Population and Health Data Science: SURES Funded PhD in Multimodal Machine Learning Prediction of Neuropathy, Foot Ulceration and Mortality

This PhD will investigate whether routinely collected diabetic retinal photographs, combined with clinical measurements, can more accurately identify individuals at risk of developing diabetic neuropathy, foot ulceration, other long-term complications and mortality. The project draws on a uniquely rich 9-year dataset from Sheffield’s One Stop microvascular screening service, where retinal images, validated point-of-care nerve tests (DPNCheck and SUDOSCAN), neuropathy scoring, foot assessment and blood biomarkers). Participants were then followed for 7–9 years to determine who went on to develop confirmed neuropathy, foot ulceration or mortality. The student will extract quantitative features from retinal images and combine these with clinical variables using interpretable machine learning methods to build practical risk-prediction tools. The aim is to identify early microvascular or nerve-related signals that may precede symptoms. This PhD aligns with emerging NHS priorities and benefits from Dr Tesfaye unique position as advisor to NHS England on the development of national One Stop microvascular screening services. The project aims to produce clinically interpretable prediction tools that could support earlier detection of high-risk individuals and reduce the burden of neuropathy, ulceration and mortality.

(To be eligible, International Applicant must also hold a SUIPRES Scholarship).

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