“…Also, it would be interesting to add memory to the model using recurrent networks, as the classification of some inputs, following the clinical definition, depends as well on the status of the neighbouring epochs. Biswal et al [22] Massachusetts General Hospital, 1000 recordings 0,77 0,81 0,70 0,77 0,83 0,92 Längkvist et al [18] St Vicent's University Hospital, 25 recordings 0,63 0,73 0,44 0,65 0,86 0,80 Sors et al [23] SHHS, 1730 recordings 0,81 0,91 0,43 0,88 0,85 0,85 Supratak et al [21] MASS dataset, 62 recordings 0,80 0,87 0,60 0,90 0,82 0,89 Supratak et al [21] SleepEDF, 20 recordings 0,76 0,85 0,47 0,86 0,85 0,82 Tsinalis et al [19] SleepEDF, 39 recordings 0,71 0,72 0,47 0,85 0,84 0,81 Tsinalis et al [20] SleepEDF, 39 recordings 0,66 0,67 0,44 0,81 0,85 0,76…”