The following publications are possibly variants of this publication:
- Evaluation of Machine-Learning Approaches to Estimate Sleep Apnea Severity From At-Home Oximetry RecordingsGonzalo C. Gutiérrez-Tobal, Daniel Álvarez, Andrea Crespo, Félix del Campo, Roberto Hornero. titb, 23(2):882-892, 2019. [doi]
- Automatic Assessment of Pediatric Sleep Apnea Severity Using Overnight Oximetry and Convolutional Neural NetworksFernando Vaquerizo-Villar, Daniel Álvarez, Leila Kheirandish-Gozal, Gonzalo C. Gutiérrez-Tobal, Javier Gomez-Pilar, Andrea Crespo, Félix del Campo, David Gozal, Roberto Hornero. embc 2020: 633-636 [doi]
- Analysis and classification of oximetry recordings to predict obstructive sleep apnea severity in childrenGonzalo C. Gutiérrez-Tobal, Leila Kheirandish-Gozal, Daniel Álvarez, Andrea Crespo, Mona F. Philby, Meelad Mohammadi, Félix del Campo, David Gozal, Roberto Hornero. embc 2015: 4540-4543 [doi]
- Diagnosis of pediatric obstructive sleep apnea: Preliminary findings using automatic analysis of airflow and oximetry recordings obtained at patients' homeGonzalo C. Gutiérrez-Tobal, M. Luz Alonso-Álvarez, Daniel Álvarez, Félix del Campo, Joaquín Terán-Santos, Roberto Hornero. bspc, 18:401-407, 2015. [doi]
- Prospective evaluation of logistic regression models from overnight oximetry to assist in sleep apnea diagnosisDaniel Álvarez, Roberto Hornero, J. Víctor Marcos, Thomas Penzel, Félix del Campo, Niels Wessel. isda 2011: 920-924 [doi]