Deep learning predicts epidermal growth factor receptor mutation subtypes in lung adenocarcinoma.PURPOSE
 This study aimed to explore the predictive ability of deep learning (DL) for the common epidermal growth factor receptor (EGFR) mutation subtypes in patients with lung adenocarcinoma.



Deep learning
In the training set, an 18-layer convolutional neural network (CNN) and fivefold cross-validation strategy were used to establish a CNN model. 
Convolutional neural network (CNN)
Grad-weighted class activation mapping (Grad-CAM) technology was used for the visual interpretation of the CNN model. 
Grad-weighted class activation mapping (Grad-CAM)