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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

Everything You Need To Know About Staff Augmentation

The staff augmentation model is a fantastic alternative for IT organizations looking to save on expenses while increasing production and efficiency. Before you use this model, you must first understand what it entails, what it can be used for, what the benefits are, and how to work effectively with augmented teams.

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