Performance variability of radiomics machine learning models for the detection of clinically significant prostate cancer in heterogeneous MRI datasets-Reference-Cited by-同舟云学术

Performance variability of radiomics machine learning models for the detection of clinically significant prostate cancer in heterogeneous MRI datasets

Published:2022-11 Issue:11 Volume:12 Page:4990-5003
ISSN:2223-4292
Container-title:Quantitative Imaging in Medicine and Surgery
language:
Short-container-title:Quant Imaging Med Surg

Author:

Gresser Eva,Schachtner Balthasar,Stüber Anna Theresa,Solyanik Olga,Schreier Andrea,Huber Thomas,Froelich Matthias Frank,Magistro Giuseppe,Kretschmer Alexander,Stief Christian,Ricke Jens,Ingrisch Michael,Nörenberg Dominik

Publisher

AME Publishing Company

Subject

Radiology, Nuclear Medicine and imaging

Link

https://qims.amegroups.com/article/download/101324/pdf

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