  Event extraction is an important work of medical text processing. According
to the complex characteristics of medical text annotation, we use the
end-to-end event extraction model to enhance the output formatting information
of events. Through pre training and fine-tuning, we can extract the attributes
of the four dimensions of medical text: anatomical position, subject word,
description word and occurrence state. On the test set, the accuracy rate was
0.4511, the recall rate was 0.3928, and the F1 value was 0.42. The method of
this model is simple, and it has won the second place in the task of mining
clinical discovery events (task2) in the Chinese electronic medical record of
the seventh China health information processing Conference (chip2021).
