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Deterministic small‐scale undulations of image‐based risk predictions from the deep learning of lung tumors in motion
INTRODUCTION: Deep learning (DL) models that use medical images to predict clinical outcomes are poised for clinical translation. For tumors that reside in organs that move, however, the impact of motion (i.e., degenerated object appearance or blur) on DL model accuracy remains unclear. We examine t...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
John Wiley and Sons Inc.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10115400/ https://www.ncbi.nlm.nih.gov/pubmed/35962958 http://dx.doi.org/10.1002/mp.15869 |