Detecting Site‐Level Fraud via an Artificial Intelligence/Machine Learning Paradoxical Patient Analysis in an Alzheimer's Disease Clinical Trial

Abstract

This work demonstrates that NetraAI's paradoxical patient-focused approach can identify anomalous patients and sites in AD clinical trials using screening and baseline data alone, even without prior site-level fraud data. By relying solely on patient-level metrics, NetraAI provides a scalable, objective strategy to enhance data integrity in clinical trials. Future research will extend these insights to direct site-level assessments, further refining this framework for broader clinical trial applications.

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