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A deep-learning-based unsupervised model on esophageal manometry using variational autoencoder
High-resolution manometry (HRM) is the primary method for diagnosing esophageal motility disorders and its interpretation and classification are based on variables (features) from data of each swallow. Modeling and learning the semantics directly from raw swallow data could not only help automate th...
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| Published in: | Artif Intell Med |
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| Main Authors: | , , , , , , |
| Format: | Artigo |
| Language: | Inglês |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7901248/ https://ncbi.nlm.nih.gov/pubmed/33581826 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.artmed.2020.102006 |
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