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Using deep learning–derived image features in radiologic time series to make personalised predictions: proof of concept in colonic transit data
OBJECTIVES: Siamese neural networks (SNN) were used to classify the presence of radiopaque beads as part of a colonic transit time study (CTS). The SNN output was then used as a feature in a time series model to predict progression through a CTS. METHODS: This retrospective study included all patien...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244854/ https://www.ncbi.nlm.nih.gov/pubmed/37284869 http://dx.doi.org/10.1007/s00330-023-09769-9 |