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Journal of Applied Statistics Volume 50, 2023 - Issue 3: Statistical Approaches for Big Data and Machine Learning
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Articles

Multi-resolution super learner for voxel-wise classification of prostate cancer using multi-parametric MRI

Jin Jina Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USACorrespondence[email protected]
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,
Lin Zhangb Devision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USAView further author information
,
Ethan Lengc Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USAView further author information
,
Gregory J. Metzgerd Department of Radiology, University of Minnesota, Minneapolis, MN, USAView further author information
&
Joseph S. Koopmeinersb Devision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USAView further author information
Pages 805-826 | Received 09 Jul 2020, Accepted 05 Dec 2021, Published online: 17 Dec 2021

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Yichuan Zhao, Chi-Hua Chen, Feng Feng & Dragan Pamucar. (2023) Editorial to the special issue: Statistical Approaches for Big Data and Machine Learning. Journal of Applied Statistics 50:3, pages 451-455.
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Articles from other publishers (2)

Rola Saouaf, Yibin Xie, Sungjin Kim, Yaniv Raphael, Christopher Nguyen, Daniel Luthringer, Timothy J. Daskivich, Eric Lo, Mourad Tighiouart, Debiao Li & Hyung L. Kim. (2024) High-resolution Diffusion-weighted Imaging to Detect Changes in Tumor Size and ADC, and Predict Adverse Biopsy Histology during Prostate Cancer Active Surveillance. Cancer Research Communications 4:3, pages 938-945.
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Logeshwaran Jaganathan, Saurabh Singhal & Amit Garg. (2023) MultiResolution 3D Magnetic Resonance Imaging Analysis for Prostate Cancer Imaging. MultiResolution 3D Magnetic Resonance Imaging Analysis for Prostate Cancer Imaging.

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