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More slices, less truth: effects of different test-set design strategies for magnetic resonance image classification
AIM: To assess the effects of different test-set design strategies for magnetic resonance (MR) image classification using deep learning. METHODS: Error rates in 10 experimental settings were assessed. The performance of pretrained models and data augmentation were examined as possible contributing f...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Croatian Medical Schools
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9468729/ https://www.ncbi.nlm.nih.gov/pubmed/36046934 http://dx.doi.org/10.3325/cmj.2022.63.370 |