Deep Digital Phenotyping and Digital Twins for Precision Health: Time to Dig Deeper
Author(s) -
Guy Fagherazzi
Publication year - 2019
Publication title -
journal of medical internet research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.446
H-Index - 142
eISSN - 1439-4456
pISSN - 1438-8871
DOI - 10.2196/16770
Subject(s) - digital health , data science , computer science , dig , scale (ratio) , precision medicine , health care , world wide web , medicine , cartography , geography , pathology , economics , economic growth
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.
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