Predictive analytics with ensemble modeling in laparoscopic surgery:A technical note
作者机构：Department of Emergency MedicineSir Run Run Shaw HospitalZhejiang University School of MedicineHangzhou 310016China Department of Critical Care MedicineJinhua Hospital of Zhejiang University School of MedicineJinhua 321000China Emergency DepartmentZigong Fourth People's HospitalZigong 643000China Institute of Medical Big DataZigong Academy of Artificial Intelligence and Big Data for Medical Science Artificial IntelligenceZigong 643000China Artificial Intelligence Key Laboratory of Sichuan ProvinceZigong 643000China
出 版 物：《Laparoscopic, Endoscopic and Robotic Surgery》 (腔镜、内镜与机器人外科（英文）)
年 卷 期：2022年第5卷第1期
页 面：25-34页
学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学]
基 金：funding from RUIYI emergency medical research fund(202013) Open Foundation of Artificial Intelligence Key Laboratory of Sichuan Province(2020RYY03) Research project of Health and Family Planning Commission of Sichuan Province(17PJ136) funding from Key Research&Development project of Zhejiang Province(2021C03071)
主 题：Ensemble modeling Laparoscopic surgery Machine learning
摘 要：Predictive analytics have been widely used in the literature with respect to laparoscopic surgery and risk ***,most predictive analytics in this field exploit generalized linearmodels for predictive purposes,which are limited by model assumptionsdincluding linearity between response variables and additive interactions between *** many instances,such assumptions may not hold true,and the complex relationship between predictors and response variables is usually *** address this limitation,machine-learning algorithms can be employed to model the underlying *** advantage of machine learning algorithms is that they usually do not require strict assumptions regarding data structure,and they are able to learn complex functional forms using a nonparametric ***,two or more machine learning algorithms can be synthesized to further improve predictive *** a process is referred to as ensemble modeling,and it has been used broadly in various ***,this approach has not been widely reported in the laparoscopic surgical literature due to its complexity in both model training and *** this technical note,we provide a comprehensive overview of the ensemble-modeling technique and a step-by-step tutorial on how to implement ensemble modeling.
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