Using physiologically based models for clinical translation: predictive modelling, data interpretation or something in-between?

16Citations
Citations of this article
43Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Heart disease continues to be a significant clinical problem in Western society. Predictive models and simulations that integrate physiological understanding with patient information derived from clinical data have huge potential to contribute to improving our understanding of both the progression and treatment of heart disease. In particular they provide the potential to improve patient selection and optimisation of cardiovascular interventions across a range of pathologies. Currently a significant proportion of this potential is still to be realised. In this paper we discuss the opportunities and challenges associated with this realisation. Reviewing the successful elements of model translation for biophysically based models and the emerging supporting technologies, we propose three distinct modes of clinical translation. Finally we outline the challenges ahead that will be fundamental to overcome if the ultimate goal of fully personalised clinical cardiac care is to be achieved. (Figure presented.).

Cite

CITATION STYLE

APA

Niederer, S. A., & Smith, N. P. (2016). Using physiologically based models for clinical translation: predictive modelling, data interpretation or something in-between? Journal of Physiology, 594(23), 6849–6863. https://doi.org/10.1113/JP272003

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free