Investigating a Domain Adaptation Approach for Integrating Different Measurement Instruments in a Longitudinal Clinical Registry.

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作者： Maren,Hackenberg ^[1] ; Michelle,Pfaffenlehner ^[1] ; Max,Behrens ^[1] ; Astrid,Pechmann ^[2] ; Janbernd,Kirschner ^[2] ; Harald,Binder ^[3]

作者单位： Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.;Freiburg Center for Data Analysis and Modeling, University of Freiburg, Freiburg, Germany. ^[1] Department of Neuropediatrics and Muscle Disorders, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany. ^[2] Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.;Freiburg Center for Data Analysis and Modeling, University of Freiburg, Freiburg, Germany.;Centre for Integrative Biological Signalling Studies (CIBSS), University of Freiburg, Freiburg, Germany. ^[3]

关键词 deep learning domain adaptation dynamic modeling latent representation

主题词人类(Humans);登记(Registries);纵向研究(Longitudinal Studies);生物测量学(Biometry);肌萎缩, 脊髓性(Muscular Atrophy, Spinal);模型, 统计学(Models, Statistical)

DOI 10.1002/bimj.70023

PMID 39698740

发布时间 2025-01-04

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