Key takeaways: One model used approximately 106 features to predict OSA, whereas the other only used four. Receiver operating characteristic areas under the curves were above 0.7 for predicting any OSA and moderate-severe OSA. Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP 2026 Annual Meeting.