Enhance Your Clinical Expertise with AI-Driven Screening
Diabetic retinopathy (DR) is a leading cause of vision loss worldwide, and early detection is critical to preventing severe complications. Artificial intelligence (AI) is transforming the way healthcare professionals detect and manage DR, offering faster, more accurate, and scalable screening solutions. However, understanding how to interpret AI results and knowing when human expertise is necessary are key skills for ensuring optimal patient outcomes.
In this interactive eLearning course, you will:
✅ Explore real-world applications of AI in DR screening, from detecting early signs of the disease to assessing severe cases.
✅ Engage with case scenarios that challenge you to make clinical decisions based on AI results, patient history, and best practices.
✅ Learn to navigate AI limitations, including ungradable images and situations where human intervention is required.
Who Should Enroll?
This course is designed for healthcare professionals involved in diabetes management and eye care, including:
🔹 Endocrinologists & Diabetologists
🔹 Ophthalmologists & Optometrists
🔹 General Practitioners & Healthcare Providers Interested in AI in Medicine
Course Structure
📌 Module 1: Understanding AI in Diabetic Retinopathy Screening
- The burden of diabetic retinopathy (DR)
- Key benefits of AI in DR screening
- Integrating AI into clinical practice
📌 Module 2: Case-Based Learning & Decision-Making
- Mild NPDR – AI vs. Human Judgment
- Ungradable Images – AI Limitations and Next Steps
🎓 Earn a CME/CPD Certificate Upon Completion (1 CME/CPD credit)
Take a step into the future of AI-assisted medicine and gain practical skills that enhance your ability to diagnose and manage diabetic retinopathy.
🔗 Enroll now and stay ahead in the evolving landscape of AI-driven healthcare!
This course is supported by iCare.