AI-Driven Anomaly Detection for Data Quality // Automated data quality auditing using unsupervised machine learning. Provides AI-driven anomaly detection for data quality assessment, primarily designed for Electronic Health Records (EHR) data, with benchmarking capabilities for validation and publication. Methods based on: Liu et al. (2008) doi:10.1109/ICDM.2008.17, Breunig et al. (2000) doi:10.1145/342009.335388.