonelli, Emanuele Rubilotta, Deepak Ragoori, Emanuele Balloni, Marina Paolanti, Vineet Gauhar, Andrea Benedetto Galosi

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更正：基于机器学习的输尿管软镜术后感染（I-FUN）预测模型：评估肾结石逆行肾内手术后脓毒症风险的新临床工具。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

World Journal of Urology 医学-泌尿学与肾脏学

CiteScore

6.80

自引率

8.80%

发文量

317

审稿时长

4-8 weeks

期刊介绍： The WORLD JOURNAL OF UROLOGY conveys regularly the essential results of urological research and their practical and clinical relevance to a broad audience of urologists in research and clinical practice. In order to guarantee a balanced program, articles are published to reflect the developments in all fields of urology on an internationally advanced level. Each issue treats a main topic in review articles of invited international experts. Free papers are unrelated articles to the main topic.