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Detection of Atrial Fibrillation from Short ECGs : Minimalistic Complexity Analysis for Feature-Based Classifiers
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- Abdukalikova, Anara (author)
- Luleå tekniska universitet,Datavetenskap
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- Kleyko, Denis, 1990- (author)
- Luleå tekniska universitet,Datavetenskap
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- Osipov, Evgeny (author)
- Luleå tekniska universitet,Datavetenskap
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- (creator_code:org_t)
- IEEE, 2018
- 2018
- English.
- In: Computing in Cardiology 2018. - : IEEE.
- Conference paper (peer-reviewed)
Abstract
Subject headings
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- In order to facilitate data-driven solutions for early detection of atrial fibrillation (AF), the 2017 CinC conference challenge was devoted to automatic AF classification based on short ECG recordings. The proposed solutions concentrated on maximizing the classifiers F 1 score, whereas the complexity of the classifiers was not considered. However, we argue that this must be addressed as complexity places restrictions on the applicability of inexpensive devices for AF monitoring outside hospitals. Therefore, this study investigates the feasibility of complexity reduction by analyzing one of the solutions presented for the challenge.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Kardiologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cardiac and Cardiovascular Systems (hsv//eng)
Keyword
- Dependable Communication and Computation Systems
- Kommunikations- och beräkningssystem
Publication and Content Type
- ref (subject category)
- kon (subject category)
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