Performance of neural networks and heuristic models for disease prediction from liver enzymes: Application to biochemistry device output

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dc.contributor.authorÇavga, Seyit Hamza
dc.date.accessioned2024-09-11T19:52:42Z
dc.date.available2024-09-11T19:52:42Z
dc.date.issued2024
dc.departmentİstanbul Gelişim Üniversitesien_US
dc.description.abstractIn the application of decision-making systems in the field of healthcare, with advancing technology, the outputs of direct analysis devices have become usable. As the dataset becomes richer, the accuracy of models also increases. The parameters of the dataset used in this study contain raw data closer to real conditions in terms of both quantity and quality compared to previous studies. When examining the models established to identify liver diseases, it is observed that besides the model performance, the performance of experts also affects due to the use of parameters containing expert opinions. The data set used in this study did not include subjective data other than class values, and only expert opinions were used in training the model. Thus, the model performance will be less dependent on the dataset compared to other studies. Real-life data has been worked on with different models to see which structures are better. Artificial neural networks and particle swarm optimization methods were trained to solve the classification problem and results were analyzed by testing with training and test data in the study.en_US
dc.identifier.doi10.17341/gazimmfd.1268957
dc.identifier.endpage2270en_US
dc.identifier.issn1300-1884
dc.identifier.issn1304-4915
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85195586645en_US
dc.identifier.startpage2263en_US
dc.identifier.urihttps://doi.org/10.17341/gazimmfd.1268957
dc.identifier.urihttps://hdl.handle.net/11363/8010
dc.identifier.volume39en_US
dc.identifier.wosWOS:001265086400001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isotren_US
dc.publisherGazi Univ, Fac Engineering Architectureen_US
dc.relation.ispartofJournal of The Faculty of Engineering And Architecture of Gazi Universityen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz20240903_Gen_US
dc.subjectLiver diseasesen_US
dc.subjectArtificial neural networksen_US
dc.subjectParticle swarm optimizationen_US
dc.subjectLogistic regressionen_US
dc.titlePerformance of neural networks and heuristic models for disease prediction from liver enzymes: Application to biochemistry device outputen_US
dc.typeArticleen_US

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