Detection of Intra-beat Waves on Ambulatory ECG: Interpretable Deep Learning Approaches
In this lecture, we will explore signal processing and artificial intelligence techniques for detecting intra-beat waves in long-term electrocardiogram (ECG) signals. A particular focus will be placed on the interpretability of deep learning models, such as transformers, which is crucial in the healthcare field to ensure that clinicians can trust and rely on the results.
Date and Time
Location
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Registration
- Date: 25 Sep 2024
- Time: 10:00 AM to 11:00 AM
- All times are (UTC+02:00) Zagreb
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- University of Zagreb Faculty of Electrical Engineering and Computing
- Unska 3
- Zagreb, Grad Zagreb
- Croatia 10000
- Building: D
- Room Number: D033
- Click here for Map
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- Co-sponsored by University of Zagreb Faculty of Electrical Engineering and Computing
Speakers
Carmen Plaza Seco of Universidad de Alcalá
Detection of Intra–beat Waves on Ambulatory ECG: Interpretable Deep Learning Approaches
In this lecture, we will explore signal processing and artificial intelligence techniques for detecting intra-beat waves in long-term electrocardiogram (ECG) signals. A particular focus will be placed on the interpretability of deep learning models, such as transformers, which is crucial in the healthcare field to ensure that clinicians can trust and rely on the results.
Biography:
Carmen Plaza Seco is a PhD student at the University of Alcalá, Madrid, Spain. She graduated in Biomedical Engineering in 2020 and completed her MSc in Computational Intelligence and Interactive Systems at the Autonomous University of Madrid in 2021. Her current research focuses on the development of learning-based techniques for the characterization of long-term electrocardiographic signals. She is also collaborating with the University of Delaware in the United States as part of her PhD work.
Email:
Address:Universidad de Alcalá, Pza. San Diego, s/n, Alcalá de Henares, Madrid, Spain, 28801