Fidel Alfaro studied Computer Sciences at Universidad de Granada (Spain) in 2006, obtained a Masters Degree in Artificial Intelligence from UNED (Spain) in 2011, and completed his DPhil in Clinical Neurosciences at the University of Oxford in 2020. Between those degrees he worked as a Software Engineer in Spanish private consultancy companies and spent a year at CERN (Switzerland) with a fellowship from the Spanish Government. He has worked in brain imaging analysis in Madrid (2011 to 2013) and Oxford (2013 to present day) where he started his DPhil. His research is focused on developing fully automated analyses tools for the UK Biobank Project, the largest brain imaging study to date, with 6 different brain imaging modalities acquired from 100,000 subjects. In this project his aim is to develop new methods for multimodal-imaging population modelling using supervised machine learning methods, with the ultimate goal being to find early biomarkers of brain diseases.
Brain Imaging in UK Biobank
The UK Biobank is a prospective epidemiological study that aims to gather all kinds of data from 500,000 people in the UK. So far, UKB has acquired and processed 6 brain image modalities of 50,000 volunteers. In this talk, we will see the details of how to guarantee full automatisation of that processing, data management, and details of quality control. We will also have a look at the kind of data that is openly available for researchers worldwide and some tips about how to use that data in correlational studies.