CNN (88.3% accuracy) and XGBoost (86%) beat zero-shot LLMs (about 46%) on NMPA medical device classification, with no single model winning on accuracy, interpretability, and cost simultaneously.
Regulatory frameworks for ai-enabled medical device software in china: Com- parative analysis and review of implications for global manufacturer,
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AI for Regulatory Affairs: Balancing Accuracy, Interpretability, and Computational Cost in Medical Device Classification
CNN (88.3% accuracy) and XGBoost (86%) beat zero-shot LLMs (about 46%) on NMPA medical device classification, with no single model winning on accuracy, interpretability, and cost simultaneously.