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Cardiovascular models for personalised medicine: Where now and where next?
Hose, D Rodney; Lawford, Patricia V; Huberts, Wouter; Hellevik, Leif Rune; Omholt, Stig W; van de Vosse, Frans N.
Afiliación
  • Hose DR; Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield S10 2TN, UK; Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; Insigneo Institute for in silico Medicine, University of Sheffield, S
  • Lawford PV; Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield S10 2TN, UK; Insigneo Institute for in silico Medicine, University of Sheffield, Sheffield, UK.
  • Huberts W; Department of Biomedical Engineering, Maastricht University, Maastricht, The Netherlands.
  • Hellevik LR; Department of Structural Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
  • Omholt SW; Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
  • van de Vosse FN; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Med Eng Phys ; 72: 38-48, 2019 10.
Article en En | MEDLINE | ID: mdl-31554575
The aim of this position paper is to provide a brief overview of the current status of cardiovascular modelling and of the processes required and some of the challenges to be addressed to see wider exploitation in both personal health management and clinical practice. In most branches of engineering the concept of the digital twin, informed by extensive and continuous monitoring and coupled with robust data assimilation and simulation techniques, is gaining traction: the Gartner Group listed it as one of the top ten digital trends in 2018. The cardiovascular modelling community is starting to develop a much more systematic approach to the combination of physics, mathematics, control theory, artificial intelligence, machine learning, computer science and advanced engineering methodology, as well as working more closely with the clinical community to better understand and exploit physiological measurements, and indeed to develop jointly better measurement protocols informed by model-based understanding. Developments in physiological modelling, model personalisation, model outcome uncertainty, and the role of models in clinical decision support are addressed and 'where-next' steps and challenges discussed.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Medicina de Precisión / Modelos Cardiovasculares Tipo de estudio: Guideline / Prognostic_studies Límite: Humans Idioma: En Revista: Med Eng Phys Asunto de la revista: BIOFISICA / ENGENHARIA BIOMEDICA Año: 2019 Tipo del documento: Article Pais de publicación: Reino Unido
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Medicina de Precisión / Modelos Cardiovasculares Tipo de estudio: Guideline / Prognostic_studies Límite: Humans Idioma: En Revista: Med Eng Phys Asunto de la revista: BIOFISICA / ENGENHARIA BIOMEDICA Año: 2019 Tipo del documento: Article Pais de publicación: Reino Unido