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Analysis and classification of oximetry recordings to predict obstructive sleep apnea severity in children., , , , , , , , and . EMBC, page 4540-4543. IEEE, (2015)Exploring the spectral information of airflow recordings to help in pediatric Obstructive Sleep Apnea-Hypopnea Syndrome diagnosis., , , , , and . EMBC, page 2298-2301. IEEE, (2014)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)Machine learning for nocturnal diagnosis of chronic obstructive pulmonary disease using digital oximetry biomarkers., , , and . CoRR, (2020)Usefulness of Spectral Analysis of Respiratory Rate Variability to Help in Pediatric Sleep Apnea-Hypopnea Syndrome Diagnosis., , , , , , , and . EMBC, page 4580-4583. IEEE, (2019)Convolutional Neural Networks to Detect Pediatric Apnea-Hypopnea Events from Oximetry., , , , , , , and . EMBC, page 3555-3558. IEEE, (2019)Usefulness of recurrence plots from airflow recordings to aid in paediatric sleep apnoea diagnosis., , , , , , , , and . Comput. Methods Programs Biomed., (2020)Utility of bispectrum in the screening of pediatric sleep apnea-hypopnea syndrome using oximetry recordings., , , , , , , , and . Comput. Methods Programs Biomed., (2018)Assessment of spectral bands of interest in airflow signal to assist in sleep apnea-hypopnea syndrome diagnosis., , , , and . EMBC, page 5021-5024. IEEE, (2013)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)