Automatic genetic phenotype normalization from dysmorphology physical examinations: an overview of the BioCreative VIII-Task 3 competition
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
We present here an overview of the BioCreative VIII Task 3 competition, which called for the development of state-of-the-art approaches to automatic normalization of observations noted by physicians in dysmorphology physical examinations to the Human Phenotype Ontology (HPO). We made available for the task 3136 deidentified and manually annotated observations extracted from electronic health records of 1652 paediatric patients at the Children’s Hospital of Philadelphia. This task is challenging due to the discontinuous, overlapping, and descriptive mentions of the observations corresponding to HPO terms, severely limiting the performance of straightforward strict matching approaches. Ultimately, an effective automated solution to the task will facilitate computational analysis that could uncover novel correlations and patterns of observations in patients with rare genetic diseases, enhance our understanding of known genetic conditions, and even identify previously unrecognized conditions. A total of 20 teams registered, and 5 teams submitted their predictions. We summarize the corpus, the competing systems approaches, and their results. The top system used a pre-trained large language model and achieved a 0.82 F1 score, which is close to human performance, confirming the impact that recent advances in natural language processing can have on tasks such as this. The post-evaluation period of the challenge, at https://codalab.lisn.upsaclay.fr/competitions/11351, will be open for submissions for at least 18 months past the end of the competition. Database URL: https://codalab.lisn.upsaclay.fr/competitions/11351
Date Issued
2025-09-24
Date Acceptance
2025-07-07
Citation
Database : the journal of biological databases and curation, 2025, 2025
ISSN
1758-0463
Publisher
Oxford University Press
Journal / Book Title
Database : the journal of biological databases and curation
Volume
2025
Copyright Statement
© The Author(s) 2025. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/40996704
PII: 8263853
Subjects
Life Sciences & Biomedicine
Mathematical & Computational Biology
Science & Technology
Publication Status
Published
Coverage Spatial
England
Article Number
baaf051
Date Publish Online
2025-09-24