  We investigated the ability of deep learning models for imaging based HPV
status detection. To overcome the problem of small medical datasets we used a
transfer learning approach. A 3D convolutional network pre-trained on sports
video clips was fine tuned such that full 3D information in the CT images could
be exploited. The video pre-trained model was able to differentiate
HPV-positive from HPV-negative cases with an area under the receiver operating
characteristic curve (AUC) of 0.81 for an external test set. In comparison to a
3D convolutional neural network (CNN) trained from scratch and a 2D
architecture pre-trained on ImageNet the video pre-trained model performed
best.
