Related Experiment Video
Updated: Jun 10, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Predicting conversion from mild cognitive impairment to Alzheimer's disease using neuropsychological tests and
Robert M Chapman1, Mark Mapstone, John W McCrary
1Brain and Cognitive Sciences and Center for Visual Science, University of Rochester, Rochester, NY 14627–0270, USA. rmc@cvs.rochester.edu
None:
Behavioral markers measured through neuropsychological testing in mild cognitive impairment (MCI) were analyzed and combined in multivariate ways to predict conversion to Alzheimer's disease (AD) in a longitudinal study of 43 MCI patients. The test measures taken at a baseline evaluation were first reduced to underlying components (principal component analysis, PCA), and then the component scores were used in discriminant analysis to classify MCI individuals as likely to convert or not. When empirically weighted and combined, episodic memory, speeded executive functioning, recognition memory (false and true positives), visuospatial memory processing speed, and visuospatial episodic memory were together strong predictors of conversion to AD. These multivariate combinations of the test measures achieved through the PCA were good, statistically significant predictors of MCI conversion to AD (84% accuracy, 86% sensitivity, and 83% specificity). Importantly, the posterior probabilities of group membership that accompanied the binary prediction for each participant indicated the confidence of the prediction. Most of the participants (81%) were in the highly confident probability bins (.70-1.00), where the obtained prediction accuracy was more than 90%. The strength and reliability of this multivariate prediction method were tested by cross-validation and randomized resampling.
More Related Videos
06:23The 4 Mountains Test: A Short Test of Spatial Memory with High Sensitivity for the Diagnosis of Pre-dementia Alzheimer's Disease
Published on: October 13, 2016
08:43Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
Published on: August 7, 2017
Related Concept Videos
Alzheimer Disease l: Introduction
Alzheimer's Disease: Overview
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ and tau...
Dementia l: Introduction
Alzheimer Disease ll: Pathophysiology