1. Applied Machine Learning

Machine learning approaches for predicting sleep arousal response based on heart rate variability, oxygen saturation, and body profiles, Digital Health, 2023.

Screening the risk of obstructive sleep apnea by utilizing supervised learning techniques based on anthropometric features and snoring events, Digital Health, 2023.

Prediction of posttraumatic functional recovery in middle-aged and older patients through dynamic ensemble selection modeling, Frontiers in Public Health, 2023.

Machine learning approaches for screening the risk of obstructive sleep apnea in the Taiwan population based on body profile, Informatics for Health and Social Care, 2022.

Screening for Obstructive Sleep Apnea Risk by Using Machine Learning Approaches and Anthropometric Features, Sensors, 2022.

Differentiation model for insomnia disorder and the respiratory arousal threshold phenotype in obstructive sleep apnea in the taiwanese population based on oximetry and anthropometric features, Diagnostics, 2021.