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Machine learning prediction of liver stiffness using clinical and T2-weighted MRI radiomic data

L He, H Li, JA Dudley, TC Maloney… - American Journal of …, 2019 - Am Roentgen Ray Soc
OBJECTIVE. The purpose of this study is to develop a machine learning model to
categorically classify MR elastography (MRE)–derived liver stiffness using clinical and …
被引用次数：47 相关文章

Machine Learning Prediction of Liver Stiffness Using Clinical and T2-Weighted MRI Radiomic Data.

L He, H Li, JA Dudley, TC Maloney… - … . American Journal of …, 2019 - europepmc.org
OBJECTIVE. The purpose of this study is to develop a machine learning model to
categorically classify MR elastography (MRE)-derived liver stiffness using clinical and …

Machine Learning Prediction of Liver Stiffness Using Clinical and T2-Weighted MRI Radiomic Data

L He, H Li, JA Dudley, TC Maloney… - AJR. American …, 2019 - pubmed.ncbi.nlm.nih.gov
OBJECTIVE. The purpose of this study is to develop a machine learning model to
categorically classify MR elastography (MRE)-derived liver stiffness using clinical and …

[引用][C] Machine Learning Prediction of Liver Stiffness Using Clinical and T2-Weighted MRI Radiomic Data

L He, H Li, JA Dudley, TC Maloney, SL Brady… - American Journal of …, 2019 - cir.nii.ac.jp
Machine Learning Prediction of Liver Stiffness Using Clinical and T2-Weighted MRI Radiomic
Data | CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 検索 …