Using data science to diagnose and characterize heterogeneity of Alzheimer's disease.

ABSTRACT:

Introduction

Despite the availability of age- and education-adjusted standardized scores for most neuropsychological tests, there is a lack of objective rules in how to interpret multiple concurrent neuropsychological test scores that characterize the heterogeneity of Alzheimer's disease.

Methods

Using neuropsychological test scores of 2091 participants from the Framingham Heart Study, we devised an automated algorithm that follows general diagnostic criteria and explores the heterogeneity of Alzheimer's disease.

Results

We developed a series of stepwise diagnosis rules that evaluate information from multiple neuropsychological tests to produce an intuitive and objective Alzheimer's disease dementia diagnosis with more than 80% accuracy.

Discussion

A data-drive

SUBMITTER: Ang TFA 

PROVIDER: S-EPMC6603309 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature