Towards Structuring Clinical Texts: Joint Entity and Relation Extraction from Japanese Case Report Corpus

Daisaku Shibata1, Emiko Shinohara1, Kiminori Shimamoto1

  • 1Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Summary

This study demonstrates high accuracy in extracting patient symptom and diagnosis information from clinical texts using natural language processing (NLP). The machine learning models achieved excellent performance in named entity recognition (NER) and relation extraction (RE).

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