Protocol for the automatic extraction of epidemiological information via a pre-trained language model

The lack of systems to automatically extract epidemiological fields from open -ac-cess COVID-19 cases restricts the timeliness of formulating prevention measures. Here we present a protocol for using CCIE, a COVID-19 Cases Information Extraction system based on the pre-trained language model.1 We describe steps for preparing supervised training data and executing python scripts for named entity recognition and text category classification. We then detail the use of ma-chine evaluation and manual validation to illustrate the effectiveness of CCIE.For complete details on the use and execution of this protocol, please refer to Wang et al.2

Automated summary

This article presents a protocol for using CCIE, a COVID-19 Cases Information Extraction system based on the pre-trained language model. The protocol includes steps for preparing training data, executing Python scripts for entity recognition and text classification, and using machine evaluation and manual validation to validate the effectiveness of CCIE. For complete details, please refer to Wang et al.