A Systematic Review of Artificial Neural Networks in Medical Science and Applications

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dc.authoridMustafina, Jamila/0000-0001-5770-4111
dc.contributor.authorAl-Salman, Omar
dc.contributor.authorMustafina, Jamila
dc.contributor.authorShahoodh, Gailan
dc.date.accessioned2024-09-29T16:03:29Z
dc.date.available2024-09-29T16:03:29Z
dc.date.issued2020
dc.departmentKarabük Üniversitesien_US
dc.description13th International Conference on Developments in eSystems Engineering (DeSE) -- DEC 13-17, 2020 -- ELECTR NETWORKen_US
dc.description.abstractArtificial intelligence, and especially Artificial Neural Networks (ANN), has gain a monumental growth and interest of healthcare providers to improve medical care while reduce cost. Applications of ANN for classification and prediction are well-established on numerous aspects of realworld applications. One of these many aspects is to improve healthcare delivery through influencing healthcare provider decisions. This study provides a systematic review of the applications of ANN to medical applications. We have screened 87 articles from several academic databases with coverage our cross-disciplinary query to identify matches in the literature based on the combinations following keywords; Artificial Neural Networks, Medicine, Healthcare, and Applications. Our systematic review process involves searching evidence from different sections while focusing on eligibility, rationale, objectives, evaluation and limitations. Reviewed studies have targeted the use of different ANN used including multilayer perceptron, convolutional and recurrent neural networks, along with deep learning approaches. Most of these studies informed classification of diseases or decision-making process. The commonest ANN architecture in this review was found to be the multilayer perceptron within a feed forward learning approach. Interpreting ANN final models was found to be the main challenge with medical applications.en_US
dc.description.sponsorshipInst Elect & Elect Engineers,IEEE Comp Soc,eSystem Engn Soc,IEEE UK & Ireland Comp Soc Chapter,Liverpool John Moores Univ,Leeds Beckett Univ,Univ Anbaren_US
dc.identifier.doi10.1109/DeSE51703.2020.9450245
dc.identifier.endpage282en_US
dc.identifier.isbn978-1-6654-2238-3
dc.identifier.issn2161-1343
dc.identifier.scopus2-s2.0-85112523903en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage279en_US
dc.identifier.urihttps://doi.org/10.1109/DeSE51703.2020.9450245
dc.identifier.urihttps://hdl.handle.net/20.500.14619/6116
dc.identifier.wosWOS:000687851400039en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIeeeen_US
dc.relation.ispartof2020 13th International Conference On Developments in Esystems Engineering (Dese 2020)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial Neural Networksen_US
dc.subjectMedicineen_US
dc.subjectHealthcareen_US
dc.subjectApplicationsen_US
dc.titleA Systematic Review of Artificial Neural Networks in Medical Science and Applicationsen_US
dc.typeConference Objecten_US

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