Connectionists: PhD Studentship: Bayesian Deep Learning for Alzheimer's conversion prediction in Mild Cognitive Impairment subjects

[Alba García]

Mild cognitive impairment (MCI) is a transitional state between normal
ageing and dementia. In a number of cases, MCI carries the risk of
conversion to Alzheimer’s disease-related dementia. MCI typically includes
slowing of motor performance and information processing, impaired attention
and impaired executive functions with partial preservation of memory.
Machine learning techniques have recently been identified as promising
tools in neuroimaging data analysis and can, to a certain extent, work on a
single patient basis in predicting conversion from MCI to Alzheimer’s
disease (AD). This PhD will investigate novel convolutional and Bayesian
deep learning techniques to identify biomarkers of MCI and improve the
accuracy of detecting early signs of the potential for MCI to progress into
AD. Early AD diagnosis is important for giving access to treatments that
can improve symptoms and slow down the progress of the disease.



The successful applicant will be supervised by Dr Luca Citi and Dr Alba
García and will be part of the Essex BCI and Neural Engineering Lab (
http://essexbcis.uk): today the UK’s largest research group in
brain-computer interfaces.



Deadline: Friday 23 February 2018



http://www.jobs.ac.uk/job/BHF171/phd-studentship-bayesian-deep-learning-for-alzheimers-conversion-prediction-in-mild-cognitive-impairment-subjects/



Dr Alba García Seco de Herrera PhD

Lecturer

Department of Computer Science and Electronic Engineering

University of Essex



T +44 (0)1206 872907

E alba.garcia at essex.ac.uk

► https://www1.essex.ac.uk/csee/
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