|Funding for:||UK Students, EU Students|
|Funding amount:||Not Specified|
|Placed On:||26th March 2019|
|Closes:||26th June 2019|
Howard Bowman and Marek Grzes
This PhD research would focus 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. The PhD student would 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).
Please direct enquires to Professor Howard Bowman (H.Bowman@kent.ac.uk).
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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