Mining data from hemodynamic simulations for generating prediction and explanation models

Zoran Bosnić; Petar Vračar; Milos D Radović; Goran Devedžić; Nenad D Filipović; Igor Kononenko

doi:10.1109/TITB.2011.2164546

Mining data from hemodynamic simulations for generating prediction and explanation models

IEEE Trans Inf Technol Biomed. 2012 Mar;16(2):248-54. doi: 10.1109/TITB.2011.2164546. Epub 2011 Aug 15.

Authors

Zoran Bosnić¹, Petar Vračar, Milos D Radović, Goran Devedžić, Nenad D Filipović, Igor Kononenko

Affiliation

¹ University of Ljubljana, Faculty of Computer and Information Science. zoran.bosnic@fri.uni-lj.si

PMID: 21846607
DOI: 10.1109/TITB.2011.2164546

Abstract

One of the most common causes of human death is stroke, which can be caused by carotid bifurcation stenosis. In our work, we aim at proposing a prototype of a medical expert system that could significantly aid medical experts to detect hemodynamic abnormalities (increased artery wall shear stress). Based on the acquired simulated data, we apply several methodologies for1) predicting magnitudes and locations of maximum wall shear stress in the artery, 2) estimating reliability of computed predictions, and 3) providing user-friendly explanation of the model's decision. The obtained results indicate that the evaluated methodologies can provide a useful tool for the given problem domain.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Carotid Arteries / pathology
Carotid Arteries / physiopathology
Carotid Stenosis / pathology
Carotid Stenosis / physiopathology*
Computer Simulation
Data Mining / methods*
Databases, Factual
Hemodynamics / physiology*
Humans
Models, Cardiovascular*
Models, Statistical*
Neural Networks, Computer
Regression Analysis
Reproducibility of Results