Automated AJCC (7th edition) staging of non-small cell lung cancer (NSCLC) using deep convolutional neural network (CNN) and recurrent neural network (RNN).

ABSTRACT:

Purpose

A large chunk of lung cancers are of the type non-small cell lung cancer (NSCLC). Both the treatment planning and patients' prognosis depend greatly on factors like AJCC staging which is an abstraction over TNM staging. Many significant efforts have so far been made towards automated staging of NSCLC, but the groundbreaking application of a deep neural networks (DNNs) is yet to be observed in this domain of study. DNN is capable of achieving higher level of accuracy than the traditional artificial neural networks (ANNs) as it uses deeper layers of convolutional neural network (CNN). The objective of the present study is to propose a simple yet fast CNN model combined with recurrent neural network (RNN) for automated AJCC staging of NSCLC and to compare the outcome with a fe

SUBMITTER: Moitra D 

PROVIDER: S-EPMC6667593 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature