Detecting neurodegenerative disorders from web search signals.

Journal Article (Journal Article)

Neurodegenerative disorders, such as Parkinson's disease (PD) and Alzheimer's disease (AD), are important public health problems warranting early detection. We trained machine-learned classifiers on the longitudinal search logs of 31,321,773 search engine users to automatically detect neurodegenerative disorders. Several digital phenotypes with high discriminatory weights for detecting these disorders are identified. Classifier sensitivities for PD detection are 94.2/83.1/42.0/34.6% at false positive rates (FPRs) of 20/10/1/0.1%, respectively. Preliminary analysis shows similar performance for AD detection. Subject to further refinement of accuracy and reproducibility, these findings show the promise of web search digital phenotypes as adjunctive screening tools for neurodegenerative disorders.

Full Text

Duke Authors

Cited Authors

  • White, RW; Doraiswamy, PM; Horvitz, E

Published Date

  • 2018

Published In

Volume / Issue

  • 1 /

Start / End Page

  • 8 -

PubMed ID

  • 31304293

Pubmed Central ID

  • PMC6550228

Electronic International Standard Serial Number (EISSN)

  • 2398-6352

Digital Object Identifier (DOI)

  • 10.1038/s41746-018-0016-6

Language

  • eng

Conference Location

  • England