Development and temporal validation of a machine learning model to estimate total MoCA scores from telephone-based items in patients with mild cognitive impairment.

Findings In the fivefold cross-validation on the training set, the Random Forest model achieved the lowest mean Root Mean Squared Error (RMSE=1.2034) of 1.2034 points (SD=0.0407; 95% CI 1.1528 to 1.2540) for Visual Score prediction, though pairwise differences between models did not reach statistical significance, likely reflecting the limited power of fivefold comparisons.

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