Browsing by Author "Tøndel, Kristin"
Now showing items 1-5 of 5
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A computational pipeline for quantification of mouse myocardial stiffness parameters
Nordbø, Øyvind; Lamata, P.; Land, Sander; Niederer, Steven A.; Aronsen, Jan Magnus; Louch, William Edward; Sjaastad, Ivar; Martens, Harald; Gjuvsland, Arne Bjørke; Tøndel, Kristin; Torp, Hans; Lohezic, M; Schneider, Jürgen; Remme, Espen W.; Smith, Nicolas P; Omholt, Stig W; Vik, Jon Olav (Journal article; Peer reviewed, 2014)The mouse is an important model for theoretical–experimental cardiac research, and biophysically based whole organ models of the mouse heart are now within reach. However, the passive material properties of mouse myocardium ... -
Hierarchical multivariate regression-based sensitivity analysis reveals complex parameter interaction patterns in dynamic models
Tøndel, Kristin; Vik, Jon Olav; Martens, Harald; Indahl, Ulf Geir; Smith, Nic; Omholt, Stig W (Journal article; Peer reviewed, 2013) -
Is heart failure with mid range ejection fraction (HFmrEF) a distinct clinical entity or an overlap group?
Webb, Jessica; Draper, Jane; Fovargue, Lauren; Sieniewicz, Benjamin; Gould, Justin; Claridge, Simon; Barton, Carys; Smith, Silapiya; Tøndel, Kristin; Ronak, Rajani; Kapetanakis, Stamatis; Rinaldi, Christopher A; McDonagh, Theresa A.; Razavi, Reza; Carr-White, Gerald (Journal article; Peer reviewed, 2018) -
Metamodelling of the Hodgkin-Huxley model and the Pinsky-Rinzel model using local multivariate regression and deep learning
Ødegaard, Lars Erik (Master thesis, 2019)Biological processes, such as the electrical activity in neurons, are often modelled using complex, non-linear and high dimensional differential systems. Such models are usually associated with a high computational cost. ... -
On the application of machine learning techniques for phenotypic classification and clustering of heart failure patients
Adrik, Samir (Master thesis, 2018)In this thesis, we attempt to investigate how well various clustering algorithms (hierarchical clustering, k-means and expectation–maximization) perform in producing phenotypically distinct clinical patient groups (i.e. ...