Search Results for author:
Found 4 papers, 0 papers with code
Benchmarking the Impact of Noise on Deep Learning-based Classification of Atrial Fibrillation in 12-Lead ECG
We analyze the accuracy of the Deep Learning model with respect to both metrics and observe that the method can robustly identify atrial fibrillation, even in cases signals are labelled by human experts as being noisy on multiple leads.
Measurement of Individual Alteration in Perioperative ECGs During Elective Percutaneous Coronary Intervention
In this work, we evaluate the inter-patient magnitude of individual ECG alterations during ischemia.
Analysis of a Deep Learning Model for 12-Lead ECG Classification Reveals Learned Features Similar to Diagnostic Criteria
Despite their remarkable performance, deep neural networks remain unadopted in clinical practice, which is considered to be partially due to their lack in explainability.
Edge computing in 5G cellular networks for real-time analysis of electrocardiography recorded with wearable textile sensors
In conclusion, 5G cellular networks in combination with edge devices are a suitable infrastructure for continuous vital sign analysis using deep learning models.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
