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Contact information


fidel.alfaroalmagro@ndcn.ox.ac.uk

Teaching Experience

Websites

Fidel Alfaro Almagro

Bioinformatician

DPhil in Brain Image Analysis.

MSc in Artificial Intelligence.

BSc in Computer Sciences.

My research is focused on developing fully automated analyses tools for UK Biobank Project, the biggest brain imaging study up to date with 6 different brain imaging modalities for 100,000 subjects. In that project my aim will be to develop new methods for multimodal-imaging population modelling using supervised machine learning methods. The final goal will be to find early biomarkers of brain diseases.

Department: FMRIB Analysis Group

Research interests: Machine learning, artificial intelligence, brain imaging, quality control, big data.

Personal interests: Science policy, public engagement and science communication.

Supervisors: Mark Jenkinson and Stephen Smith.

UK Biobank

Introduction to the UK Biobank Brain Imaging repository.

Collaborators

Key publications

SARS-CoV-2 is associated with changes in brain structure in UK Biobank

Journal article

Douaud G. et al, (2021)

Medium-term effects of SARS-CoV-2 infection on multiple vital organs, exercise capacity, cognition, quality of life and mental health, post-hospital discharge

Journal article

Raman B. et al, (2021), EClinicalMedicine, 31, 100683 - 100683

Confound modelling in UK Biobank brain imaging

Other

Alfaro-Almagro F. et al, (2020)

Handedness, language areas and neuropsychiatric diseases: insights from brain imaging and genetics

Journal article

Wiberg A. et al, (2019), Brain, 142, 2938 - 2947

Genome-wide association studies of brain imaging phenotypes in UK Biobank

Journal article

Elliott LT. et al, (2018), Nature, 562, 210 - 216

Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank

Journal article

Alfaro-Almagro F. et al, (2018), NeuroImage, 166, 400 - 424

An empirical, 21st century evaluation of phrenology

Journal article

Jones OP. et al, (2018)

Hand classification of fMRI ICA noise components

Journal article

Griffanti L. et al, (2017), NeuroImage, 154, 188 - 205

BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods

Journal article

Gorgolewski KJ. et al, (2017), PLOS Computational Biology, 13, e1005209 - e1005209

Multimodal population brain imaging in the UK Biobank prospective epidemiological study

Journal article

Miller KL. et al, (2016), Nature Neuroscience, 19, 1523 - 1536

More publications