JMIR Publications

ABSTRACT

Background:

The concept of digital twins, widely adopted in industry, is entering healthcare. However, there is a lack of consensus on what constitutes the digital twin of a patient.

Objective:

The objective of this scoping review was to analyse definitions and characteristics of patient digital twins being developed for clinical use, as reported in the scientific literature.

Methods:

We searched PubMed, Scopus, Embase, IEEE, and Google Scholar for studies claiming digital twin development/evaluation until August 2023. Data on definitions, characteristics, and development phase were extracted. Unsupervised classification of claimed digital twins was performed.

Results:

We identified 86 articles representing 80 unique claimed digital twins, with 98% in preclinical phases. Based on the analysis, we propose to define a patient digital twin as "a viewable digital replica of a patient, organ, or biological system that contains multidimensional, patient-specific information". Two main forms were found: simulation digital twins using computational modeling for personalised predictions and therapy evaluations, mostly for one-time assessments; and monitoring digital twins harnessing aggregated patient data for continuous risk/outcome forecasting and care optimization.

Conclusions:

As patient digital twins rapidly emerge, the proposed definitions and subtypes offer a framework to guide research into realizing the potential of these personalised, integrative technologies to advance clinical care.