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Research Topic: Using AI to combine genomic with pathology Images to improve Lymphoma Diagnosis
Supervisors: Dr Sharon Barrance, Dr Cathy Burton, Professor David Westhead
About Sam: Sam studied Physics and Astronomy at Durham University followed by a Masters in AI and Computer Science at St Andrews University.
Project Description: In my project I will be looking at lymphoma image and genetic data, with the intention to contribute to the understanding of different sub-types of lymphoma and to improve diagnosis. Lymphoma arises from excessive mutations in lymphocytes. The pathogenic variants often occur during lymphocyte differentiation, where induced variation is crucial. Currently, researchers have defined over 60 sub-types of lymphoma, although these are usually grouped into broader categories. In this project I hope to utilise a range of tools based on deep learning and supervised and unsupervised techniques to identify lymphoma sub-groups and better understand the disease. For this, over 1500 data samples have been made available. Each data sample has genetic data and image data, where each image of the tissue sample is high resolution, featuring microscopic detail, resolving features down to cell nuclei.