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Dr Jim Coke

Postgraduate Student

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Postgraduate Student in the Department of Computer Science  


There are over 120 features that characterise a person with Down Syndrome, but most individuals carry about eight which are recognised through prenatal screening. In Sub-Saharan Africa, prenatal screening is generally inaccessible and unaffordable to the general population. Therefore there is a need to develop computer-aided systems to detect Downs Syndrome. Jim’s primary research is to develop machine learning models for facial recognition to detect the characteristic dysmorphic features of Down Syndrome patients in Africa. The models will ultimately lead to the build of a freely available mobile app that will help trained clinicians, teachers, and the general public identify an African with Down Syndrome.