Machine Learning-assisted Digital Twin for Diabetic Retinopathy

Diabetic retinopathy is one of the leading causes of vision loss among individuals with diabetes. The condition develops when prolonged high blood sugar levels damage blood vessels in the retina. Early detection and continuous monitoring are essential for preventing severe vision impairment.

The concept of a digital twin in healthcare involves creating a virtual representation of a patient’s physiological condition using data from medical records, diagnostic images, and health monitoring devices. In this use case, machine learning techniques are used to develop digital twin models for patients at risk of diabetic retinopathy.

For additional context and detailed documentation of this use case, please refer to pages 95-104 in the attached Casebook.