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Deep Learning
Investigating the Utility of Explainable Artificial Intelligence for Neuroimaging-Based Dementia Diagnosis and Prognosis
Artificial intelligence and neuroimaging enable accurate dementia prediction but often involve ‘black box’ models that can …
Sophie A Martin
,
An Zhao
,
Jiongqi Qu
,
Phoebe Imms
,
Andrei Irimia
,
Frederik Barkhof
,
James H Cole
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Project
DOI
Interpretable deep learning for dementia: a systematic review
Introduction.
Machine learning research into automated dementia diagnosis is becoming increasingly popular but so far has had limited …
Sophie A Martin
,
Frederik Barkhof
,
James H Cole
Cite
Project
DOI
Interpretable Dementia Prediction
Developing a framework for interpretable, explainable dementia prediction and validating existing methods.
Sophie A Martin
Low-field MRI
Enhancing low-field MRI images using generative models, in particular diffusion models
Rui Yeow
,
James H Cole
Motor Neurone Disease
Predicting disease progression in motor neurone disease
James H Cole
,
Florence Townend
,
Ayodeji Ijishakin
Multimodal Brain Age
Using the UK Biobank to predict brain age from multiple modalities of MRI data, including structural, diffusion and functional scans.
Melis Anatürk
,
James H Cole
Neurodevelopment
Predicting risk of poor educational outcomes from MRI measurements of the brain during infancy and early childhood
Francesca Biondo
,
James H Cole
,
Mariam Zabihi
Scottish Medical Imaging Archive
Exploring the utility of brain age in a population-scale imaging dataset with linked health records.
Sophie A Martin
,
James H Cole
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