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Training a Convolutional Neural Network with Terminology Summarization Data Improves SNOMED CT Enrichment
As a step toward learning to automatically insert new concepts into a large biomedical ontology, we are studying the easier problem of automatically verifying that an IS-A link should exist between a new child concept and an existing parent concept. We are using a Convolutional Neural Network, a pow...
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| Izdano u: | AMIA Annu Symp Proc |
|---|---|
| Glavni autori: | , , , |
| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
American Medical Informatics Association
2020
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| Teme: | |
| Online pristup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7153126/ https://ncbi.nlm.nih.gov/pubmed/32308894 |
| Oznake: |
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