Patient-specific uncertainty and bias quantification of non-transparent convolutional neural network model through knowledge distillation and Bayesian deep learning.

Gong, Hao; Yu, Lifeng; Leng, Shuai; Hsieh, Scott S; Fletcher, Joel G; McCollough, Cynthia H

Gong, Hao; Yu, Lifeng; Leng, Shuai; Hsieh, Scott S; Fletcher, Joel G; McCollough, Cynthia H.

Afiliación

Gong H; Department of Radiology, Mayo Clinic, Rochester, MN, 55901, USA.
Yu L; Department of Radiology, Mayo Clinic, Rochester, MN, 55901, USA.
Leng S; Department of Radiology, Mayo Clinic, Rochester, MN, 55901, USA.
Hsieh SS; Department of Radiology, Mayo Clinic, Rochester, MN, 55901, USA.
Fletcher JG; Department of Radiology, Mayo Clinic, Rochester, MN, 55901, USA.
McCollough CH; Department of Radiology, Mayo Clinic, Rochester, MN, 55901, USA.

Proc SPIE Int Soc Opt Eng ; 124632023 Feb.

Article en En | MEDLINE | ID: mdl-37063493

Palabras clave

Bayesian neural network; Deep learning; bias; knowledge distillation; uncertainty; x-ray CT

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Proc SPIE Int Soc Opt Eng Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

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