Related Experiment Video
Updated: Feb 15, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Predicting progression from normal cognition to mild cognitive impairment for individuals at 5 years
Marilyn Albert1, Yuxin Zhu2, Abhay Moghekar1
1Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Abstract:
Recent evidence indicates that measures from cerebrospinal fluid, MRI scans and cognitive testing obtained from cognitively normal individuals can be used to predict likelihood of progression to mild cognitive impairment several years later, for groups of individuals. However, it remains unclear whether these measures are useful for predicting likelihood of progression for an individual. The increasing focus on early intervention in clinical trials for Alzheimer's disease emphasizes the importance of improving the ability to identify which cognitively normal individuals are more likely to progress over time, thus allowing researchers to efficiently screen participants, as well as determine the efficacy of any treatment intervention. The goal of this study was to determine which measures, obtained when individuals were cognitively normal, predict on an individual basis, the onset of clinical symptoms associated with a diagnosis of mild cognitive impairment due to Alzheimer's disease. Cognitively normal participants (n = 224, mean baseline age = 57 years) were evaluated with a range of measures, including: cerebrospinal fluid amyloid-β and phosphorylated-tau, hippocampal and entorhinal cortex volume, cognitive tests scores and APOE genotype. They were then followed to determine which individuals developed mild cognitive impairment over time (mean follow-up = 11 years). The primary outcome was progression from normal cognition to the onset of clinical symptoms of mild cognitive impairment due to Alzheimer's disease at 5 years post-baseline. Time-dependent receiver operating characteristic analyses examined the sensitivity and specificity of individual measures, and combinations of measures, as predictors of the outcome. Six measures, in combination, were the most parsimonious predictors of transition to mild cognitive impairment 5 years after baseline (area under the curve = 0.85; sensitivity = 0.80, specificity = 0.75). The addition of variables from each domain significantly improved the accuracy of prediction. The incremental accuracy of prediction achieved by adding individual measures or sets of measures successively to one another was also examined, as might be done when enrolling individuals in a clinical trial. The results indicate that biomarkers obtained when individuals are cognitively normal can be used to predict which individuals are likely to develop clinical symptoms at 5 years post-baseline. As a number of the measures included in the study could also be used as subject selection criteria in a clinical trial, the findings also provide information about measures that would be useful for screening in a clinical trial aimed at individuals with preclinical Alzheimer's disease.
More Related Videos
Related Concept Videos
Cognitive Dissonance
Language and Cognition
Cognitive Therapy
Cognition and Behavior
Cognitive Learning
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
Introduction to Cognitive Psychology
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...

