Deep digital phenotyping and digital twins for precision health: Time to dig deeper

Guy Fagherazzi*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

17 Citations (Scopus)

Abstract

This viewpoint describes the urgent need for more large-scale, deep digital phenotyping to advance toward precision health. It describes why and how to combine real-world digital data with clinical data and omics features to identify someone’s digital twin, and how to finally enter the era of patient-centered care and modify the way we view disease management and prevention.

Original languageEnglish
Article numbere16770
JournalJournal of Medical Internet Research
Volume22
Issue number3
DOIs
Publication statusPublished - Mar 2020

Keywords

  • Big data
  • Data lake
  • Deep digital phenotyping
  • Digital cohort
  • Digital epidemiology
  • Digital health
  • Digital orthodoxy
  • Digital phenotyping
  • Digitosome
  • Omics
  • Personalized medicine
  • Precision health
  • Precision medicine
  • Precision prevention

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