Automatic extraction of cancer registry reportable information from free-text pathology reports using multitask convolutional neural networks

Abstract

The hard parameter sharing MTCNN offers superior classification accuracy for automated coding support of pathology documents across a wide range of cancers and multiple information extraction tasks while maintaining similar training and inference time as those of a single task-specific model.