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"Learning Interpretable Regularized Ordinal Models from 3D Mesh Data for ..."

Yuji Zhao et al. (2022)

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DOI: 10.1007/978-3-031-17899-3_12

access: closed

type: Conference or Workshop Paper

metadata version: 2024-05-07

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  dblp key:
  - conf/miccai/ZhaoLHOPDRWCGYW22
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  persistent URL:
  - https://dblp.org/rec/conf/miccai/ZhaoLHOPDRWCGYW22
Yuji Zhao, Max A. Laansma, Eva M. van Heese, Conor Owens-Walton, Laura M. Parkes, Ines Debove, Christian Rummel, Roland Wiest, Fernando Cendes, Rachel Guimaraes, Clarissa Lin Yasuda, Jiun-Jie Wang, Tim J. Anderson, John C. Dalrymple-Alford, Tracy R. Melzer, Toni L. Pitcher, Reinhold Schmidt, Petra Schwingenschuh, Gaëtan Garraux, Mario Rango, Letizia Squarcina, Sarah Al-Bachari, Hedley C. A. Emsley, Johannes C. Klein, Clare E. Mackay, Michiel F. Dirkx, Rick C. Helmich, Francesca Assogna, Fabrizio Piras, Joanna K. Bright, Gianfranco Spalletta, Kathleen Poston, Christine Lochner, Corey T. McMillan, Daniel Weintraub, Jason Druzgal, Benjamin Newman, Odile A. van den Heuvel, Neda Jahanshad, Paul M. Thompson, Ysbrand D. van der Werf, Boris Gutman:
Learning Interpretable Regularized Ordinal Models from 3D Mesh Data for Neurodegenerative Disease Staging. MLCN@MICCAI 2022: 115-124

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