Connectionists: PhD Available: Predicting Recovery from Stroke with Machine Learning

[Howard Bowman]

PhD Available: Predicting Recovery from Stroke with Machine Learning

 

Professor Howard Bowman (University of Kent and University of Birmingham) is
looking to take on a PhD student to work on interpretable machine learning
applied to data acquired from stroke patients
(https://www.ucl.ac.uk/ploras/). This work will be with Professor Cathy
Price (Wellcome Centre for Human Neuroimaging, UCL), whose (PLORAS) team has
collected one of the largest data sets of stroke patients (greater than
1,000), including structural MRI scans, behaviour and demographics. A key
focus of Cathy Price's work is to predict the recovery trajectory of stroke
patients from their structural MRI scans, particularly patients with
language deficits (i.e. that are aphasic). Progress has been made on this
using traditional and now deep learning methods.

 

Critical to clinical uptake of machine learning in this area is the ability
to interpret the predictions it provides in a fashion that can be
communicated to clinicians, patients and carers. We seek to appoint a PhD
student to work on this topic, using methods such as neural-symbolic
techniques. The student will be located in the School of Computing at the
University of Kent, but will regularly visit and work closely with Cathy
Price's team at the Wellcome Centre for Human Neuroimaging. Expertise in
machine learning will be provided by Dr Thomas Hope (Wellcome Centre for
Human Neuroimaging, UCL) and Dr Marek Grzes (School of Computing, University
of Kent).

 

The PhD being advertised will be one of a tranche of scholarships available
in the School of Computing at the University of Kent at Canterbury. These
will be competitively allocated across a range of topics. To be eligible for
these scholarships, please contact Howard Bowman (H.Bowman at kent.ac.uk)
before 31st March 2019.

 

Relevant articles:

 

Besold, T. R., Garcez, A. D. A., Bader, S., Bowman, H., Domingos, P.,
Hitzler, P., ... & de Penning, L. (2017). Neural-symbolic learning and
reasoning: A survey and interpretation. arXiv preprint arXiv:1711.03902.

 

Hope, T. M., Seghier, M. L., Leff, A. P., & Price, C. J. (2013). Predicting
outcome and recovery after stroke with lesions extracted from MRI images.
NeuroImage: clinical, 2, 424-433.

 

Seghier, M. L., Patel, E., Prejawa, S., Ramsden, S., Selmer, A., Lim, L.,
... & Price, C.J. (2016). The PLORAS database: a data repository for
predicting language outcome and recovery after stroke. Neuroimage, 124,
1208-1212.

 

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