ClinicalSoftwareAI: Конформная оценка неопределенности, контрфактический аудит и одобренный FDA вывод
ClinicalSoftwareAI предоставляет инженерную инфраструктуру для создания, клинической сертификации и непрерывной актуализации алгоритмов машинного обучения в соответствии со стандартами FDA GMLP, Законом ЕС об ИИ и IEC 62304.
Clinical AI Governance Architecture
Continuous Drift Detection, PCCP Validation, and Explainability Gateway
Central System: Clinical AI Governance Core - FDA GMLP & Drift Engine
Clinical IoMT Nodes
- Clinical Data Lineage Tracker
- Distribution Drift Monitor
- PCCP Performance Bounds Enforcer
- Explainable Saliency Engine
- EHR Clinical Decision Interface
Architectural Layers & Regulatory Standards
- Clinical Data Provenance & Lineage (DVC (Data Version Control) / Merkle Provenance Hashes): Immutable tracking of clinical training datasets, demographic distributions, and data harmonization pipelines.
- Real-Time Distribution Drift Detection (Kolmogorov-Smirnov Drift Test / Maximum Mean Discrepancy (MMD)): Continuous statistical evaluation of inbound hospital telemetry against training baselines detecting covariate and concept shift.
- Predetermined Change Control Enforcer (PCCP Boundary Validator / Automated Regression Test Matrix): Automated verification that continuous weight updates stay within the pre-cleared sensitivity, specificity, and demographic parity boundaries.
- Explainability & Human-in-the-Loop Gateway (Integrated Gradients / Grad-CAM++ / Expected Calibration Error (ECE)): Synthesizing pixel attribution maps, confidence calibration scores, and contraindication warnings for clinician review.
Key Metrics: 10 Principles (FDA/Health Canada GMLP Adherence) | < 1 Sec (Real-Time Drift Detection Window) | 100% (Traceable Training Data Lineage) | High Risk (EU AI Act Classification Readiness)
Раскрытие потенциала адаптивного клинического ИИ без постоянных повторных подач
Traditional medical software clearance freezes machine learning weights at regulatory submission. ClinicalSoftwareAI implements FDA Predetermined Change Control Plans (PCCP), enabling continuous retraining on real-world clinical datasets within strictly validated performance envelopes.
Core Engineering Areas
Technical Articles
Related Cluster Architecture Specifications
- HealthVigilance — Zero-Trust IoMT Architecture, SaMD Risk Engineering & Autonomous Clinical Post-Market Vigilance
- AgenticSaMD — Autonomous Agentic Software as a Medical Device, Multi-Agent Clinical Decision Support & FDA GMLP Guardrails
- AITelemonitoring — Autonomous AI Telemonitoring, Virtual Nursing Assistants & Predictive Clinical Deterioration Scoring
- BCI2IoMT — Brain-Computer Interface IoMT Gateways, Neural Decoding & Electrophysiological Streaming