ClinicalSoftwareAI：コンフォーマル不確実性推定、反事実監査、FDA認可水準の高信頼推論

ClinicalSoftwareAIは、FDA GMLP、EU AI法、IEC 62304標準に準拠して臨床機械学習アルゴリズムを構築、許認可取得、継続的アップデートするために必要なエンジニアリングインフラストラクチャを提供します。

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)

継続的な再提出なしに適応型臨床AIを実現する

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