AI retinal imaging
Clinical Research · 2026

Understanding decision complexity in retinal follow-up

A clinical study exploring how specialists make decisions in complex retinal cases — and how decision support tools can improve clarity, speed, and consistency.

These decisions are often made under time pressure, with incomplete clarity, and vary significantly between clinicians.

Complex Cases
AMD / DME
Longitudinal
Decision-Making
Treatment
Response Evaluation
Cognitive
Clinician Load
About the Study

Why this research matters

Chronic retinal diseases require lifelong monitoring. In busy clinics, the cognitive demand of synthesizing years of imaging, treatment history, and disease progression is significant — and understudied.

In high-volume retinal clinics, clinicians review large amounts of imaging and clinical data at every follow-up visit. For chronic diseases like macular degeneration and diabetic eye disease, treatment decisions depend on comparing multiple scans across time.

Under time pressure, clinicians must quickly synthesize years of imaging, treatment history, and disease progression patterns before deciding whether to treat or defer.

"The goal is not to replace physician judgment — but to understand where the system creates unnecessary cognitive burden, and what structured support could look like."

This study captures the real-world experience of retinal specialists across practice settings, experience levels, and clinical roles — including residents and fellows whose perspective on workflow friction is uniquely valuable.

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Evidence-Based Design

Survey responses will directly inform clinical tool design grounded in real workflow challenges — not assumptions.

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Anonymous & Confidential

All responses are anonymous and analyzed only in aggregate. No personally identifiable data is collected.

Minimal Time Commitment

The survey takes approximately 5–7 minutes. Your time and clinical expertise are deeply valued.

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Findings Shared With Participants

All participants who leave contact information will receive a summary of the research findings.

What we are investigating

This study addresses four core questions about retinal workflow and clinical decision-making under real-world conditions.

01

Longitudinal Review Patterns

How do retinal specialists currently review and synthesize prior imaging and treatment history during follow-up visits?

02

Decision-Making Under Pressure

How does time pressure affect the thoroughness of longitudinal review — and what gets shortened or skipped?

03

Cognitive Load & Confidence

What factors make treat vs. defer decisions most challenging, and how confident are clinicians in their assessments?

04

Clinical Tool Readiness

What would a longitudinal intelligence tool need to look like to meaningfully support — not disrupt — clinical workflow?

05

Teaching Environment Impact

How does the presence of residents and fellows affect the quality and depth of longitudinal data review?

06

Systems & Integration Gaps

What are the most painful limitations of current OCT viewers, EHR systems, and injection tracking tools?

Research Team

Led by clinical experts

This study is conducted by a multidisciplinary team combining expertise in artificial intelligence, medical imaging, and clinical ophthalmology.

HA

Dr. Hanan Alghamdi

Associate Professor of AI in Medical Imaging

Leading research at the intersection of artificial intelligence and medical imaging systems. Principal investigator for the RetinalInsight clinical workflow study.

ST

Dr. Safwan Tayeb

Assistant Professor of Ophthalmology

Clinical co-investigator with expertise in retinal disease management and surgical ophthalmology. Guides the clinical validity and relevance of all research instruments.

Your clinical experience
is the evidence

The most valuable data in this study comes directly from specialists managing retinal disease every day. Whether you are a consultant, fellow, or resident — your perspective shapes what gets built.

~5 minutes to complete
Anonymous · no passwords
Open to all experience levels
Begin the Survey →

This research directly informs the development of a clinical decision support tool being built for real-world use.

For questions: research@retinalinsight.org