Automatic identification of, and responding to, cognition impairment

Abstract

Aspects of the present disclosure are directed to a cognition analysis and response system that can A) generate machine learning training data and use it to build a cognitive impairment machine learning model; B) identify cognitive impairments by applying the cognitive impairment machine learning model and performing a false positive/false negative analysis; and C) apply various automated adaptive measures for users with identified cognitive impairment. The cognition analysis and response system can apply the cognitive impairment machine learning model and can analyze these results to identify false positive and false negative cognitive impairment determinations by analyzing result confidence values, determining whether the result matches an expected progression of cognitive impairment, and/or analyzing external factors which may have caused incorrect results. The cognition analysis and response system can then validate or invalidate the result or exclude or apply weighting factors to parts of the input before regenerating the result.