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782 ± 0.097, 95% CI [0.777-0.787]; 100% 0.869 ± 0.064, 95% CI [0.864-0.872]), and with increasing number of data sources (2 0.788 ± 0.102, 95% CI [0.787-0.790]; 3 0.808 ± 0.092, 95% CI [0.807-0.810]; 4 0.821 ± 0.085, 95% CI [0.819-0.823]). Different cohorts show varying levels of generalization to other cohorts. Automatic sleep stage scoring systems based on deep learning algorithms should consider as much data as possible from as many sources available to ensure proper generalization. Public datasets for benchmarking should be made available for fu

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