Cargando…
The Digital Twin in Medicine: A Key to the Future of Healthcare?
There is a growing need for precise diagnosis and personalized treatment of disease in recent years. Providing treatment tailored to each patient and maximizing efficacy and efficiency are broad goals of the healthcare system. As an engineering concept that connects the physical entity and digital s...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9330225/ https://www.ncbi.nlm.nih.gov/pubmed/35911407 http://dx.doi.org/10.3389/fmed.2022.907066 |
_version_ | 1784758110950260736 |
---|---|
author | Sun, Tianze He, Xiwang Song, Xueguan Shu, Liming Li, Zhonghai |
author_facet | Sun, Tianze He, Xiwang Song, Xueguan Shu, Liming Li, Zhonghai |
author_sort | Sun, Tianze |
collection | PubMed |
description | There is a growing need for precise diagnosis and personalized treatment of disease in recent years. Providing treatment tailored to each patient and maximizing efficacy and efficiency are broad goals of the healthcare system. As an engineering concept that connects the physical entity and digital space, the digital twin (DT) entered our lives at the beginning of Industry 4.0. It is evaluated as a revolution in many industrial fields and has shown the potential to be widely used in the field of medicine. This technology can offer innovative solutions for precise diagnosis and personalized treatment processes. Although there are difficulties in data collection, data fusion, and accurate simulation at this stage, we speculated that the DT may have an increasing use in the future and will become a new platform for personal health management and healthcare services. We introduced the DT technology and discussed the advantages and limitations of its applications in the medical field. This article aims to provide a perspective that combining Big Data, the Internet of Things (IoT), and artificial intelligence (AI) technology; the DT will help establish high-resolution models of patients to achieve precise diagnosis and personalized treatment. |
format | Online Article Text |
id | pubmed-9330225 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93302252022-07-29 The Digital Twin in Medicine: A Key to the Future of Healthcare? Sun, Tianze He, Xiwang Song, Xueguan Shu, Liming Li, Zhonghai Front Med (Lausanne) Medicine There is a growing need for precise diagnosis and personalized treatment of disease in recent years. Providing treatment tailored to each patient and maximizing efficacy and efficiency are broad goals of the healthcare system. As an engineering concept that connects the physical entity and digital space, the digital twin (DT) entered our lives at the beginning of Industry 4.0. It is evaluated as a revolution in many industrial fields and has shown the potential to be widely used in the field of medicine. This technology can offer innovative solutions for precise diagnosis and personalized treatment processes. Although there are difficulties in data collection, data fusion, and accurate simulation at this stage, we speculated that the DT may have an increasing use in the future and will become a new platform for personal health management and healthcare services. We introduced the DT technology and discussed the advantages and limitations of its applications in the medical field. This article aims to provide a perspective that combining Big Data, the Internet of Things (IoT), and artificial intelligence (AI) technology; the DT will help establish high-resolution models of patients to achieve precise diagnosis and personalized treatment. Frontiers Media S.A. 2022-07-14 /pmc/articles/PMC9330225/ /pubmed/35911407 http://dx.doi.org/10.3389/fmed.2022.907066 Text en Copyright © 2022 Sun, He, Song, Shu and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Medicine Sun, Tianze He, Xiwang Song, Xueguan Shu, Liming Li, Zhonghai The Digital Twin in Medicine: A Key to the Future of Healthcare? |
title | The Digital Twin in Medicine: A Key to the Future of Healthcare? |
title_full | The Digital Twin in Medicine: A Key to the Future of Healthcare? |
title_fullStr | The Digital Twin in Medicine: A Key to the Future of Healthcare? |
title_full_unstemmed | The Digital Twin in Medicine: A Key to the Future of Healthcare? |
title_short | The Digital Twin in Medicine: A Key to the Future of Healthcare? |
title_sort | digital twin in medicine: a key to the future of healthcare? |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9330225/ https://www.ncbi.nlm.nih.gov/pubmed/35911407 http://dx.doi.org/10.3389/fmed.2022.907066 |
work_keys_str_mv | AT suntianze thedigitaltwininmedicineakeytothefutureofhealthcare AT hexiwang thedigitaltwininmedicineakeytothefutureofhealthcare AT songxueguan thedigitaltwininmedicineakeytothefutureofhealthcare AT shuliming thedigitaltwininmedicineakeytothefutureofhealthcare AT lizhonghai thedigitaltwininmedicineakeytothefutureofhealthcare AT suntianze digitaltwininmedicineakeytothefutureofhealthcare AT hexiwang digitaltwininmedicineakeytothefutureofhealthcare AT songxueguan digitaltwininmedicineakeytothefutureofhealthcare AT shuliming digitaltwininmedicineakeytothefutureofhealthcare AT lizhonghai digitaltwininmedicineakeytothefutureofhealthcare |