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Digital Twins as Global Learning Health and Disease Models of Individuals

Year: 2024

Type: preprint

Abstract: Emerging molecular and computational techniques may allow construction and computational treatment of dynamic digital twins on the scale of populations to individuals. This approach may pave the way for predictive, preventive, and personalized treatment. Because digital twins are independent of geographical location, this may also contribute to global equitable health.

Source: Preprints.org

DOI: 10.20944/preprints202406.0357.v1

Authors: Xinxiu Li, Joseph Loscalzo, AKM Firoj Mahmud, Dina Mansour Aly Aly, Andrey Rzhetsky, Marinka Zitnik, Mikael Benson

Institutions: Karolinska Institutet, Brigham and Women's Hospital, Harvard University, University of Chicago, Broad Institute

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W4399436403

Cites: 28

Cited by: 3

Related to: 10