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Intelligent Control Techniques for the Detection of Biomedical Ear Infections

The capacity to carry out one's regular tasks is affected to varying degrees by hearing difficulties. Poorer understanding, slower learning, and an overall reduction in efficiency in academic endeavours are just a few of the negative impacts of hearing impairments on children's performance...

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Autores principales: Abdulaal, Mohammed J., Mehedi, Ibrahim M., Aljohani, Abdulah Jeza, Milyani, Ahmad H., Mahmoud, Mohamed, Sahu, Manish Kumar, Abusorrah, Abdullah M., Meem, Rahtul Jannat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9467762/
https://www.ncbi.nlm.nih.gov/pubmed/36105634
http://dx.doi.org/10.1155/2022/9653513
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author Abdulaal, Mohammed J.
Mehedi, Ibrahim M.
Aljohani, Abdulah Jeza
Milyani, Ahmad H.
Mahmoud, Mohamed
Sahu, Manish Kumar
Abusorrah, Abdullah M.
Meem, Rahtul Jannat
author_facet Abdulaal, Mohammed J.
Mehedi, Ibrahim M.
Aljohani, Abdulah Jeza
Milyani, Ahmad H.
Mahmoud, Mohamed
Sahu, Manish Kumar
Abusorrah, Abdullah M.
Meem, Rahtul Jannat
author_sort Abdulaal, Mohammed J.
collection PubMed
description The capacity to carry out one's regular tasks is affected to varying degrees by hearing difficulties. Poorer understanding, slower learning, and an overall reduction in efficiency in academic endeavours are just a few of the negative impacts of hearing impairments on children's performance, which may range from mild to severe. A significant factor in determining whether or not there will be a decrease in performance is the kind and source of impairment. Research has shown that the Artificial Neural Network technique is capable of modelling both linear and nonlinear solution surfaces in a trustworthy way, as demonstrated in previous studies. To improve the precision with which hearing impairment challenges are diagnosed, a neural network backpropagation approach has been developed with the purpose of fine-tuning the diagnostic process. In particular, it highlights the vital role performed by medical informatics in supporting doctors in the identification of diseases as well as the formulation of suitable choices via the use of data management and knowledge discovery. As part of the intelligent control method, it is proposed in this research to construct a Histogram Equalization (HE)-based Adaptive Center-Weighted Median (ACWM) filter, which is then used to segment/detect the OM in tympanic membrane images using different segmentation methods in order to minimise noise and improve the image quality. A tympanic membrane dataset, which is freely accessible, was used in all experiments.
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spelling pubmed-94677622022-09-13 Intelligent Control Techniques for the Detection of Biomedical Ear Infections Abdulaal, Mohammed J. Mehedi, Ibrahim M. Aljohani, Abdulah Jeza Milyani, Ahmad H. Mahmoud, Mohamed Sahu, Manish Kumar Abusorrah, Abdullah M. Meem, Rahtul Jannat Comput Intell Neurosci Research Article The capacity to carry out one's regular tasks is affected to varying degrees by hearing difficulties. Poorer understanding, slower learning, and an overall reduction in efficiency in academic endeavours are just a few of the negative impacts of hearing impairments on children's performance, which may range from mild to severe. A significant factor in determining whether or not there will be a decrease in performance is the kind and source of impairment. Research has shown that the Artificial Neural Network technique is capable of modelling both linear and nonlinear solution surfaces in a trustworthy way, as demonstrated in previous studies. To improve the precision with which hearing impairment challenges are diagnosed, a neural network backpropagation approach has been developed with the purpose of fine-tuning the diagnostic process. In particular, it highlights the vital role performed by medical informatics in supporting doctors in the identification of diseases as well as the formulation of suitable choices via the use of data management and knowledge discovery. As part of the intelligent control method, it is proposed in this research to construct a Histogram Equalization (HE)-based Adaptive Center-Weighted Median (ACWM) filter, which is then used to segment/detect the OM in tympanic membrane images using different segmentation methods in order to minimise noise and improve the image quality. A tympanic membrane dataset, which is freely accessible, was used in all experiments. Hindawi 2022-09-05 /pmc/articles/PMC9467762/ /pubmed/36105634 http://dx.doi.org/10.1155/2022/9653513 Text en Copyright © 2022 Mohammed J. Abdulaal 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 Research Article
Abdulaal, Mohammed J.
Mehedi, Ibrahim M.
Aljohani, Abdulah Jeza
Milyani, Ahmad H.
Mahmoud, Mohamed
Sahu, Manish Kumar
Abusorrah, Abdullah M.
Meem, Rahtul Jannat
Intelligent Control Techniques for the Detection of Biomedical Ear Infections
title Intelligent Control Techniques for the Detection of Biomedical Ear Infections
title_full Intelligent Control Techniques for the Detection of Biomedical Ear Infections
title_fullStr Intelligent Control Techniques for the Detection of Biomedical Ear Infections
title_full_unstemmed Intelligent Control Techniques for the Detection of Biomedical Ear Infections
title_short Intelligent Control Techniques for the Detection of Biomedical Ear Infections
title_sort intelligent control techniques for the detection of biomedical ear infections
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9467762/
https://www.ncbi.nlm.nih.gov/pubmed/36105634
http://dx.doi.org/10.1155/2022/9653513
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