Multimodal learning for temporal relation extraction in clinical texts.

Journal: Journal of the American Medical Informatics Association : JAMIA

Published Date: May 20, 2024

Abstract

OBJECTIVES: This study focuses on refining temporal relation extraction within medical documents by introducing an innovative bimodal architecture. The overarching goal is to enhance our understanding of narrative processes in the medical domain, particularly through the analysis of extensive reports and notes concerning patient experiences.

Authors

Timotej Knez

Faculty of Computer and Information Science, University of Ljubljana, Ljubljana 1000, Slovenia.
Slavko Žitnik

Faculty of Computer and Information Science, University of Ljubljana, Ljubljana 1000, Slovenia.

Keywords

Data Mining Datasets as Topic Electronic Health Records Humans Information Storage and Retrieval Machine Learning Narration Natural Language Processing

External Resources

View on PubMed Access via DOI PubMed (38531680)

Multimodal learning for temporal relation extraction in clinical texts.

Abstract

Authors

Keywords

External Resources

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