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A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection
Artificial Intelligence (AI) is the domain of computer science that focuses on the development of machines that operate like humans. In the field of AI, medical disease detection is an instantly growing domain of research. In the past years, numerous endeavours have been made for the improvements of...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Hindawi
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8455185/ https://www.ncbi.nlm.nih.gov/pubmed/34557257 http://dx.doi.org/10.1155/2021/5990999 |
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author | Pervaiz, Sobia Ul-Qayyum, Zia Bangyal, Waqas Haider Gao, Liang Ahmad, Jamil |
author_facet | Pervaiz, Sobia Ul-Qayyum, Zia Bangyal, Waqas Haider Gao, Liang Ahmad, Jamil |
author_sort | Pervaiz, Sobia |
collection | PubMed |
description | Artificial Intelligence (AI) is the domain of computer science that focuses on the development of machines that operate like humans. In the field of AI, medical disease detection is an instantly growing domain of research. In the past years, numerous endeavours have been made for the improvements of medical disease detection, because the errors and problems in medical disease detection cause serious wrong medical treatment. Meta-heuristic techniques have been frequently utilized for the detection of medical diseases and promise better accuracy of perception and prediction of diseases in the domain of biomedical. Particle Swarm Optimization (PSO) is a swarm-based intelligent stochastic search technique encouraged from the intrinsic manner of bee swarm during the searching of their food source. Consequently, for the versatility of numerical experimentation, PSO has been mostly applied to address the diverse kinds of optimization problems. However, the PSO techniques are frequently adopted for the detection of diseases but there is still a gap in the comparative survey. This paper presents an insight into the diagnosis of medical diseases in health care using various PSO approaches. This study presents to deliver a systematic literature review of current PSO approaches for knowledge discovery in the field of disease detection. The systematic analysis discloses the potential research areas of PSO strategies as well as the research gaps, although, the main goal is to provide the directions for future enhancement and development in this area. This paper gives a systematic survey of this conceptual model for the advanced research, which has been explored in the specified literature to date. This review comprehends the fundamental concepts, theoretical foundations, and conventional application fields. It is predicted that our study will be beneficial for the researchers to review the PSO algorithms in-depth for disease detection. Several challenges that can be undertaken to move the field forward are discussed according to the current state of the PSO strategies in health care. |
format | Online Article Text |
id | pubmed-8455185 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-84551852021-09-22 A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection Pervaiz, Sobia Ul-Qayyum, Zia Bangyal, Waqas Haider Gao, Liang Ahmad, Jamil Comput Math Methods Med Review Article Artificial Intelligence (AI) is the domain of computer science that focuses on the development of machines that operate like humans. In the field of AI, medical disease detection is an instantly growing domain of research. In the past years, numerous endeavours have been made for the improvements of medical disease detection, because the errors and problems in medical disease detection cause serious wrong medical treatment. Meta-heuristic techniques have been frequently utilized for the detection of medical diseases and promise better accuracy of perception and prediction of diseases in the domain of biomedical. Particle Swarm Optimization (PSO) is a swarm-based intelligent stochastic search technique encouraged from the intrinsic manner of bee swarm during the searching of their food source. Consequently, for the versatility of numerical experimentation, PSO has been mostly applied to address the diverse kinds of optimization problems. However, the PSO techniques are frequently adopted for the detection of diseases but there is still a gap in the comparative survey. This paper presents an insight into the diagnosis of medical diseases in health care using various PSO approaches. This study presents to deliver a systematic literature review of current PSO approaches for knowledge discovery in the field of disease detection. The systematic analysis discloses the potential research areas of PSO strategies as well as the research gaps, although, the main goal is to provide the directions for future enhancement and development in this area. This paper gives a systematic survey of this conceptual model for the advanced research, which has been explored in the specified literature to date. This review comprehends the fundamental concepts, theoretical foundations, and conventional application fields. It is predicted that our study will be beneficial for the researchers to review the PSO algorithms in-depth for disease detection. Several challenges that can be undertaken to move the field forward are discussed according to the current state of the PSO strategies in health care. Hindawi 2021-09-13 /pmc/articles/PMC8455185/ /pubmed/34557257 http://dx.doi.org/10.1155/2021/5990999 Text en Copyright © 2021 Sobia Pervaiz et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Pervaiz, Sobia Ul-Qayyum, Zia Bangyal, Waqas Haider Gao, Liang Ahmad, Jamil A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection |
title | A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection |
title_full | A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection |
title_fullStr | A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection |
title_full_unstemmed | A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection |
title_short | A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection |
title_sort | systematic literature review on particle swarm optimization techniques for medical diseases detection |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8455185/ https://www.ncbi.nlm.nih.gov/pubmed/34557257 http://dx.doi.org/10.1155/2021/5990999 |
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