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A Bayesian neural network approach to compare the spectral information from nasal pressure and thermistor airflow in the automatic sleep apnea severity estimation., , , , , , , and . EMBC, page 3741-3744. IEEE, (2017)Utility of bispectrum in the screening of pediatric sleep apnea-hypopnea syndrome using oximetry recordings., , , , , , , , and . Comput. Methods Programs Biomed., (2018)Ensemble-learning regression to estimate sleep apnea severity using at-home oximetry in adults., , , , , , , and . Appl. Soft Comput., (2021)A Modeling Framework for an Innovative e-Health Service: The Hospital at Home., , , , , and . SIMULTECH (Selected Papers), volume 306 of Lecture Notes in Networks and Systems, page 111-132. Springer, (2020)Bispectral Analysis to Enhance Oximetry as a Simplified Alternative for Pediatric Sleep Apnea Diagnosis., , , , , , , , and . EMBC, page 175-178. IEEE, (2018)Automatic Assessment of Pediatric Sleep Apnea Severity Using Overnight Oximetry and Convolutional Neural Networks., , , , , , , , and . EMBC, page 633-636. IEEE, (2020)Automated analysis of nocturnal oximetry as screening tool for childhood obstructive sleep apnea-hypopnea syndrome., , , , , , , , and . EMBC, page 2800-2803. IEEE, (2015)Improving the Diagnostic Ability of Oximetry Recordings in Pediatric Sleep Apnea-Hypopnea Syndrome by Means of Multi-Class AdaBoost., , , , , , , , and . EMBC, page 167-170. IEEE, (2018)Usefulness of discrete wavelet transform in the analysis of oximetry signals to assist in childhood sleep apnea-hypopnea syndrome diagnosis., , , , , , , , and . EMBC, page 3753-3756. IEEE, (2017)Adopting Technological Devices in Hospital at Home: A Modelling and Simulation Perspective., , , , , , , , , and 6 other author(s). SIMULTECH, page 110-119. ScitePress, (2020)