Clinical validation of MyCog Mobile: development of a parsimonious and clinically interpretable prediction model for mild cognitive impairment

The final model prioritized parsimony to reduce patient burden while maintaining clinical accuracy to detect MCI. Stability across traditional regression and regularized regression approaches from the statistical learning literature indicated a robust predictive signal. Findings support MyCog Mobile as an accurate and accessible cognitive screener able to detect the earliest signs of cognitive impairment in primary care.