DRRisk: A Web-based tool to Assess the Risk of Diabetic Retinopathy through Machine Learning on Electronic Health...

Objective: We developed a web-based tool for diabetic retinopathy (DR) risk assessment called DRRisk (https://drandml.cdrewu.edu/) using machine learning on electronic health record (EHR) data, with a goal of preventing vision loss in persons with diabetes, especially in underserved settings. Methods: DRRisk uses Python's Flask framework. Its user-interface is implemented using HTML, CSS and Javascript. Clinical experts were consulted on the tool's design. Results: DRRisk assesses current DR risk for people with diabetes, categorizing their risk level as low, moderate, or high, depending on the percentage of DR risk assigned by the underlying machine learning model. Discussion: A goal of our tool is to help providers prioritize patients at high risk for DR in order to prevent blindness. Conclusion: Our tool uses DR risk factors from EHR data to calculate a diabetic person's current DR risk. It may be useful for identifying unscreened diabetic patients who have undiagnosed DR.