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Modeling Coronary Artery Calcification Levels from Behavioral Data in a Clinical Study

Shuo Yang; Kristian Kersting; Greg Terry; Jefferey Carr; Sriraam Natarajan
In: John H. Holmes; Riccardo Bellazzi; Lucia Sacchi; Niels Peek (Hrsg.). Artificial Intelligence in Medicine - 15th Conference on Artificial Intelligence in Medicine. Conference on Artificial Intelligence in Medicine (AIME-2015), June 17-20, Pavia, Italy, Pages 182-187, Lecture Notes in Computer Science, Vol. 9105, Springer, 2015.


Cardiovascular disease (CVD) is one of the key causes for death worldwide. We consider the problem of modeling an imaging biomarker, Coronary Artery Calcification (CAC) measured by computed tomography, based on behavioral data. We employ the formalism of Dynamic Bayesian Network (DBN) and learn a DBN from these data. Our learned DBN provides insights about the associations of specific risk factors with CAC levels. Exhaustive empirical results demonstrate that the proposed learning method yields reasonable performance during cross-validation.

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