Quantitative study demonstrates Named Entity Recognition improves clinical decision support in breast cancer EHRs, indicating substantial benefits for treatment outcomes.
Key Points
The proposed model enhances clinical decision support for breast cancer, improving accuracy in medical entity recognition.
With a precision of 87.24% and an F1-score of 86.93%, the model significantly outperforms baseline approaches.
This observational analysis incorporates the ChCancerBERT model, utilizing specialized cancer corpora for effective NER in Chinese EHRs.
The findings highlight the potential for improved entity recognition in cancer records, emphasizing the importance of domain-specific data.