Cardiovascular models for personalised medicine: where now and where next?

D. Rodney Hose (Corresponding author), Patricia V. Lawford, Wouter Huberts, Leif Rune Hellevik, Stig W. Omholt, Frans N. van de Vosse

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

1 Citaat (Scopus)

Uittreksel

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.

TaalEngels
Pagina's38-48
Aantal pagina's11
TijdschriftMedical Engineering & Physics
Volume72
DOI's
StatusGepubliceerd - 1 okt 2019

Vingerafdruk

Cardiovascular Models
Precision Medicine
Medicine
Clinical Decision Support Systems
Mathematics
Artificial Intelligence
Practice Management
Physics
Traction
Uncertainty
Health
Control theory
Computer science
Artificial intelligence
Learning systems
Network protocols
Monitoring

Trefwoorden

    Citeer dit

    Hose, D. Rodney ; Lawford, Patricia V. ; Huberts, Wouter ; Hellevik, Leif Rune ; Omholt, Stig W. ; van de Vosse, Frans N./ Cardiovascular models for personalised medicine : where now and where next?. In: Medical Engineering & Physics. 2019 ; Vol. 72. blz. 38-48
    @article{044b31c1e0fb4dd8abae9e27bbeb91a6,
    title = "Cardiovascular models for personalised medicine: where now and where next?",
    abstract = "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.",
    keywords = "Cardiovascular modelling, Clinical descision support, Model, Model personalisation, Physiological modelling, Uncertainity",
    author = "Hose, {D. Rodney} and Lawford, {Patricia V.} and Wouter Huberts and Hellevik, {Leif Rune} and Omholt, {Stig W.} and {van de Vosse}, {Frans N.}",
    year = "2019",
    month = "10",
    day = "1",
    doi = "10.1016/j.medengphy.2019.08.007",
    language = "English",
    volume = "72",
    pages = "38--48",
    journal = "Medical Engineering & Physics",
    issn = "1350-4533",
    publisher = "Elsevier",

    }

    Cardiovascular models for personalised medicine : where now and where next? / Hose, D. Rodney (Corresponding author); Lawford, Patricia V.; Huberts, Wouter; Hellevik, Leif Rune; Omholt, Stig W.; van de Vosse, Frans N.

    In: Medical Engineering & Physics, Vol. 72, 01.10.2019, blz. 38-48.

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

    TY - JOUR

    T1 - Cardiovascular models for personalised medicine

    T2 - Medical Engineering & Physics

    AU - Hose,D. Rodney

    AU - Lawford,Patricia V.

    AU - Huberts,Wouter

    AU - Hellevik,Leif Rune

    AU - Omholt,Stig W.

    AU - van de Vosse,Frans N.

    PY - 2019/10/1

    Y1 - 2019/10/1

    N2 - 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.

    AB - 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.

    KW - Cardiovascular modelling

    KW - Clinical descision support

    KW - Model

    KW - Model personalisation

    KW - Physiological modelling

    KW - Uncertainity

    UR - http://www.scopus.com/inward/record.url?scp=85072084973&partnerID=8YFLogxK

    U2 - 10.1016/j.medengphy.2019.08.007

    DO - 10.1016/j.medengphy.2019.08.007

    M3 - Article

    VL - 72

    SP - 38

    EP - 48

    JO - Medical Engineering & Physics

    JF - Medical Engineering & Physics

    SN - 1350-4533

    ER -