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An Optimized Framework for Surgical Team Selection
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作者 Hemant Petwal Rinkle Rani 《Computers, Materials & Continua》 SCIE EI 2021年第11期2563-2582,共20页
In the healthcare system,a surgical team is a unit of experienced personnel who provide medical care to surgical patients during surgery.Selecting a surgical team is challenging for a multispecialty hospital as the pe... In the healthcare system,a surgical team is a unit of experienced personnel who provide medical care to surgical patients during surgery.Selecting a surgical team is challenging for a multispecialty hospital as the performance of its members affects the efficiency and reliability of the hospital’s patient care.The effectiveness of a surgical team depends not only on its individual members but also on the coordination among them.In this paper,we addressed the challenges of surgical team selection faced by a multispecialty hospital and proposed a decision-making framework for selecting the optimal list of surgical teams for a given patient.The proposed framework focused on improving the existing surgical history management system by arranging surgery-bound patients into optimal subgroups based on similar characteristics and selecting an optimal list of surgical teams for a new surgical patient based on the patient’s subgroups.For this end,two population-based meta-heuristic algorithms for clustering of mixed datasets and multi-objective optimization were proposed.The proposed algorithms were tested using different datasets and benchmark functions.Furthermore,the proposed framework was validated through a case study of a real postoperative surgical dataset obtained from the orthopedic surgery department of a multispecialty hospital in India.The results revealed that the proposed framework was efficient in arranging patients in optimal groups as well as selecting optimal surgical teams for a given patient. 展开更多
关键词 Multi-objective optimization artificial electric field algorithm mixed dataset clustering surgical team strength Pareto
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