Advancing Glaucoma Care: Integrating Artificial Intelligence in Diagnosis, Management, and Progression Detection

Area of Science:

• Ophthalmology
• Medical Artificial Intelligence

Background:

• Glaucoma is a leading cause of irreversible blindness globally.
• Early detection and lifelong management are crucial for preserving vision.

Purpose of the Study:

• To review the current and future applications of artificial intelligence (AI) in clinical glaucoma care.
• To discuss practical considerations for implementing AI in glaucoma management.

Main Methods:

• Review of current AI technologies in glaucoma screening, diagnosis, monitoring, and treatment.
• Analysis of AI's role in surgical outcomes, training, patient education, and adherence.

Main Results:

• AI algorithms enhance screening by identifying high-risk patients.
• Deep learning models improve diagnosis by interpreting ocular imaging data.
• AI facilitates continuous monitoring, predictive analytics for precision medicine, and surgical advancements.

Conclusions:

• AI demonstrates transformative potential across the glaucoma care spectrum.
• Successful implementation requires careful consideration of clinical integration, usability, diversity, and ethics.