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https://github.com/rfonod/deepsleep2

😴 DeepSleep2 is a compact U-Net-inspired convolutional neural network with 740,551 parameters, designed to predict non-apnea sleep arousals from full-length multi-channel polysomnographic recordings at 5-millisecond resolution. Achieves similar performance to DeepSleep with lower computational cost.
https://github.com/rfonod/deepsleep2

cnn computational-efficiency convolutional-networks deep-learning encoder-decoder machine-learning medical-ai multichannel neural-networks physionet polysomnography pytorch segmentation sleep-analysis sleep-apnea sleep-arousals time-series u-net

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😴 DeepSleep2 is a compact U-Net-inspired convolutional neural network with 740,551 parameters, designed to predict non-apnea sleep arousals from full-length multi-channel polysomnographic recordings at 5-millisecond resolution. Achieves similar performance to DeepSleep with lower computational cost.

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