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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>.

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