Upcoming Events

A Celebration of the IDentIFY project and Ten Years of ABIC Oct 22, 2019 09:30 AM - 03:30 PM — Suttie Centre for Teaching & Learning in Healthcare, Medical School Campus, University of Aberdeen
4D flow MRI workshop Oct 22, 2019 12:30 PM - 04:30 PM — ICE Building, Queen Elizabeth University Hospital Glasgow
NRS Mental Health Network Annual Scientific Meeting 2019 Oct 29, 2019 09:00 AM - 04:30 PM — Technology Innovation Centre, 99 George Street, Glasgow
PET is Wonderful Annual Meeting 2019 Oct 29, 2019 09:00 AM - 05:00 PM — Royal Society of Edinburgh, 22-26 George Street, Edinburgh
Scottish Radiological Society Annual General Meeting 2019 Nov 01, 2019 12:00 AM — Principal Grand Central Hotel, Glasgow

People


Your search for Keyword: 'Predictive Classification' returned 9 Result(s)



Mrs Jyothsna Divyananda


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Dr Javier Escudero

We focus on processing biomedical signals and images in clinical applications.

Our main aim is to reveal the subtle changes that major diseases (e.g., Alzheimer's and epilepsy) cause in the brain activity and how this changes in different conditions and mental states.

In collaboration with researchers at Edinburgh, across the UK and overseas, we are currently working in the processing and analysis of biomedical signals, particularly human brain activity. By applying advanced mathematics, we aim at increasing our understanding of how several brain conditions progress. Of particular interest is the evaluation of brain functional connectivity in both neurodevelopmental and neurodegenerative diseases to understand how they affect the way in which different brain regions interact with each other. We are also interested in the interplay between structure and function in the brain and in the application of pattern recognition techniques to highly-dimensional clinical datasets to support decision making. Finally, we also work in the development of non-invasive methods for rehabilitation purposes, being either the dexterous controls prostheses for amputees or brain-computer interfaces.

For additional information, please see: http://www.research.ed.ac.uk/portal/jescuder

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Miss Maria Goni


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Dr Jano van Hemert

Retinal imaging, image processing, automated image analysis, machine learning, medical devices, ophthalmology, eye health care, eye diseases, systemic diseases apparent in the eye.

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Dr Robin Ince


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Dr Rajeev Krishnadas

I completed my basic medical training from Govt Medical College, Thrissur, India, and MD in psychiatry from TN Medical college, Bombay University, India. Following this, I was sponsored by the British Council PGME scheme to train in psychiatry in the UK.  I am a member of the Royal College of Psychiatrists, and completed my PhD from the University of Glasgow.

I currently work as a Consultant Psychiatrist with the NHS GGC in ESTEEM, the only early intervention in psychosis team in Scotland.

Academic area of interest include using functional MRI and functional connectivity to predict outcomes in complex mental health problems. Linking inflammation to brain connectivity.

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Dr Kristin Nicodemus

Social cognition, neuroeconomics, computational psychiatry, schizophrenia, anxiety, bipolar disorder, depression, imaging genetics

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Miss Emma Pead

Assessing neurodegeneration of the retina and brain with ultra-widefield retinal images.

Philosophers have often described the eye as the window to the soul. This can also be addressed on the scientific basis that the retina is a direct window into the health of the brain (or CNS). My focus is on the development of automatic detection algorithms of biomarkers for Age-related macular degeneration (AMD) and Alzheimer’s disease (AD) in retinal images. AMD is often characterised by the presence of drusen, small deposits of cellular debris, in retinal images appearing as bright white/yellow spots. The hallmark of AD is the presence of Aβ-amyloid which has also been shown to be present in drusen. There are currently no treatments for late AMD, therefore early diagnosis and detection of drusen could provide timely treatment. Additionally, the potential of drusen as an early biomarker of AD will be explored. My methods focus on image analysis and quantification of fundus and OptoMap images (Optos) and application of machine learning algorithms as an automatic detection strategy.

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Professor Douglas Steele

Psychiatry, neurology, brain imaging: http://dslink333.dyndns.org/

 

 

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