TY  - JOUR
T1  - A Convolutional Neural Network Application for Predicting the Locating of Squamous Cell Carcinoma in the Lung
AU  - Akıncı, Tahir Cetin
AU  - Noğay, H. Selçuk
PY  - 2018
DA  - July
DO  - 10.17694/bajece.455132
JF  - Balkan Journal of Electrical and Computer Engineering
PB  - MUSA YILMAZ
WT  - DergiPark
SN  - 2147-284X
SP  - 207
EP  - 210
VL  - 6
IS  - 3
LA  - en
AB  - Squamouscell carcinoma, one of the most common types of lung cancer types, usuallyoccurs in the middle, right or left bronchi. Squamous cell carcinoma can beeasily detected by imaging methods to determine the location within thelung.  However, rarely the location ofsome tumor types cannot be determined. In this case, it may be delayed to obtain the results ofthe assay such as biopsy. This possible delay also means delayed diagnosis anddelayed start of treatment. In order to solve this problem, it is possible toperform applications with machine learning methods. In this study,convolutional neural networks method was used to determine the location ofcancerous tumor in squamous cell carcinoma of lung. With the designed convolutional neural network model,squamous cell carcinoma tumor location in lung cancer was estimated with anaccuracy rate close to 100%.
KW  - Convolutional neuran networks
KW  - squamous cell carcinoma
KW  - classification
KW  - estimation
KW  - accuracy rate
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UR  - https://doi.org/10.17694/bajece.455132
L1  - https://dergipark.org.tr/en/download/article-file/526758
ER  -