A Novel Score Fusion Approach for Breast Cancer Diagnosis

Year 2019, Volume: 7 Issue: 3, 1045 - 1060, 31.07.2019

Erdem Yavuz , Can Eyüpoğlu

https://doi.org/10.29130/dubited.488460

Cited By: 6

Abstract

Early diagnosis of breast cancer disease is critical for
patients to recover from this disease entirely as it is a common disease all
over the world. In order to facilitate the diagnosis of the disease, medical
doctors can benefit from computer-aided expert systems. In this paper, a score
fusion method based on generalized regression neural network (GRNN) and feed
forward neural network (FFNN) has been proposed so as to split breast cancer
data samples into benign or malignant classes. The proposed method is tested on
the Wisconsin Diagnostic Breast Cancer (WDBC) dataset. The utilities of these
basic neural networks and the proposed method are examined and comparative performance
results are presented. The experimental results show that the proposed method
is promising for the diagnosis of breast cancer and may be used as an assisting
tool in the decision-making of medical professionals.

Keywords

Score Fusion, Breast Cancer Diagnosis, Neural Network, Feed Forward, Generalized Regression

Meme Kanseri Teşhisi İçin Yeni Bir Skor Füzyon Yaklaşımı

Abstract

Meme kanseri tüm dünyada yaygın bir
hastalık olması sebebiyle hastalığın erken teşhisi, hastaların bu hastalıktan
tamamen kurtulabilmeleri açısından kritik öneme sahiptir. Hastalığın teşhisini
kolaylaştırmak için tıp doktorları bilgisayar destekli uzman sistemlerden
yararlanabilmektedir. Bu çalışmada meme kanseri veri örneklerini iyi huylu veya
kötü huylu sınıflarına ayırmak için genel regresyon sinir ağı (Generalized Regression
Neural Network-GRNN) ve ileri beslemeli sinir ağı (Feed Forward Neural Network-FFNN)
temelli bir skor füzyon yöntemi önerilmiştir. Önerilen yöntem Wisconsin Teşhis
Meme Kanseri (Wisconsin Diagnostic Breast Cancer-WDBC) veri seti üzerinde test
edilmiştir. Bu iki temel ağın ve önerilen yöntemin kullanışlılığı incelenmiş ve
performans sonuçları karşılaştırmalı olarak sunulmuştur. Önerilen yöntem
sınıflandırma doğruluğu bakımından literatürde WDBC veri setini kullanarak
yapılan mevcut çalışmalar ile kıyaslanmıştır. Elde edilen deneysel sonuçlar
önerilen yöntemin, meme kanseri teşhisi için umut vadettiğini ve tıp
uzmanlarının hastalığa ilişkin karar vermelerinde yardımcı bir araç olarak
kullanılabileceğini göstermektedir. 

Keywords

Skor Füzyon, Meme Kanseri Teşhisi, Sinir Ağı, İleri Besleme, Genel Regresyon

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