ArticleProceedings. IEEE International Conference on Bioinformatics and Biomedicine2021
Data Normalization Improves Semantic Annotation - a Case Study of Rare Disease Name Annotation.
Article in Proceedings. IEEE International Conference on Bioinformatics and Biomedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Integrative Rare Disease Profile Creation via NormMap to Advance Rare Disease Research.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2022Article
- Semantic Annotation of NIH Funding Data for Supporting Rare Disease Research.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2022Article
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3 authors.
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Abstract
Despite the individually low prevalence of rare diseases, they collectively constitute a big challenge to human health. Accurate annotation of rare diseases in biomedical data through natural language processing (NLP) could be instrumental in biomedical informatics research. Herein, we propose a data normalization-based annotation approach, complementary to the popular biomedical data annotation tool named MetaMap, for disease annotation from biomedical data in free text.
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Registered trials
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