Deep learning-based prognosis of the treatment success of Age-related Macular Degeneration (AMD)

DeepEye project: Using AI to
combat old-age blindness

Challenge

Age-related macular degeneration (AMD) is an eye disease that occurs frequently in old age, with over 25 million people worldwide, and which severely affects the eyesight of those affected. The eye center at St. Franziskus-Hospital Münster is a renowned contact point for AMD sufferers and is constantly looking for ways to improve the diagnostic and treatment methods used.

Supported by the biotech and pharmaceutical company Novartis, a proof of concept was carried out to determine how well the AMD disease can be recognized using deep learning and the success of the treatment can be predicted.

Approach

With the help of so-called convolutional neural networks – a type of neural network that is frequently used in image recognition – various models relating to the diagnosis and treatment of AMD were created. The documentation of the cases treated over the years was used to learn the neural networks. In addition to the OCT examinations of the retina including metadata, this also includes information from other examinations, medication prescriptions and patient master data, such as age and gender.

Result

The trained models can predict the various AMD cases with an accuracy of up to 90%. When used as diagnostic assistance, the developed models have the potential to relieve medical staff in everyday clinical practice, to support them in choosing a suitable treatment and thus to minimize wrong decisions.

Project Information

Industry:
Medicin, Ophthalmology

Use Case:
Prognosis of the treatment success of Age-related Macular Degeneration (AMD)

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