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Artificial neural network prediction of same-day discharge following primary total knee arthroplasty based on preoperative and intraoperative variables.
The Bone & Joint Journal ( IF 4.6 ) Pub Date : 2021-8-3 , DOI: 10.1302/0301-620x.103b8.bjj-2020-1013.r2 Chapman Wei 1 , Theodore Quan 1 , Kevin Y Wang 2 , Alex Gu 1, 3 , Safa C Fassihi 1 , Cynthia A Kahlenberg 4 , Michael-Alexander Malahias 4 , Jiabin Liu 5 , Savyasachi Thakkar 2 , Alejandro Gonzalez Della Valle 3 , Peter K Sculco 3
The Bone & Joint Journal ( IF 4.6 ) Pub Date : 2021-8-3 , DOI: 10.1302/0301-620x.103b8.bjj-2020-1013.r2 Chapman Wei 1 , Theodore Quan 1 , Kevin Y Wang 2 , Alex Gu 1, 3 , Safa C Fassihi 1 , Cynthia A Kahlenberg 4 , Michael-Alexander Malahias 4 , Jiabin Liu 5 , Savyasachi Thakkar 2 , Alejandro Gonzalez Della Valle 3 , Peter K Sculco 3
Affiliation
This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA).
中文翻译:
基于术前和术中变量的初次全膝关节置换术后当天出院的人工神经网络预测。
本研究使用人工神经网络 (ANN) 模型确定最重要的术前和围手术期变量,以预测接受全膝关节置换术 (TKA) 的患者当天出院。
更新日期:2021-08-03
中文翻译:
基于术前和术中变量的初次全膝关节置换术后当天出院的人工神经网络预测。
本研究使用人工神经网络 (ANN) 模型确定最重要的术前和围手术期变量,以预测接受全膝关节置换术 (TKA) 的患者当天出院。