Benchmarking the generalizability of brain age models: Challenges posed by scanner variance and prediction bias-Reference-Cited by-同舟云学术

Benchmarking the generalizability of brain age models: Challenges posed by scanner variance and prediction bias

Published:2022-11-08 Issue:3 Volume:44 Page:1118-1128
ISSN:1065-9471
Container-title:Human Brain Mapping
language:en
Short-container-title:Human Brain Mapping

Author:

Jirsaraie Robert J.¹,Kaufmann Tobias²³,Bashyam Vishnu⁴,Erus Guray⁴,Luby Joan L.⁵,Westlye Lars T.³⁶⁷^ORCID,Davatzikos Christos⁴,Barch Deanna M.⁸,Sotiras Aristeidis⁹^ORCID

Affiliation:

1. Division of Computational and Data Sciences Washington University in St. Louis St. Louis Missouri USA

2. Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health University of Tübingen Tübingen Germany

3. Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine University of Oslo Oslo Norway

4. Center for Biomedical Image Computing and Analytics, Department of Radiology University of Pennsylvania Philadelphia Pennsylvania USA

5. Department of Psychiatry Washington University in St. Louis St. Louis Missouri USA

6. Department of Psychology University of Oslo Oslo Norway

7. KG Jebsen Centre for Neurodevelopmental Disorders University of Oslo Oslo Norway

8. Department of Psychological & Brain Sciences Washington University in St. Louis St. Louis Missouri USA

9. Department of Radiology Washington University School of Medicine in St. Louis St. Louis Missouri USA

Funder

National Institute of Mental Health

National Science Foundation

Publisher

Wiley

Subject

Neurology (clinical),Neurology,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology,Anatomy

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/hbm.26144

Reference44 articles.

1. Deep Learning and Multiplex Networks for Accurate Modeling of Brain Age

2. MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide

3. Neuroanatomical Assessment of Biological Maturity

4. Pitfalls in brain age analyses

5. Demographically Corrected Normative Standards for the English Version of the NIH Toolbox Cognition Battery

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