Leveraging AI for Enhanced Retinal Care image
Leveraging AI for Enhanced Retinal Care image

Independent Medical Education supported by Apellis and AbbVie. Content supplied by EURETINA.

May/June 2025 Supplement | The Role of AI in Diagnostics and Workflow Efficiency

Leveraging AI for Enhanced Retinal Care

Arshad M. Khanani, MD, MA headshot

While many practices have yet to adopt AI tools, their potential to streamline workflows and enhance patient care is increasingly evident. Even in well-organized clinics, challenges with imaging evaluation and appointment scheduling can hinder patient flow. AI-powered tools automate image analysis, efficiently comparing past and current scans to reduce manual review time and improve diagnostic accuracy. Scheduling also presents obstacles, as appointment urgency is typically determined by human judgment, which can lead to inefficiencies. AI-driven scheduling prioritizes patients based on disease severity, optimizing workflow and minimizing delays for urgent cases.

AI’s Diagnostic and Monitoring Capabilities

A recent EURETINA Clinical Trends Survey found 79% of respondents believe AI will enhance their practice, particularly in diagnosis and imaging. AI’s ability to efficiently and accurately compare historical and current imaging provides valuable insights for both clinicians and patients. For example, in nAMD, AI can assess pigment epithelial detachment height and fluid levels, while in geographic atrophy, it can track photoreceptor and RPE loss. These insights enhance disease understanding and treatment response.

Furthermore, AI enhances diagnostic efficiency by automating fluid detection in OCT imaging and improving assessment accuracy. AI-powered home monitoring solutions analyze remote OCT scans, alerting clinicians to disease progression and enabling earlier intervention while reducing unnecessary visits.

As sustained drug delivery systems reduce the need for clinic visits, AI-driven home monitoring will become even more essential for maintaining quality of care and efficiency.

Data Security and Privacy

Clinicians are concerned about AI’s impact on patient privacy. Compliance with stringent security protocols is critical. Robust safety measures and adherence to regulatory standards allow healthcare providers to integrate AI while maintaining patient confidentiality.

Cloud-based AI tools must anonymize patient images before uploading and fully comply with HIPAA regulations. Ongoing advancements in AI security continue to strengthen data protection, ensuring clinicians can leverage AI’s benefits without compromising privacy.

The Future of AI in Retinal Care

AI will revolutionize surgical planning and intervention by providing predictive insights based on baseline patient characteristics. In complex procedures, AI-guided and robotic-assisted surgeries will enhance precision and safety.

As AI continues to evolve, emphasis should be placed on developing user-friendly solutions, along with standardized databases, to ensure consistency, accuracy, and improved patient care. With strategic implementation, AI-driven tools will not only enhance clinical decision-making but also set new benchmarks in retinal care.

Conclusion

AI is transforming workflow efficiency, diagnostic accuracy, and patient outcomes. With careful implementation and attention to data security, AI will play a crucial role in shaping the future of retinal care.

The views and opinions expressed in this content may not necessarily represent those of Bryn Mawr Communications or Retina Today.

Arshad M. Khanani, MD, MA headshot

Arshad M. Khanani, MD, MA, FASRS

  • Dr. Arshad M. Khanani is managing partner, director of Clinical Research, and director of Fellowship at Sierra Eye Associates and clinical professor at the University of Nevada, Reno School of Medicine, USA. Dr. Khanani can be contacted at arshad.khanani@gmail.com
  • Financial Disclosures: Consultant: Apellis and Astellas Pharma; Research Funding: Apellis and Astellas Pharma.