Fig. 2.

Method of selection of participants for creating a test data set and a training data set from the FHS data. The available data consisted of 3113 samples from 1254 participants, 486 of which have been reviewed by a panel for dementia status. The participants who were reviewed by the panel were candidates for creating a test data set. Their samples were eliminated according to the inclusion criteria, and then the qualifying samples were passed through age, education and gender matching. This resulted in a test set of 80 samples. The participants who were not reviewed by the dementia review panel were used for creating a larger weakly-labeled data set, only for the purpose of machine learning training. Validation of predictive modeling consisted of the hold-out method (train on weak-labels, test on ground-truth), and cross-validation (train on ground-truth, test on ground-truth). .