Under the title "Digital Eye Clinic – Bringing AI diagnostics into practice", it highlights nine key areas:

1. Addressing diabetic retinopathy
2. The medical and technological potential of AI
3. Designing the patient journey with AI diagnostics
4. Assessment of diagnostic providers and platforms
5. Development and validation of in-house AI models
6. Concept for testing phase
7. Moving towards the Digital Eye Clinic
8. Regulatory and ethical requirements
9. Conclusions and best practices

Diabetic retinopathy is one of the leading causes of preventable blindness, but screening is costly and difficult to scale. AI diagnostics can help here by automating routine examinations and supporting specialists. The team therefore examined existing AI tools and, as none met the clinic's requirements, developed its own AI platform using an open source tool.

The results provide healthcare organizations with a practical framework for evaluating AI diagnostic tools and show that open source solutions can be successfully deployed in public hospitals.

Report:
German
English