Contact information
Colleges
Teaching Experience
- FMRIB Graduate Teaching Programme (internal Oxford course)
- FSL Course (external course)
Websites
-
ResearchGate Profile
ResearchGate
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@NeuroFidelity
Twitter Profile
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
Key publications
SARS-CoV-2 is associated with changes in brain structure in UK Biobank.
Journal article
Douaud G. et al, (2022), medRxiv
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
Confound modelling in UK Biobank brain imaging.
Other
Alfaro-Almagro F. et al, (2021), NeuroImage, 224, 117002 - 117002
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
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 Comput Biol, 13
Multimodal population brain imaging in the UK Biobank prospective epidemiological study.
Journal article
Miller KL. et al, (2016), Nat Neurosci, 19, 1523 - 1536
