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Improving Prediction of Low-Prior Clinical Events with Simultaneous General Patient-State Representation Learning
Low-prior targets are common among many important clinical events, which introduces the challenge of having enough data to support learning of their predictive models. Many prior works have addressed this problem by first building a general patient-state representation model, and then adapting it to...
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| Publicado no: | Artif Intell Med Conf Artif Intell Med (2005-) |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8301230/ https://ncbi.nlm.nih.gov/pubmed/34308430 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-77211-6_57 |
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