A Survey in Deep Convolutional Neural Networks for Diagnosis of Dieases

Creative Commons License

Noğay H. S., Akıncı T. Ç., Önal Ş. E.

BdKCSE’xx2017 International Conference on7-8 December 2017, Sofia, Bulgaria Big Data, Knowledge and Control Systems Engineering, Sofija, Bulgaristan, 7 - 08 Aralık 2017, ss.3-11, (Tam Metin Bildiri)

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Basıldığı Şehir: Sofija
  • Basıldığı Ülke: Bulgaristan
  • Sayfa Sayıları: ss.3-11
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Bursa Uludağ Üniversitesi Adresli: Hayır

Özet

Abstract: Before designing a deep convolutional neural network (DCNN), it is necessary to preliminarily investigate the decisions that need to be made about design processes. When designing a DCNN for medical diagnosis, specific information about the disease itself is needed. In this study, the stages of designing a DCNN model that can be used to diagnose diseases have been investigated and information affecting decision-making processes at each stage has been identified

Keywords: Convolutional Neural Networks, Deep Learning, Artificial Intelligence