title: Diagnostic Accuracy Comparison of Artificial Immune Algorithms for Primary Headaches.
abstract: The present study evaluated the diagnostic accuracy of immune system algorithms with the aim of classifying the primary types of headache that are not related to any organic etiology. They are divided into four types: migraine, tension, cluster, and other primary headaches. After we took this main objective into consideration, three different neurologists were required to fill in the medical records of 850 patients into our web-based expert system hosted on our project web site. In the evaluation process, Artificial Immune Systems (AIS) were used as the classification algorithms. The AIS are classification algorithms that are inspired by the biological immune system mechanism that involves significant and distinct capabilities. These algorithms simulate the specialties of the immune system such as discrimination, learning, and the memorizing process in order to be used for classification, optimization, or pattern recognition. According to the results, the accuracy level of the classifier used in this study reached a success continuum ranging from 95% to 99%, except for the inconvenient one that yielded 71% accuracy.
authors.affiliation: Department of Computer Engineering, Faculty of Computer and Information Science, Sakarya University, 54187 Sakarya, Turkey.
authors.forename: Ufuk
authors.initials: U
authors.lastname: Çelik
authors.affiliation: Department of Computer Engineering, Faculty of Computer and Information Science, Sakarya University, 54187 Sakarya, Turkey.
authors.forename: Nilüfer
authors.initials: N
authors.lastname: Yurtay
authors.affiliation: Department of Neurology, Faculty of Medicine, Balikesir University, 10145 Balikesir, Turkey.
authors.forename: Emine Rabia
authors.initials: ER
authors.lastname: Koç
authors.affiliation: Department of Neurology, Faculty of Medicine, Balikesir University, 10145 Balikesir, Turkey.
authors.forename: Nermin
authors.initials: N
authors.lastname: Tepe
authors.affiliation: Department of Neurology, Faculty of Medicine, Izmir University, 35530 Izmir, Turkey.
authors.forename: Halil
authors.initials: H
authors.lastname: Güllüoğlu
authors.affiliation: Department of Neurology, Faculty of Medicine, Istanbul University, 34093 Istanbul, Turkey.
authors.forename: Mustafa
authors.initials: M
authors.lastname: Ertaş
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D019295:Computational Biology; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005103:Expert Systems; D005260:Female; D051270:Headache Disorders, Primary / Q000145:classification* / Q000175:diagnosis*; D006801:Humans; D007107:Immune System; D008297:Male; D008959:Models, Neurological; D015203:Reproducibility of Results