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A graph-based method for reconstructing entities from coordination ellipsis in medical text.

Chi Yuan^1,2, Yongli Wang¹, Ning Shang²

¹Department of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China.

Journal of the American Medical Informatics Association : JAMIA

|July 29, 2020

Summary

This study introduces RECEEM, a novel method for reconstructing concepts from medical coordinated elliptical expressions. RECEEM improves concept normalization accuracy across various biomedical texts, outperforming existing approaches.

Keywords:

concept normalization coordination ellipsis natural language processing

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Area of Science:

Natural Language Processing
Computational Linguistics
Medical Informatics

Background:

Coordination ellipsis in medical text poses challenges for accurate concept normalization.
Recognizing elliptical expressions referencing multiple entities is difficult, hindering information extraction.

Purpose of the Study:

To develop a generalizable method for reconstructing concepts from medical coordinated elliptical expressions.
To address the bottleneck in concept normalization caused by coordination ellipsis.

Main Methods:

Proposed a graph-based representation model and a pipeline named RECEEM.
Modules include identifying conjunct pairs, calculating coefficients using embedding models, global optimization for decomposition selection, and concept rebuilding via pathfinding.
Evaluated on 2658 coordinated elliptical expressions from biomedical literature, clinical narratives, and clinical trial eligibility criteria.

Main Results:

Achieved F1 scores of 0.862 for biomedical publications, 0.721 for clinical narratives, and 0.870 for eligibility criteria.
RECEEM outperformed two previously released methods.
Integration into NLP tools boosted F1 scores from 0.248 to 0.460 and 0.287 to 0.630 for concept mapping.

Conclusions:

RECEEM enhances concept normalization for medical coordinated elliptical expressions across diverse biomedical corpora.
The method surpasses existing approaches and improves the performance of NLP systems for coordination ellipse mapping.
The RECEEM algorithm is publicly available online.