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Found 6 papers, 1 papers with code
Generative Pre-Trained Transformer for Cardiac Abnormality Detection
Our team, CinCSEM, proposes to draw the parallel between text and periodic time series signals by viewing the repeated period as words and the whole signal as a sequence of such words.
Cardiac Arrhythmia Detection from ECG with Convolutional Recurrent Neural Networks
We applied the neural networks to the dataset used for the challenge of Computing in Cardiology 2017 and a dataset built by joining three databases available on PhysioNet.
ECG Classification with a Convolutional Recurrent Neural Network
The model combines convolutional and recurrent layers, takes sliding windows of ECG signals as input and yields the probability of each class as output.
Convolutional-Recurrent Neural Networks on Low-Power Wearable Platforms for Cardiac Arrhythmia Detection
Low-power sensing technologies, such as wearables, have emerged in the healthcare domain since they enable continuous and non-invasive monitoring of physiological signals.
Classification of Cardiac Arrhythmias from Single Lead ECG with a Convolutional Recurrent Neural Network
While most heart arrhythmias are not immediately harmful, they can lead to severe complications.
Embedded Deep Learning for Sleep Staging
The rapidly-advancing technology of deep learning (DL) into the world of the Internet of Things (IoT) has not fully entered in the fields of m-Health yet.
