Decision tree application to reduce incorrect diagnosis in symptoms of jaundice

Basit Öğe Kaydı
dc.authorscopusid26657059400
dc.authorscopusid7003327596
dc.contributor.authorTopaloğlu M.
dc.contributor.authorSur H.
dc.date.accessioned2024-06-12T10:29:02Z
dc.date.available2024-06-12T10:29:02Z
dc.date.issued2015
dc.description.abstractObjective: In this study, decision support system was created to diagnose jaundice and to reduce incorrect diagnosis of jaundice. The study was conducted to help physicians to diagnose jaundice. Material and Method: In this study, data of 300 patients diagnosed with jaundice was taken from a health institution. All tests performed for the patients were included in the study from the beginning of complaints to the final diagnosis. To this end, data of patients previously diagnosed with jaundice were collected in the database, edited, and organized. Training kit was created with this organized data. Then data mining methods applied to agreed algorithms and the decision tree models were created from the results. Decision trees were created by using C5.0 and J48 algorithms. The purpose of the decision tree is to reach 16 illness using 21 qualities. Results: In decision support system are two different decision trees and separate pages designed according to expert opinion. The purpose is not to create decision support system with a single decision tree, but to identify the disease with three different opinions. Trimming operations were carried out in trees created with the algorithms. With most appropriate trimming 16 illnesses were reached with 100% accuracy. Conclusion: Decision support system helping the physicians be able to use the decision trees in clinic environment easily has been developed. This study was conducted with the aim of preventing time loss in diagnosis phase and helping the physicians diagnose jaundice accurately. © Nobel İlaç AŞ.en_US
dc.identifier.endpage73en_US
dc.identifier.issn1305-2381
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-84952901756en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage64en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14551/17549
dc.identifier.volume11en_US
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherNobelmedicusen_US
dc.relation.ispartofNobel Medicusen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDecision Trees; Differential Diagnosis; Expert Opinion; Jaundiceen_US
dc.subjectAlgorithm; Article; Clinical Decision Making; Data Mining; Decision Support System; Decision Tree; Diagnostic Accuracy; Diagnostic Error; Human; Jaundice; Major Clinical Studyen_US
dc.titleDecision tree application to reduce incorrect diagnosis in symptoms of jaundiceen_US
dc.title.alternativeSarilik semptomlarinda yanliş teş hisi azaltmak için karar ağaci uygulamasien_US
dc.typeArticleen_US

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