aiml-validation-framework

name	aiml-validation-framework
description	AI/ML medical device validation skill implementing FDA's GMLP principles
allowed-tools	["Read","Write","Glob","Grep","Edit","Bash"]
metadata	{"specialization":"biomedical-engineering","domain":"science","category":"Medical Device Software","skill-id":"BME-SK-021"}
graph	{"domains":["domain:biomedical-engineering"],"skillAreas":["skill-area:machine-learning-frameworks","skill-area:statistical-analysis","skill-area:compliance-automation"],"workflows":["workflow:experiment-design","workflow:peer-review-cycle"],"roles":["role:biomedical-engineer","role:ml-engineer"]}

AI/ML Validation Framework Skill

Purpose

The AI/ML Validation Framework Skill supports validation of AI/ML-enabled medical devices per FDA Good Machine Learning Practice (GMLP) principles, addressing data quality, model performance, and predetermined change control.

Capabilities

• Training data quality assessment
• Ground truth labeling validation
• Model performance metrics calculation (AUC, sensitivity, specificity)
• Subgroup performance analysis
• Bias and fairness evaluation
• Predetermined change control plan (PCCP) templates
• Clinical validation study design
• Locked algorithm vs. adaptive documentation