Machine Learning for Risk Stratification of Diabetic Foot Ulcers Using Biomarkers

Kyle Martin, Ashish Upadhyay, Anjana Wijekoon, Nirmalie Wiratunga, Stewart Massie

Abstract: Development of a Diabetic Foot Ulcer (DFU) causes a sharp decline in a patient’s health and quality of life. The process of risk stratification is crucial for informing the care that a patient should receive to help manage their Diabetes before an ulcer can form. In existing practice, risk stratification is a manual process where a clinician allocates a risk category based on biomarker features captured during routine appointments. We present the preliminary outcomes of a feasibility study on machine learning techniques for risk stratification of DFU formation. Our findings highlight the importance of considering patient history, and allow us to identify biomarkers which are important for risk classification.