ArticleApplied soft computing2021
HSSAGA: Designation and scheduling of nurses for taking care of COVID-19 patients using novel method of Hybrid Salp Swarm Algorithm and Genetic Algorithm.
Article in Applied soft computing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Process Improvement Approaches for Increasing the Response of Emergency Departments against the COVID-19 Pandemic: A Systematic Review.International journal of environmental research and public health · 2021Pooled it
- An integrated TOPSIS and ARAS method multi-criteria decision-making approach for optimizing investment portfolios using goal programming and genetic algorithm model.Scientific reports · 2025Article
- Personnel Scheduling during the COVID-19 Pandemic: A Probabilistic Graph-Based Approach.Healthcare (Basel, Switzerland) · 2023Article
- Derivation of a Unique, Algorithm-Based Approach to Cancer Patient Navigator Workload Management.JCO clinical cancer informatics · 2023Article
- Development of a new personalized staff-scheduling method with a work-life balance perspective: case of a hospital.Annals of operations research · 2023Article
- Article
- Towards an efficient collection and transport of COVID-19 diagnostic specimens using genetic-based algorithms.Applied soft computing · 2022Article
- An Analysis of New Feature Extraction Methods Based on Machine Learning Methods for Classification Radiological Images.Computational intelligence and neuroscience · 2022Article
- Cardiac Implications of COVID-19 in Deceased and Recovered Patients: A Systematic Review.Interdisciplinary perspectives on infectious diseases · 2022Review
- Presented a Framework of Computational Modeling to Identify the Patient Admission Scheduling Problem in the Healthcare System.Journal of healthcare engineering · 2022Article
- WTD-PSD: Presentation of Novel Feature Extraction Method Based on Discrete Wavelet Transformation and Time-Dependent Power Spectrum Descriptors for Diagnosis of Alzheimer's Disease.Computational intelligence and neuroscience · 2022Article
- Review
- Study of Complexity Systems in Public Health for Evaluating the Correlation between Mental Health and Age-Related Demographic Characteristics: A General Health Study.Journal of healthcare engineering · 2022Article
- Supervised learning of COVID-19 patients' characteristics to discover symptom patterns and improve patient outcome prediction.Informatics in medicine unlocked · 2022Article
- FDCNet: Presentation of the Fuzzy CNN and Fractal Feature Extraction for Detection and Classification of Tumors.Computational intelligence and neuroscience · 2022Article
- PSOWNNs-CNN: A Computational Radiology for Breast Cancer Diagnosis Improvement Based on Image Processing Using Machine Learning Methods.Computational intelligence and neuroscience · 2022Article
- Presentation of a Segmentation Method for a Diabetic Retinopathy Patient's Fundus Region Detection Using a Convolutional Neural Network.Computational intelligence and neuroscience · 2021Article
- The Progress of Medical Image Semantic Segmentation Methods for Application in COVID-19 Detection.Computational intelligence and neuroscience · 2021Review
- A Hybrid SSA and SMA with Mutation Opposition-Based Learning for Constrained Engineering Problems.Computational intelligence and neuroscience · 2021Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The COVID-19 pandemic is viewed as the most basic worldwide disaster that humankind has observed since the second World War. There is no report of any clinically endorsed antiviral medications or antibodies that are successful against COVID-19. It has quickly spread everywhere, presenting tremendous well-being, financial, ecological, and social difficulties to the whole human populace. The COVID flare-up is seriously disturbing the worldwide economy. Practically all the countries are battling to hinder the transmission of the malady by testing and treating patients, isolating speculated people through contact following, confining huge social affairs, keeping up total or incomplete lockdown, etc. Proper scheduling of nursing workers and optimal designation of nurses may significantly affect the quality of clinical facilities. It is delivered by eliminating unbalanced workloads or undue stress, which could lead to decreased nurse performance and potential human errors., Nurses are frequently asked to leave while caring for all sick patients. However, regular scheduling formulas are not thought to consider this possibility because they are out of scheduling control in typical scenarios. In this paper, a novel model of the Hybrid Salp Swarm Algorithm and Genetic Algorithm (HSSAGA) is proposed to solve nurses' scheduling and designation. The findings of the suggested test function algorithm demonstrate that this algorithm has outperformed state-of-the-art approaches.
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