Concepts and applications of digital twins in healthcare and medicine.

Journal

Patterns (New York, N.Y.)
ISSN: 2666-3899
Titre abrégé: Patterns (N Y)
Pays: United States
ID NLM: 101767765

Informations de publication

Date de publication:
09 Aug 2024
Historique:
medline: 5 9 2024
pubmed: 5 9 2024
entrez: 5 9 2024
Statut: epublish

Résumé

The digital twin (DT) is a concept widely used in industry to create digital replicas of physical objects or systems. The dynamic, bi-directional link between the physical entity and its digital counterpart enables a real-time update of the digital entity. It can predict perturbations related to the physical object's function. The obvious applications of DTs in healthcare and medicine are extremely attractive prospects that have the potential to revolutionize patient diagnosis and treatment. However, challenges including technical obstacles, biological heterogeneity, and ethical considerations make it difficult to achieve the desired goal. Advances in multi-modal deep learning methods, embodied AI agents, and the metaverse may mitigate some difficulties. Here, we discuss the basic concepts underlying DTs, the requirements for implementing DTs in medicine, and their current and potential healthcare uses. We also provide our perspective on five hallmarks for a healthcare DT system to advance research in this field.

Identifiants

DOI: 10.1016/j.patter.2024.101028 PMID: 39233690 PMC: PMC11368703
pubmed: 39233690
doi: 10.1016/j.patter.2024.101028
pii: S2666-3899(24)00161-2
pmc: PMC11368703
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

101028

Informations de copyright

© 2024 The Authors.

Déclaration de conflit d'intérêts

The authors declare no competing interests.

Auteurs

Kang Zhang (K)

National Clinical Eye Research Center, Eye Hospital, Wenzhou Medical University, Wenzhou 325000, China.
Institute for Clinical Data Science, Wenzhou Medical University, Wenzhou 325000, China.
Institute for AI in Medicine and Faculty of Medicine, Macau University of Science and Technology, Macau 999078, China.
Institute for Advanced Study on Eye Health and Diseases, Wenzhou Medical University, Wenzhou 325000, China.

Hong-Yu Zhou (HY)

Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02138, USA.

Daniel T Baptista-Hon (DT)

Institute for AI in Medicine and Faculty of Medicine, Macau University of Science and Technology, Macau 999078, China.
School of Medicine, University of Dundee, DD1 9SY Dundee, UK.

Yuanxu Gao (Y)

Department of Big Data and Biomedical AI, College of Future Technology, Peking University, Beijing 100000, China.

Xiaohong Liu (X)

Cancer Institute, University College London, WC1E 6BT London, UK.

Eric Oermann (E)

NYU Langone Medical Center, New York University, New York, NY 10016, USA.

Sheng Xu (S)

Department of Chemical Engineering and Nanoengineering, University of California San Diego, San Diego, CA 92093, USA.

Shengwei Jin (S)

Institute for Clinical Data Science, Wenzhou Medical University, Wenzhou 325000, China.
Department of Anesthesia and Critical Care, The Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou 325000, China.

Jian Zhang (J)

National Clinical Eye Research Center, Eye Hospital, Wenzhou Medical University, Wenzhou 325000, China.
Department of Anesthesia and Critical Care, The Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou 325000, China.

Zhuo Sun (Z)

Institute for Advanced Study on Eye Health and Diseases, Wenzhou Medical University, Wenzhou 325000, China.

Yun Yin (Y)

Faculty of Business and Health Science Institute, City University of Macau, Macau 999078, China.

Ronald M Razmi (RM)

Zoi Capital, New York, NY 10013, USA.

Alexandre Loupy (A)

Université Paris Cité, INSERM U970 PARCC, Paris Institute for Transplantation and Organ Regeneration, 75015 Paris, France.

Stephan Beck (S)

Cancer Institute, University College London, WC1E 6BT London, UK.

Jia Qu (J)

National Clinical Eye Research Center, Eye Hospital, Wenzhou Medical University, Wenzhou 325000, China.
Institute for Clinical Data Science, Wenzhou Medical University, Wenzhou 325000, China.

Joseph Wu (J)

Cardiovascular Research Institute, Stanford University, Standford, CA 94305, USA.

Classifications MeSH