Deep Learning Performance on Medical Image, Data and Signals

Yıl 2019, Cilt: 2 Sayı: 1, 28 - 40, 30.04.2019

Pakize Erdoğmuş

https://doi.org/10.35377/saucis.02.01.541366

Cited By: 1

Öz

Bu
çalışmada, 2009-2019 yılları arasında Tıpta derin öğrenme ile ilgili yapılmış
çalışmalar, derin öğrenmenin Tıbbı görüntü, veri ve sinyaller üzerine
başarısını gözlemlemek için araştırılmıştır. Web of Science’tan elde edilen
çalışmalar değerlendirilmiş ve atıf sayısına göre seçilmişlerdir. Çalışmalar
yayın yılı, derin ağ yapısı, kullanılan veritabanı ve değerlendirme kriterine
göre tablo haline getirilmiştir. The results have shown that the deep learning
network structures, applied on fundus images, have attained nearly %99 percent accuracy.
Sonuçlar retinal fundus görüntüleri uygulanan derin öğrenme ağ yapılarının
doğruluklarının %99’lara ulaştığını göstemektedir.  Bu aralıktaki çalışmaların çoğu radyoloji ve
nükleer tıp alanında yapılmış olsa de sonuçlar henüz %80-90 aralığında
görülmektedir. Bu sonuçlar bilgisayar destekli teşhis sistemlerinin çok yakın
bir gelecekte tam performans ile kullanılacağını göstermektedir.

Anahtar Kelimeler

edical data, deep learning, convolutional neural networks

Kaynakça

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