A consensus statement on the use of digital twins in medicine
Abstract Digital Health Technologies represent a marked shift from current medical technologies in use, the approach to health and healthcare and stakeholders engaged in healthcare delivery. What the digitalized future of medicine will look like and how it should be governed is unclear. A participat...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-025-01897-4 |
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| author | Jeffrey David Iqbal Michael Krauthammer Claudia M. Witt Nikola Biller-Andorno Markus Christen |
| author_facet | Jeffrey David Iqbal Michael Krauthammer Claudia M. Witt Nikola Biller-Andorno Markus Christen |
| author_sort | Jeffrey David Iqbal |
| collection | DOAJ |
| description | Abstract Digital Health Technologies represent a marked shift from current medical technologies in use, the approach to health and healthcare and stakeholders engaged in healthcare delivery. What the digitalized future of medicine will look like and how it should be governed is unclear. A participatory process with interdisciplinary expert groups developed scenarios of Artificial Intelligence use in medicine and recommendations on their governance. The process included a patient-consumer focus group and the recommendations were validated by a representative population survey in Switzerland. Digital twins were identified as a pivotal innovation for personalized healthcare, with 62% of the Swiss population expressing interest, though 87% oppose mandatory use. Additionally, 75% view the state as responsible for ensuring necessary infrastructure. Digital twins are seen as an opportunity to support both the healthcare provider as well as patient-consumer directly in different modes of use and along functions, prevention, diagnosis, prognosis, and therapy. |
| format | Article |
| id | doaj-art-8bcbcd2b8e30424f876a5c4e15a4ab53 |
| institution | Kabale University |
| issn | 2398-6352 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj-art-8bcbcd2b8e30424f876a5c4e15a4ab532025-08-20T03:46:12ZengNature Portfolionpj Digital Medicine2398-63522025-07-01811810.1038/s41746-025-01897-4A consensus statement on the use of digital twins in medicineJeffrey David Iqbal0Michael Krauthammer1Claudia M. Witt2Nikola Biller-Andorno3Markus Christen4Digital Society Initiative, University of ZurichDigital Society Initiative, University of ZurichDigital Society Initiative, University of ZurichDigital Society Initiative, University of ZurichDigital Society Initiative, University of ZurichAbstract Digital Health Technologies represent a marked shift from current medical technologies in use, the approach to health and healthcare and stakeholders engaged in healthcare delivery. What the digitalized future of medicine will look like and how it should be governed is unclear. A participatory process with interdisciplinary expert groups developed scenarios of Artificial Intelligence use in medicine and recommendations on their governance. The process included a patient-consumer focus group and the recommendations were validated by a representative population survey in Switzerland. Digital twins were identified as a pivotal innovation for personalized healthcare, with 62% of the Swiss population expressing interest, though 87% oppose mandatory use. Additionally, 75% view the state as responsible for ensuring necessary infrastructure. Digital twins are seen as an opportunity to support both the healthcare provider as well as patient-consumer directly in different modes of use and along functions, prevention, diagnosis, prognosis, and therapy.https://doi.org/10.1038/s41746-025-01897-4 |
| spellingShingle | Jeffrey David Iqbal Michael Krauthammer Claudia M. Witt Nikola Biller-Andorno Markus Christen A consensus statement on the use of digital twins in medicine npj Digital Medicine |
| title | A consensus statement on the use of digital twins in medicine |
| title_full | A consensus statement on the use of digital twins in medicine |
| title_fullStr | A consensus statement on the use of digital twins in medicine |
| title_full_unstemmed | A consensus statement on the use of digital twins in medicine |
| title_short | A consensus statement on the use of digital twins in medicine |
| title_sort | consensus statement on the use of digital twins in medicine |
| url | https://doi.org/10.1038/s41746-025-01897-4 |
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