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DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms
Effective patient care mandates rapid, yet accurate, diagnosis. With the abundance of non-invasive diagnostic measurements and electronic health records (EHR), manual interpretation for differential diagnosis has become time-consuming and challenging. This has led to wide-spread adoption of AI-power...
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| Publicado en: | Sci Rep |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Nature Publishing Group UK
2020
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7532141/ https://ncbi.nlm.nih.gov/pubmed/33009423 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-73126-9 |
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