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...

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Detalles Bibliográficos
Autores principales: Stember, J. N., Shalu, H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research Article
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

Internet

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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