Research on Integrity Classification Algorithm for Adverse Events in Infant Incubators Based on Bert BiGRU Model
This study aims to improve the classification efficiency and accuracy of adverse event reports in infant incubators,using a model that integrates Bert model,bidirectional gated recurrent unit(BiGRU),and multi head attention mechanism(Attention).We conducted a detailed analysis of the report using a dataset provided by a certain province and successfully distinguished between complete and incomplete reports.The experimental results showed that the proposed Bert BiGRU ATT model achieved an average F1 score of 90.37%in integrity classification tasks,significantly better than traditional models,demonstrating its effectiveness in text processing in specific domains.The application of this model will improve the usability and accuracy of reports,help prevent medical accidents,reduce patient injuries,and alleviate the workload of medical professionals.
adverse events of medical devicesBert—BiGRUdeep learningintelligent classification
万方数据
维普
