Flat-Lattice-CNN: A model for Chinese medical-named-entity recognition

Experimental results show an improved performance in the task of recognizing medical-named entities on all evaluation datasets, especially on CTDD with a 2.3% increase in F1 score. The proposed Flat-Lattice-CNN model effectively addresses the challenges posed by long and multiword syntactic patterns in medical-named entities, offering improved recognition accuracy and demonstrating the potential for enhancing medical-named-entity recognition in internet-based healthcare dialogues.