The ‘Digital Twin’ to enable the vision of precision cardiology
University of Oxford · British Heart Foundation · +18 more institutions
Abstract
Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about individual patients. In this position paper, we argue that the second enabling pillar towards this vision is the increasing power of computers and algorithms to learn, reason, and build the 'digital twin' of a patient. Computational models are boosting the capacity to draw diagnosis and prognosis, and future treatments will be tailored not only to current health status and data, but also to an accurate projection of the pathways to restore health by model predictions. The early steps of the digital twin in the area of cardiovascular medicine are reviewed in this…
Citation impact
- FWCI
- 55.87
- Percentile
- 100%
- References
- 91
Authors
39Topics & keywords
- Medicine
- Boosting (machine learning)
- Precision medicine
- Data science
- Position paper
- Pillar
- Machine learning
- Digital health
Funding
- WTWellcome TrustAwards: 203148/Z/16/Z, Z/17/Z, 214290/Z/18/Z, NC/P001076/1, 209450/Z/17, 203148, WT 203148/Z/16/Z, 209450/Z/17/Z
- BHBritish Heart FoundationAwards: 214290/Z/18/Z, WT 203148/Z/16/Z, RE/13/1/30181, 209450/Z/17/Z, RG/16/14/32397, NC/P001076/1, 638284, PG/16/75/32383, TG/17/3/33406
- ANAgence Nationale de la RechercheAwards: ANR-10-IAHU-04, ANR-10, 10-IAHU-04
- EAEngineering and Physical Sciences Research CouncilAwards: WT 203148/Z/16/Z, 764738, WT 203148/Z/16/, 203148/Z/16/Z
- CFCentre For Medical Engineering, King’s College LondonAwards: ANR-10-IAHU-04, 203148/Z/16/Z, WT 203148/Z/16/Z