New statistical method can flag hidden anomalies in scientific datasets

A research team at the University of Vienna, led by pharmaceutical chemist Johannes Kirchmair, has developed a statistical method to identify hidden anomalies in scientific datasets. The method can be applied automatically to large datasets, making it easier for researchers to pinpoint those that need closer scrutiny. The approach improves the quality of data-driven research and supports the development of reliable AI applications.

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