Abstract: A machine learning method predicts whether a specified subject is at high risk of developing cognitive impairment based upon a data record for said specified subject, and a method of training a dual neural network for such. These methods may work by automatically classifying said subject into a first class associated with a first predicted risk of cognitive impairment or a second class associated with a second predicted risk of cognitive impairment. Subject records are obtained comprising a first set of measured data and a second set of data including results for two or more health assessment questionnaires; and a label indicating that the subject belongs to the first class or second class. These records are used to train first and second neural networks, and in the latter method these trained networks are able to predict whether a specified subject should belong to said first class or second class.