Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm

Integrating Internet technologies with traditional healthcare systems has enabled the emergence of cloud healthcare systems. These systems aim to optimize the balance between online diagnosis and offline treatment to effectively reduce patients’ waiting times and improve the utilization of idle medi...

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Autores principales: Pang, Xinyu, Ge, Yong-Feng, Wang, Kate, Traina, Agma J. M., Wang, Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10307766/
https://www.ncbi.nlm.nih.gov/pubmed/37397165
http://dx.doi.org/10.1007/s13755-023-00230-1
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author Pang, Xinyu
Ge, Yong-Feng
Wang, Kate
Traina, Agma J. M.
Wang, Hua
author_facet Pang, Xinyu
Ge, Yong-Feng
Wang, Kate
Traina, Agma J. M.
Wang, Hua
author_sort Pang, Xinyu
collection PubMed
description Integrating Internet technologies with traditional healthcare systems has enabled the emergence of cloud healthcare systems. These systems aim to optimize the balance between online diagnosis and offline treatment to effectively reduce patients’ waiting times and improve the utilization of idle medical resources. In this paper, a distributed genetic algorithm (DGA) is proposed as a means to optimize the balance of patient assignment (PA) in cloud healthcare systems. The proposed DGA utilizes individuals as solutions for the PA optimization problem and generates better solutions through the execution of crossover, mutation, and selection operators. Besides, the distributed framework in the DGA is proposed to improve its population diversity and scalability. Experimental results demonstrate the effectiveness of the proposed DGA in optimizing the PA problem within the cloud healthcare systems.
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spelling pubmed-103077662023-06-30 Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm Pang, Xinyu Ge, Yong-Feng Wang, Kate Traina, Agma J. M. Wang, Hua Health Inf Sci Syst Research Integrating Internet technologies with traditional healthcare systems has enabled the emergence of cloud healthcare systems. These systems aim to optimize the balance between online diagnosis and offline treatment to effectively reduce patients’ waiting times and improve the utilization of idle medical resources. In this paper, a distributed genetic algorithm (DGA) is proposed as a means to optimize the balance of patient assignment (PA) in cloud healthcare systems. The proposed DGA utilizes individuals as solutions for the PA optimization problem and generates better solutions through the execution of crossover, mutation, and selection operators. Besides, the distributed framework in the DGA is proposed to improve its population diversity and scalability. Experimental results demonstrate the effectiveness of the proposed DGA in optimizing the PA problem within the cloud healthcare systems. Springer International Publishing 2023-06-29 /pmc/articles/PMC10307766/ /pubmed/37397165 http://dx.doi.org/10.1007/s13755-023-00230-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Pang, Xinyu
Ge, Yong-Feng
Wang, Kate
Traina, Agma J. M.
Wang, Hua
Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm
title Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm
title_full Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm
title_fullStr Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm
title_full_unstemmed Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm
title_short Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm
title_sort patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10307766/
https://www.ncbi.nlm.nih.gov/pubmed/37397165
http://dx.doi.org/10.1007/s13755-023-00230-1
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