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Efficient model for emergency departments: Real case study
Faculty
Computer Science
Year:
2022
Type of Publication:
ZU Hosted
Pages:
Authors:
Osama Mohamed Abdelsalam Ahmed Elkomy
Staff Zu Site
Abstract In Staff Site
Journal:
Computers, Materials and Continua Computers, Materials and ContinuaComputers, Materials and Continua
Volume:
Keywords :
Efficient model , emergency departments: Real case
Abstract:
There are several challenges that hospitals are facing according to the emergency department (ED). The main two issues are department capacity and lead time. However, the lack of consensus on performance criteria to evaluate ED increases the complication of this process. Thus, this study aims to evaluate the efficiency of the emergency department in 20 Egyptian hospitals (12 private and 8 general hospitals) based on 13 performance metrics. This research suggests an integrated evaluation model assess ED under a framework of plithogenic theory. The proposed framework addressed uncertainty and ambiguity in information with an efficient manner via presenting the evaluation expression by plithogenic numbers. Data Envelopment Analysis (DEA) technique is used in order to measure the efficiency of the emergency department of 20 hospitals according to the number of treated patients and effect on patient’s life quality based on 11 factors. Using the Analytic Hierarchy Process (AHP), the weight of efficiency factors will be measured based on neutrosophic linguistic scale pairwise comparison. Plithogenic operations provide more accurate aggregation result according to contradiction degree between criteria values. The results show that ten of the hospitals are providing efficient service in their emergency department, while the other ten are less efficient. The analysis of the results shows that 58% of private hospitals emergency department is operating efficiently, while the efficient general hospitals represent 38%.
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Osama Mohamed Abdelsalam Ahmed Elkomy, "Two-Stage Deep Learning Framework for Discrimination between COVID-19 and Community-Acquired Pneumonia from Chest CT scans.", ELSEVIER, 2021
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Osama Mohamed Abdelsalam Ahmed Elkomy, "Recognition of phonetic Arabic figures via wavelet based Mel Frequency Cepstrum using HMMs", HBRC Journal, 2014
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Osama Mohamed Abdelsalam Ahmed Elkomy, "Multi-Objective Task Scheduling Approach for Fog Computing.", IEEE Access, 2021
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Osama Mohamed Abdelsalam Ahmed Elkomy, "An Improved Binary Grey-Wolf Optimizer with Simulated Annealing for Feature Selection", IEEE Access, 2021
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Department Related Publications
Osama Mohamed Abdelsalam Ahmed Elkomy, "MT-nCov-Net: A Multitask Deep-Learning Framework for Efficient Diagnosis of COVID-19 Using Tomography Scans", IEEE, 2021
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Osama Mohamed Abdelsalam Ahmed Elkomy, "Two-Stage Deep Learning Framework for Discrimination between COVID-19 and Community-Acquired Pneumonia from Chest CT scans.", ELSEVIER, 2021
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