{"title":"Digital twins for chronic lung diseases.","authors":"Apolline Gonsard, Martin Genet, David Drummond","doi":"10.1183/16000617.0159-2024","DOIUrl":null,"url":null,"abstract":"<p><p>Digital twins have recently emerged in healthcare. They combine advances in cyber-physical systems, modelling and computation techniques, and enable a bidirectional flow of information between the physical and virtual entities. In respiratory medicine, progress in connected devices and artificial intelligence make it technically possible to obtain digital twins that allow real-time visualisation of a patient's respiratory health. Advances in respiratory system modelling also enable the development of digital twins that could be used to predict the effectiveness of different therapeutic approaches for a patient. For researchers, digital twins could lead to a better understanding of the gene-environment-time interactions involved in the development of chronic respiratory diseases. For clinicians and patients, they could facilitate personalised and timely medicine, by enabling therapeutic adaptations specific to each patient and early detection of disease progression. The objective of this review is to allow the reader to explore the concept of digital twins, their feasibility in respiratory medicine, their potential benefits and the challenges to their implementation.</p>","PeriodicalId":12166,"journal":{"name":"European Respiratory Review","volume":"33 174","pages":""},"PeriodicalIF":9.0000,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Respiratory Review","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1183/16000617.0159-2024","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/1 0:00:00","PubModel":"Print","JCR":"Q1","JCRName":"RESPIRATORY SYSTEM","Score":null,"Total":0}
引用次数: 0
Abstract
Digital twins have recently emerged in healthcare. They combine advances in cyber-physical systems, modelling and computation techniques, and enable a bidirectional flow of information between the physical and virtual entities. In respiratory medicine, progress in connected devices and artificial intelligence make it technically possible to obtain digital twins that allow real-time visualisation of a patient's respiratory health. Advances in respiratory system modelling also enable the development of digital twins that could be used to predict the effectiveness of different therapeutic approaches for a patient. For researchers, digital twins could lead to a better understanding of the gene-environment-time interactions involved in the development of chronic respiratory diseases. For clinicians and patients, they could facilitate personalised and timely medicine, by enabling therapeutic adaptations specific to each patient and early detection of disease progression. The objective of this review is to allow the reader to explore the concept of digital twins, their feasibility in respiratory medicine, their potential benefits and the challenges to their implementation.
期刊介绍：
The European Respiratory Review (ERR) is an open-access journal published by the European Respiratory Society (ERS), serving as a vital resource for respiratory professionals by delivering updates on medicine, science, and surgery in the field. ERR features state-of-the-art review articles, editorials, correspondence, and summaries of recent research findings and studies covering a wide range of topics including COPD, asthma, pulmonary hypertension, interstitial lung disease, lung cancer, tuberculosis, and pulmonary infections. Articles are published continuously and compiled into quarterly issues within a single annual volume.
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