Automatic prediction of obstructive sleep apnea in patients with temporomandibular disorder based on multidata and machine learning.

Although the n number included in the training set (n = 44) and test set (n = 11) was limited, it was quite significant with AUC = 0.800 (95% CI 0.40–1.00, p < 0.001), sensitivity 1.00, and specificity 0.80 (Fig. 5 ).

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