Fig. 5: Machine learning pipeline for predicting cognitive impairment in Parkinson’s disease. | npj Digital Medicine

Fig. 5: Machine learning pipeline for predicting cognitive impairment in Parkinson’s disease.

From: Multi-cohort machine learning identifies predictors of cognitive impairment in Parkinson’s disease

Fig. 5: Machine learning pipeline for predicting cognitive impairment in Parkinson’s disease.The alternative text for this image may have been generated using AI.

Machine learning analysis pipeline for predicting cognitive impairment in Parkinson’s Disease. Schematic representation of the data processing and analysis workflow. Input data from three independent cohorts (LuxPARK, PPMI, and ICEBERG) is pre-processed and then analyzed using both single-cohort and multi-cohort approaches. These analyses are applied to predict both mild cognitive impairment (PD-MCI) and subjective cognitive decline (SCD) outcomes in Parkinson’s disease. The models are evaluated using cross-validation, decision curve and calibration analyses.

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