KU AIGEN ICL EDI@BC8 Track 3: Advancing phenotype named entity recognition and normalization for dysmorphology physical examination reports
File(s)
Published version
Author(s)
Type
Conference Paper
Abstract
The objective of BioCreative8 Track 3 is to extract phenotypic key medical findings embedded within EHR texts and subsequently normalize these findings to their Human Phenotype Ontology (HPO) terms. However, the presence of diverse surface forms in phenotypic findings makes it challenging to accurately normalize them to the correct HPO terms. To address this challenge, we explored various models for named entity recognition and implemented data augmentation techniques such as synonym marginalization to enhance the normalization step. Our pipeline resulted in an exact extraction and normalization F1 score 2.6% higher than the mean score of all submissions received in response to the challenge. Furthermore, in terms of the normalization F1 score, our approach surpassed the average performance by 1.9%. These findings contribute to the advancement of automated medical data extraction and normalization techniques, showcasing potential pathways for future research and application in the biomedical domain.
Date Issued
2023-11-12
Date Acceptance
2023-11-11
Citation
Proceedings of the BioCreative VIII Challenge and Workshop: Curation and Evaluation in the era of Generative Models, 2023, pp.1-5
Publisher
Zenodo
Start Page
1
End Page
5
Journal / Book Title
Proceedings of the BioCreative VIII Challenge and Workshop: Curation and Evaluation in the era of Generative Models
Copyright Statement
© 2023 The Author(s). This paper is available open access under a CC-BY licence (https://creativecommons.org/licenses/by/4.0/)
License URL
Identifier
https://zenodo.org/records/10104804
Source
AMIA 2023 Annual Symposium
Publication Status
Published
Start Date
2023-11-11
Finish Date
2023-11-15
Coverage Spatial
New Orleans, USA