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Combining patient visual timelines with deep learning to predict mortality
BACKGROUND: Deep learning algorithms have achieved human-equivalent performance in image recognition. However, the majority of clinical data within electronic health records is inherently in a non-image format. Therefore, creating visual representations of clinical data could facilitate using cuttin...
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| I publikationen: | PLoS One |
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| Huvudupphovsmän: | , , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
Public Library of Science
2019
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6668841/ https://ncbi.nlm.nih.gov/pubmed/31365580 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0220640 |
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