A Structural Labeling-File Audit and Secondary Model-Output Evaluation of Korean Specialized and Essential Medical Knowledge Datasets for Medical AI Research
The public training/validation labeling files showed favorable basic structural completeness, but the unavailable test labels, multiple-choice predominance, domain imbalance, limited record-level provenance, and incomplete model-package traceability constrain claims of clinical readiness.