Clinical Research Directory

PREDiction of Different Variants of Sleep Stages for the Diagnosis Support of Chronic Insomnia and Epilepsy

Sponsor: Assistance Publique - Hôpitaux de Paris

Summary

The objective of this study is to develop and validate deep learning algorithms for automated sleep stage and sub-stage classification using overnight polysomnography data. The models will be trained and evaluated on at least three independent datasets to ensure generalizability. \- Primary Outcome Measure : Accuracy of deep learning-based sleep stage classification compared to expert manual scoring (\>80% target agreement), evaluated across multiple polysomnography datasets including AP-HP (Assistance Publique - Hôpitaux de Paris) data. This is a retrospective, observational study.

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