eyeTech provides an adaptive ECG platform that accelerates clinician training and improves diagnostic accuracy for cardiac care. The system uses research‑driven analytics to personalize instruction and deliver precise assessments, helping healthcare providers enhance patient outcomes. It is validated through academic studies and recognized across medical conferences and media.
Funding
Funding not disclosed
Founders
Product
Problem
Cardiac electrophysiology teams often face lengthy training cycles and variable diagnostic accuracy when interpreting ECG data, which can delay treatment decisions and affect patient outcomes.
Solution
eyeTech delivers an adaptive ECG platform that shortens training timelines by providing real-time performance analytics and personalized instruction for clinicians. The system uses research‑validated algorithms to automatically assess ECG recordings, highlight critical arrhythmias, and suggest diagnostic interpretations. By continuously adapting to each user’s skill level, the platform ensures consistent, high‑precision assessments across the team. Integrated analytics generate actionable feedback, enabling clinicians to refine techniques and maintain diagnostic confidence. The solution is built on rigorously tested, academically supported technology, aligning training efficiency with improved patient care.
Target Audience
Primary users are cardiac electrophysiology departments in hospitals and specialized cardiac clinics that require efficient clinician training and reliable ECG diagnostics.
Features
- Adaptive learning engine that tailors ECG interpretation training to individual clinician proficiency
- Automated, AI‑driven arrhythmia detection with confidence scoring for each ECG segment
- Real-time analytics dashboard displaying performance metrics, error patterns, and progress trends
- Research‑backed validation framework ensuring diagnostic recommendations meet clinical standards
- Secure, cloud‑based data handling with audit trails to support regulatory compliance and patient safety