KU AIGEN ICL EDI@BC8 Track 3: Advancing Phenotype Named Entity Recognition and Normalization for Dysmorphology Phys- ical Examination Reports
Year: 2023
Type: preprint
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. This article is part of the Proceedings of the BioCreative VIII Challenge and Workshop: Curation and Evaluation in the era of Generative Models.
Source: arXiv (Cornell University)
Authors: Kim, Hajung, Kim, Chanhwi, Sohn, Jiwoong, Beck, Tim, Rei, Marek, Kim, Sunkyu, Simpson, T. Ian, Posma, Joram M., Lain, Antoine, Sung, Mujeen, Kang, Jaewoo
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Funders: Government of the United Kingdom, UK Research and Innovation, European Commission, National Research Foundation, Korea Health Industry Development Institute, National Research Foundation of Korea, Ministry of Science and ICT, South Korea, HORIZON EUROPE Framework Programme, School of Informatics, University of Edinburgh, Institute for Information and Communications Technology Promotion
OpenAlex ID: W4406549390