Exploring Interpretable AI Methods for ECG Data Classification
Author:
Affiliation:
1. Computer Science, Oslo Metropolitan University, Norway
Funder
NordSTAR - OsloMet
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3643488.3660294
Reference37 articles.
1. 2022. New Artificial Intelligence Tool Detects Often Overlooked Heart Diseases. https://www.cedars-sinai.org/newsroom/new-artificial-intelligence-tool-detects-often-overlooked-heart-diseases/. [Online; accessed on 19-February-2023].
2. ECG-iCOVIDNet: Interpretable AI model to identify changes in the ECG signals of post-COVID subjects;Agrawal Amulya;Computers in Biology and Medicine,2022
3. Assessment of electrocardiogram interpretation competency among healthcare professionals and students of Ardabil University of Medical Sciences: a multidisciplinary study;Amini Keyvan;BMC Medical Education,2022
4. Explainable AI decision model for ECG data of cardiac disorders
5. An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction
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