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Reinforcement learning using Deep [Formula: see text] networks and [Formula: see text] learning accurately localizes brain tumors on MRI with very small training sets
BACKGROUND: Supervised deep learning in radiology suffers from notorious inherent limitations: 1) It requires large, hand-annotated data sets; (2) It is non-generalizable; and (3) It lacks explainability and intuition. It has recently been proposed that reinforcement learning addresses all three of...
Autores principales: | Stember, J. N., Shalu, H. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9784281/ https://www.ncbi.nlm.nih.gov/pubmed/36564724 http://dx.doi.org/10.1186/s12880-022-00919-x |
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