Built for structured medical evaluation.
Kayalogy is designed for transparent evaluation of medical imaging AI, with reproducible testing, traceable model versions, and documentation aligned with future clinical and regulatory requirements.
Current status: Kayalogy is under development and intended for research and evaluation use.
Structured evaluation and reporting
Performance assessment is built around reproducible evaluation workflows. Model versions, configurations, and outputs are documented to support repeatable benchmarking and transparent comparison over time.
- Standard performance metrics such as Dice, IoU, Sensitivity, Specificity, Precision, and F1
- Versioned runs and traceable evaluation artifacts
- Consistent testing logic and documented configurations
Intended use and performance boundaries
Reliable clinical evaluation starts with clearly defined scope. Kayalogy documents intended use, known limitations, and relevant performance boundaries to support realistic interpretation of results.
- Defined intended use and model scope
- Documented limitations and known failure modes
- Review of generalization and subgroup behavior where feasible
Risk management and quality controls
Development is guided by MedTech-oriented quality principles. Risk analysis, documentation discipline, and change control help support safe iteration and a structured pathway toward future regulatory readiness.
- ISO 14971-style risk thinking for hazards, mitigations, and residual risk
- ISO 13485-aligned process discipline as the platform matures
- Traceability, change control, and documented improvement cycles
Privacy and data governance
Medical data requires careful governance. Kayalogy is designed around privacy-first handling, controlled access, and documented data management principles compatible with Swiss and applicable European expectations.
- Clear expectations for de-identified clinical data where appropriate
- Role-based access principles and audit-friendly control logic
- Retention and deletion principles aligned with purpose and governance requirements