Using Under-Trained Deep Ensembles to Learn under Extreme Label Noise: A Case Study for Sleep Apnea Detection

• Main Authors: Nikolaidis, Konstantinos, Plagemann, Thomas, Kristiansen, Stein, Goebel, Vera, Kankanhalli, Mohan
• Other Authors: DEPARTMENT OF INFORMATION SYSTEMS AND ANALYTICS
• Format: Article
• Published: Institute of Electrical and Electronics Engineers Inc. 2022
• Subjects: Biomedical informatics; label noise; machine learning; sleep apnea; supervised learning
• Online Access: https://scholarbank.nus.edu.sg/handle/10635/232870
• Institution: National University of Singapore

10.1109/access.2021.3067455