Multi-outcome predictive modelling of anesthesia patients
Le Yi Wang
George M.McKelvey
Hong Wang
1.Department of Electrical and Computer Engineering, Wayne State University, Detroit, MI 48202, USA2.Department of Anesthesiology, Detroit Medical Center, Detroit, MI 48201, USA3.Department of Anesthesiology, West Virginia University Hospital, Morgantown, WV 26505, USA
摘要：Conjunctive use of anesthetic agents results in drug interactions which can alter or influence multiple patient outcomes such as anesthesia depth,and cardiorespiratory parameters which can also be altered by patient conditions and surgical procedures.Using artificial intelligence technology to continuously gather data of drug infusion and patient outcomes,we can generate reliable computer models individualized for a patient during specific stages of particular surgical procedures.This data can then be used to extend the current anesthesia monitoring functions to include future impact prediction,drug administration planning,and anesthesia decisions.
机标关键词：surgical proceduresartificial intelligencedrug interactions
分类号：R614.2(外科手术学)
论文发表日期：2019-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：5( 430-434 )
英文信息