Douglas Scharre
The goal of this observational trial is to leverage the electronic Self-Administered Gerocognitive Examination (eSAGE), a variety of metadata (a set of data that describes and gives information about other data) collected during eSAGE testing, electronic health records (EHR) information, and advanced machine learning (ML) techniques to develop a new tool that can aid in early-stage prediction of individuals with cognitive impairments.
This is a retrospective and prospective record review trial for patients who are followed at the Center for Cognitive and Memory Disorders. eSAGE assessment data (including cognitive data, behavioral data, timing data and other metadata) as well as varying amount of electronic health records (EHR) data will be collected on all eligible subjects. Machine learning techniques with feature selection will identify important EHR variables to determine what may be useful for the prediction of cognitive impairment. Based on the EHR analysis additional questions will be added to the eSAGE to make an…
Inclusion Criteria: * 1\. Males and females 50 years of age and over who complete the eSAGE as part of their office visit at the Center for Cognitive and Memory Disorders. Exclusion Criteria: * None
A self-administered digital assessment that evaluates multiple cognitive domains: orientation, language, memory, executive function, calculations, abstraction, and visuospatial abilities, through multiple questions. Additionally, it includes the collection of six clinical variables: education, gender, race, family history of dementia, stroke, and emotion.
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