Digital twins for chronic lung diseases

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 in...

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Main Authors: Apolline Gonsard, Martin Genet, David Drummond
Format: Article
Language:English
Published: European Respiratory Society 2024-12-01
Series:European Respiratory Review
Online Access:http://err.ersjournals.com/content/33/174/240159.full
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author Apolline Gonsard
Martin Genet
David Drummond
author_facet Apolline Gonsard
Martin Genet
David Drummond
author_sort Apolline Gonsard
collection DOAJ
description 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.
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spelling doaj-art-7dd6eaaabd124d5bb97e016ddbd0da0c2025-08-20T02:42:57ZengEuropean Respiratory SocietyEuropean Respiratory Review0905-91801600-06172024-12-013317410.1183/16000617.0159-20240159-2024Digital twins for chronic lung diseasesApolline Gonsard0Martin Genet1David Drummond2 Department of Pediatric Pulmonology and Allergology, University Hospital Necker-Enfants Malades, AP-HP, Paris, France École Polytechnique/CNRS/Institut Polytechnique de Paris, Palaiseau, France Department of Pediatric Pulmonology and Allergology, University Hospital Necker-Enfants Malades, AP-HP, Paris, France 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.http://err.ersjournals.com/content/33/174/240159.full
spellingShingle Apolline Gonsard
Martin Genet
David Drummond
Digital twins for chronic lung diseases
European Respiratory Review
title Digital twins for chronic lung diseases
title_full Digital twins for chronic lung diseases
title_fullStr Digital twins for chronic lung diseases
title_full_unstemmed Digital twins for chronic lung diseases
title_short Digital twins for chronic lung diseases
title_sort digital twins for chronic lung diseases
url http://err.ersjournals.com/content/33/174/240159.full
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AT martingenet digitaltwinsforchroniclungdiseases
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