【Auditing Artificial Intelligence Reasoning in Healthcare: The DEEP SEETM-MIRROR Dual-Layer Architecture for Structured AI Analysis and Meta-Cognitive Safety Oversight】
#论文发表# #人工智能# #AI推理# #医疗健康#

Existing research on trustworthy artificial intelligence has largely focused on model performance, data quality, explainability, and governance. However, comparatively less attention has been directed toward systematic evaluation of the reasoning pathways through which AI systems generate those conclusions. This paper proposes the DEEP SEETM-MIRROR architecture, a dual-layer framework designed to structure and audit artificial intelligence reasoning in healthcare. The DEEP SEETM layer provides a structured reasoning protocol that guides how AI systems analyze clinical data, identify emerging safety signals, and generate interpretable reasoning outputs. The MIRROR layer introduces a meta-cognitive audit process that evaluates the integrity of those reasoning pathways by examining evidential support, logical consistency, alternative explanations, and uncertainty calibration.

DOI: 10.4236/health.2026.187041 http://t.cn/AXKR30fy