Build 'RetinaMind'—a $20K/year SaaS + hardware platform combining AI-driven retinal imaging with clinical decision support. The platform would: 1) Deploy handheld retinal scanners (e.g., Canon CR-i5) with edge AI (NVIDIA Jetson) to detect amyloid plaques in real-time (e.g., 'Patient #XYZ: 92% probability of early Alzheimer's'); 2) Provide a 'Diagnostic Confidence Dashboard' showing risk stratification (e.g., 'High-risk patients: 45%—referral required'); 3) Integrate with EHR systems (e.g., Epic, Cerner) to auto-generate specialty referrals; 4) Offer a 'Cost Savings Calculator' showing reduced misdiagnosis expenses (e.g., '$120K saved per clinic annually').

Market Catalyst & News Trigger

"FDA approves first AI-driven diagnostic tool for early-stage Alzheimer's disease detection using retinal scans"

The Workflow Friction

Neurologists and primary care physicians face a 10-15% misdiagnosis rate in early Alzheimer's due to subjective cognitive tests. Current diagnostic methods (lumbar punctures, PET scans) are invasive, expensive, and inaccessible. Delays in diagnosis result in $250K+ lifetime care costs per patient and lost therapeutic windows.

Problem Summary

Real-world problem signal validation.

One-Shot MVP Builder Blueprint (48 Hours)

Core dashboard showing real-time retinal analysis with risk scores, referral management, and integration with EHR APIs.

Recommended Developer Tech Stack

• React
• Django
• TensorFlow Lite
• PostgreSQL
• OpenCV