47 citations · 52 across the 4 of their papers we have counts for
4 papers
Pretraining on Sleep Data Improves non-Sleep Biosignal Tasks
William Lehn-Schiøler, Magnus Ruud Kjær, Phillip Hempel +7
Sleep foundation models have recently demonstrated strong performance on in-domain polysomnography tasks, including sleep staging, apnea detection, and disease risk prediction. In…
Benchmarking the Impact of Noise on Deep Learning-based Classification of Atrial Fibrillation in 12-Lead ECG
Theresa Bender, Philip Gemke, Ennio Idrobo-Avila +3
Electrocardiography analysis is widely used in various clinical applications and Deep Learning models for classification tasks are currently in the focus of research. Due to their…
Measurement of Individual Alteration in Perioperative ECGs During Elective Percutaneous Coronary Intervention
Philip Gemke, Theresa Bender, Ennio Idrobo-Avila +4
The increasing availability of wearable electrocardiography (ECG) devices enables the continuous monitoring of individual ECG alterations. This could be beneficial for patients suf…
Analysis of a Deep Learning Model for 12-Lead ECG Classification Reveals Learned Features Similar to Diagnostic Criteria
Theresa Bender, Jacqueline Michelle Beinecke, Dagmar Krefting +5
Despite their remarkable performance, deep neural networks remain unadopted in clinical practice, which is considered to be partially due to their lack in explainability. In this w…