Work

TADPOLE Challenge: Accurate Alzheimer’s Disease Prediction Through Crowdsourced Forecasting of Future Data

Year: 2019

Type: conference-paper

Source: Lecture notes in computer science

DOI: 10.1007/978-3-030-32281-6_1

Authors: Răzvan V. Marinescu, Neil P. Oxtoby, Alexandra L. Young, Esther E. Bron, Arthur W. Toga, Michael W. Weiner, Frederik Barkhof, Nick C. Fox, Polina Golland, Stefan Klein, Daniel C. Alexander

Institutions: MIT Computer Science and Artificial Intelligence Laboratory, University College London, Massachusetts Institute of Technology, Erasmus MC, University of Southern California, University of California, San Francisco, University of California San Francisco Medical Center, Amsterdam UMC Location Vrije Universiteit Amsterdam, UCL Queen Square Institute of Neurology

Language: English

Topic: Dementia and Cognitive Impairment Research

Subfield: Psychiatry and Mental health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Institute on Aging, National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering

Awards: G104586243, Neuroimaging Analysis Center (NAC), MRI-GENetics Interface Exploration_MRI-GENIE_Study, Alzheimer's Disease Neuroimaging Initiative, Alzheimer Disease Research Center

OpenAlex ID: W2979840928

FWCI: 21.09

Cites: 14

Cited by: 72

Related to: 10