New Results
Quantifying uncertainty in brain-predicted age using scalar-on-image quantile regression
View ORCID ProfileMarco Palma, Shahin Tavakoli, Julia Brettschneider, Thomas E. Nichols, for the Alzheimer’s Disease Neuroimaging Initiative
doi: https://doi.org/10.1101/853341
Marco Palma
aDepartment of Statistics, University of Warwick, Coventry, CV4 7AL, United Kingdom
Shahin Tavakoli
aDepartment of Statistics, University of Warwick, Coventry, CV4 7AL, United Kingdom
Julia Brettschneider
aDepartment of Statistics, University of Warwick, Coventry, CV4 7AL, United Kingdom
bThe Alan Turing Institute, London, NW1 2DB, United Kingdom
Thomas E. Nichols
aDepartment of Statistics, University of Warwick, Coventry, CV4 7AL, United Kingdom
cBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
dWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
Article usage
Posted November 26, 2019.
Quantifying uncertainty in brain-predicted age using scalar-on-image quantile regression
Marco Palma, Shahin Tavakoli, Julia Brettschneider, Thomas E. Nichols, for the Alzheimer’s Disease Neuroimaging Initiative
bioRxiv 853341; doi: https://doi.org/10.1101/853341
Subject Area
Subject Areas
- Biochemistry (11715)
- Bioengineering (8723)
- Bioinformatics (29129)
- Biophysics (14936)
- Cancer Biology (12049)
- Cell Biology (17359)
- Clinical Trials (138)
- Developmental Biology (9406)
- Ecology (14144)
- Epidemiology (2067)
- Evolutionary Biology (18268)
- Genetics (12221)
- Genomics (16767)
- Immunology (11843)
- Microbiology (28014)
- Molecular Biology (11560)
- Neuroscience (60814)
- Paleontology (450)
- Pathology (1864)
- Pharmacology and Toxicology (3231)
- Physiology (4940)
- Plant Biology (10384)
- Synthetic Biology (2878)
- Systems Biology (7333)
- Zoology (1642)