Multi-Class ECG Feature Importance Rankings: Cardiologists vs. Algorithms
Aston, Philip J.; Mehari, Temesgen; Bosnjakovic, Alen; Harris, Peter M.; Sundar, Ashish; Williams, Steven E.; Dössel, Olaf 1; Loewe, Axel
1; Nagel, Claudia 1; Strodthoff, Nils
1 Institut für Biomedizinische Technik (IBT), Karlsruher Institut für Technologie (KIT)
1; Nagel, Claudia 1; Strodthoff, Nils1 Institut für Biomedizinische Technik (IBT), Karlsruher Institut für Technologie (KIT)
Abstract:
Cardiologists have been using electrocardiogram features to diagnose a wide variety of heart conditions for many decades. There are also numerous algorithms that rank feature importance for a particular classification task. However, different algorithms often give quite different feature rankings. Therefore, we compared the feature importance rankings obtained by various algorithms with the features that cardiologists use for diagnosis.
| Zugehörige Institution(en) am KIT | Institut für Biomedizinische Technik (IBT) |
| Publikationstyp | Proceedingsbeitrag |
| Publikationsjahr | 2022 |
| Sprache | Englisch |
| Identifikator | ISBN: 979-83-503-0097-0 ISSN: 2325-887X KITopen-ID: 1000158441 |
| Erschienen in | 2022 Computing in Cardiology Conference (CinC) |
| Veranstaltung | 49th Computing in Cardiology (CinC 2022), Tampere, Finnland, 04.09.2022 – 07.09.2022 |
| Verlag | Institute of Electrical and Electronics Engineers (IEEE) |
| Serie | Computing in Cardiology Conference (CinC) |
| Nachgewiesen in | Dimensions Scopus |