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Alfieri, Francesca; Ancona, Andrea; Tripepi, Giovanni; Rubeis, Andrea; Arjoldi, Niccolò; Finazzi, Stefano; Cauda, Valentina; Fagugli, Riccardo Maria; Hsiao, Yi-Hsuan; Bai, Songnan; Zhou, Yongsen; Jia, Huaiyuan; Ding, Runze; Chen, Yufeng; Wang, Zuankai; Chirarattananon, Pakpong

发表日期：2023

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External validation of a deep-learning model to predict severe acute kidney injury based on urine output changes in critically ill patients

对基于危重患者尿量变化预测严重急性肾损伤的深度学习模型进行外部验证

期刊:Journal of Nephrology

影响因子:2.6

doi:10.1007/s40620-022-01335-8

Alfieri, Francesca; Ancona, Andrea; Tripepi, Giovanni; Randazzo, Vincenzo; Paviglianiti, Annunziata; Pasero, Eros; Vecchi, Luigi; Politi, Cristina; Cauda, Valentina; Fagugli, Riccardo Maria

A deep-learning model to continuously predict severe acute kidney injury based on urine output changes in critically ill patients

基于重症患者尿量变化的深度学习模型，可连续预测严重急性肾损伤。

期刊:Journal of Nephrology

影响因子:2.6

doi:10.1007/s40620-021-01046-6

Alfieri, Francesca; Ancona, Andrea; Tripepi, Giovanni; Crosetto, Dario; Randazzo, Vincenzo; Paviglianiti, Annunziata; Pasero, Eros; Vecchi, Luigi; Cauda, Valentina; Fagugli, Riccardo Maria

Outcome in noncritically ill patients with acute kidney injury requiring dialysis: Effects of differing medical staffs and organizations

非重症急性肾损伤透析患者的预后：不同医疗团队和机构的影响

期刊:Medicine

影响因子:1.4

doi:10.1097/MD.0000000000004277

Fagugli, Riccardo Maria; Patera, Francesco; Battistoni, Sara; Tripepi, Giovanni

Changes in the perceived epidemiology of primary hyperaldosteronism

原发性醛固酮增多症流行病学认知的变化

期刊:International Journal of Hypertension

影响因子:1.7

doi:10.4061/2011/162804

Fagugli, Riccardo Maria; Taglioni, Chiara

Publisher Correction: Energy efficient perching and takeoff of a miniature rotorcraft

出版商更正：微型旋翼机的节能栖息和起飞

External validation of a deep-learning model to predict severe acute kidney injury based on urine output changes in critically ill patients

对基于危重患者尿量变化预测严重急性肾损伤的深度学习模型进行外部验证

A deep-learning model to continuously predict severe acute kidney injury based on urine output changes in critically ill patients

基于重症患者尿量变化的深度学习模型，可连续预测严重急性肾损伤。

Outcome in noncritically ill patients with acute kidney injury requiring dialysis: Effects of differing medical staffs and organizations

非重症急性肾损伤透析患者的预后：不同医疗团队和机构的影响

Changes in the perceived epidemiology of primary hyperaldosteronism

原发性醛固酮增多症流行病学认知的变化