Health digital twins as tools for precision medicine: Considerations for computation, implementation, and regulation.
Kaushik P VenkateshMarium M RazaJoseph C KvedarPublished in: NPJ digital medicine (2022)
Health digital twins are defined as virtual representations ("digital twin") of patients ("physical twin") that are generated from multimodal patient data, population data, and real-time updates on patient and environmental variables. With appropriate use, HDTs can model random perturbations on the digital twin to gain insight into the expected behavior of the physical twin-offering groundbreaking applications in precision medicine, clinical trials, and public health. Main considerations for translating HDT research into clinical practice include computational requirements, clinical implementation, as well as data governance, and product oversight.
Keyphrases
- public health
- healthcare
- mental health
- electronic health record
- clinical trial
- primary care
- end stage renal disease
- clinical practice
- big data
- physical activity
- newly diagnosed
- ejection fraction
- chronic kidney disease
- quality improvement
- global health
- randomized controlled trial
- working memory
- machine learning
- pain management
- peritoneal dialysis
- data analysis
- patient reported outcomes
- climate change
- chronic pain
- phase iii