Artificial neural network analysis for prediction of headache prognosis in elderly patients

KALEAĞASI, Hakan; Özge, Aynur; HELVACI, Sema; TAŞDELEN, BAHAR

Artificial neural network analysis for prediction of headache prognosis in elderly patients

Bahar TAŞDELEN, (Mersin Üniversitesi, Tıp Fakültesi, Biyoistatistik Anabilim Dalı, Mersin, Türkiye)

Sema HELVACI, (Mersin Üniversitesi, Tıp Fakültesi, Biyoistatistik Anabilim Dalı, Mersin, Türkiye)

Hakan KALEAĞASI, (Mersin Üniversitesi, Tıp Fakültesi, Nöroloji Anabilim Dalı, Mersin, Türkiye)

Aynur ÖZGE (Mersin Üniversitesi, Tıp Fakültesi, Nöroloji Anabilim Dalı, Mersin, Türkiye)

Turkish Journal of Medical Sciences

2 0

Yıl: 2009 Cilt: 39 Sayı: 1 Sayfa Aralığı: 5 - 12 Metin Dili: Türkçe İndeks Tarihi: 29-07-2022

Artificial neural network analysis for prediction of headache prognosis in elderly patients

Öz:

Amaç: Çalışmanın amacı, sinir ağlarının takip süresi içinde başağrısı tam olarak iyileşen yaşlı hastaları belirleyerek sınıflandırma performansını incelemektir. Gereç ve Yöntem: Yaşlı hastalarda başağrısı prognozunu tahmin etmek için, en yaygın sinir ağı olan çok tabakalı perseptron kullanıldı. Veri seti, eğitim ve test setlerine ayrılarak, öğrenme algoritması olarak geriye yayılım algoritması kullanıldı. Tedavinin 20, 40 ve 60. aylarında hastalardaki tam iyileşmeyi tahmin etmek için kullanılan modellerin doğruluk dereceleri ROC eğrileri altında kalan alanlar kullanılarak değerlendirildi. Bulgular: Sınıflandırma sonuçları, sinir ağı modellerinin hem eğitim hem de test aşamalarında yüksek performansa dahip olduklarını göstermiştir. Ayrıca, her tedavi periyodu için elde edilen ROC eğrisi altında kalan alanlar, tam iyileşmeyi tahmin etmek için kullanılan modellerin doğruluk derecelerinin 0.75-0.90 aralığında olduğunu göstermiştir. Sonuç: Gruplandırılmış sağkalım verileri için sinir ağı modeli prognostik model olarak kullanılabilir. Eğer bir hastalığın görülme sıklığı düşük ise, modelin gerçek hastaları tayin etme gücü de (duyarlılığı) düşük olacaktır.

Anahtar Kelime: Yaşlı Seyir Sinir ağları (Bilgisayar) Baş ağrısı Sinir ağı

Konular: Cerrahi

Yaşlı hastalarda baş ağrısı prognozunun tahmini için yapay sinir ağları analizi

Öz:

Aim: To investigate the ability of neural networks to detect and classify the complete improvement of headache in elderly patients during the follow- up period. Materials and Methods: The multilayer perceptron (MLP), which is the most common neural network, was used to predict prognosis of headache in elderly patients. The data set was divided into training and test sets, and back-propagation algorithm was used as the learning algorithm. The accuracies of the models to predict completely improved patients at the end of 20, 40, and 60 months of follow-up were evaluated by means of the areas under the receiver operating characteristic (ROC) curves. Results: The classification results showed the neural network models had good performance in both training and test phases. In addition, the areas under the ROC curve for each period showed that the accuracies of the models to predict the completely improved patients were in the interval of 0.75-0.90. Conclusions: Neural network model for grouped survival data can be used as a prognostic model. If the prevalence of a disease is low, the sensitivity of the model for detection of the patients with disease will be low.

Anahtar Kelime: Neural Networks (Computer) Headache Nerve Net Aged Prognosis

Konular: Cerrahi

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık

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APA	TAŞDELEN B, HELVACI S, KALEAĞASI H, Özge A (2009). Artificial neural network analysis for prediction of headache prognosis in elderly patients. , 5 - 12.
Chicago	TAŞDELEN BAHAR,HELVACI Sema,KALEAĞASI Hakan,Özge Aynur Artificial neural network analysis for prediction of headache prognosis in elderly patients. (2009): 5 - 12.
MLA	TAŞDELEN BAHAR,HELVACI Sema,KALEAĞASI Hakan,Özge Aynur Artificial neural network analysis for prediction of headache prognosis in elderly patients. , 2009, ss.5 - 12.
AMA	TAŞDELEN B,HELVACI S,KALEAĞASI H,Özge A Artificial neural network analysis for prediction of headache prognosis in elderly patients. . 2009; 5 - 12.
Vancouver	TAŞDELEN B,HELVACI S,KALEAĞASI H,Özge A Artificial neural network analysis for prediction of headache prognosis in elderly patients. . 2009; 5 - 12.
IEEE	TAŞDELEN B,HELVACI S,KALEAĞASI H,Özge A "Artificial neural network analysis for prediction of headache prognosis in elderly patients." , ss.5 - 12, 2009.
ISNAD	TAŞDELEN, BAHAR vd. "Artificial neural network analysis for prediction of headache prognosis in elderly patients". (2009), 5-12.

APA	TAŞDELEN B, HELVACI S, KALEAĞASI H, Özge A (2009). Artificial neural network analysis for prediction of headache prognosis in elderly patients. Turkish Journal of Medical Sciences, 39(1), 5 - 12.
Chicago	TAŞDELEN BAHAR,HELVACI Sema,KALEAĞASI Hakan,Özge Aynur Artificial neural network analysis for prediction of headache prognosis in elderly patients. Turkish Journal of Medical Sciences 39, no.1 (2009): 5 - 12.
MLA	TAŞDELEN BAHAR,HELVACI Sema,KALEAĞASI Hakan,Özge Aynur Artificial neural network analysis for prediction of headache prognosis in elderly patients. Turkish Journal of Medical Sciences, vol.39, no.1, 2009, ss.5 - 12.
AMA	TAŞDELEN B,HELVACI S,KALEAĞASI H,Özge A Artificial neural network analysis for prediction of headache prognosis in elderly patients. Turkish Journal of Medical Sciences. 2009; 39(1): 5 - 12.
Vancouver	TAŞDELEN B,HELVACI S,KALEAĞASI H,Özge A Artificial neural network analysis for prediction of headache prognosis in elderly patients. Turkish Journal of Medical Sciences. 2009; 39(1): 5 - 12.
IEEE	TAŞDELEN B,HELVACI S,KALEAĞASI H,Özge A "Artificial neural network analysis for prediction of headache prognosis in elderly patients." Turkish Journal of Medical Sciences, 39, ss.5 - 12, 2009.
ISNAD	TAŞDELEN, BAHAR vd. "Artificial neural network analysis for prediction of headache prognosis in elderly patients". Turkish Journal of Medical Sciences 39/1 (2009), 5-12.