Decision tree application to reduce incorrect diagnosis in symptoms of jaundice
Küçük Resim Yok
Tarih
2015
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Nobelmedicus
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Objective: 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.
Açıklama
Anahtar Kelimeler
Decision Trees; Differential Diagnosis; Expert Opinion; Jaundice, Algorithm; Article; Clinical Decision Making; Data Mining; Decision Support System; Decision Tree; Diagnostic Accuracy; Diagnostic Error; Human; Jaundice; Major Clinical Study
Kaynak
Nobel Medicus
WoS Q Değeri
Scopus Q Değeri
Q4
Cilt
11
Sayı
3
