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Authors: Ahmedul Kabir 1 ; Carolina Ruiz 1 ; Sergio Alvarez 2 ; Nazish Riaz 3 and Majaz Moonis 3

Affiliations: 1 Worcester Polytechnic Institute, United States ; 2 Boston College, United States ; 3 University of Massachusetts Medical School, United States

Keyword(s): Ischemic Stroke, EM Clustering, Gaussian Mixture Model.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Health Information Systems ; Medical and Nursing Informatics ; Pattern Recognition and Machine Learning ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: The objective of our study is to find meaningful groups in the data of ischemic stroke patients using unsupervised clustering. The data are modeled using Gaussian mixture models with a variety of covariance structures. Cluster parameters in each of these models are estimated by maximum likelihood via the Expectation-Maximization algorithm. The best models are then selected by relying on information-theoretic criteria. It is observed that the stroke patients can be grouped into a small number of medically relevant clusters that are defined primarily by the presence of diabetes and atrial fibrillation. Characteristics of the clusters found are discussed, using statistical comparisons and data visualization.

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Paper citation in several formats:
Kabir, A.; Ruiz, C.; Alvarez, S.; Riaz, N. and Moonis, M. (2015). Model-based Clustering of Ischemic Stroke Patients. In Proceedings of the International Conference on Health Informatics (BIOSTEC 2015) - HEALTHINF; ISBN 978-989-758-068-0; ISSN 2184-4305, SciTePress, pages 172-181. DOI: 10.5220/0005278101720181

@conference{healthinf15,
author={Ahmedul Kabir. and Carolina Ruiz. and Sergio Alvarez. and Nazish Riaz. and Majaz Moonis.},
title={Model-based Clustering of Ischemic Stroke Patients},
booktitle={Proceedings of the International Conference on Health Informatics (BIOSTEC 2015) - HEALTHINF},
year={2015},
pages={172-181},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005278101720181},
isbn={978-989-758-068-0},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics (BIOSTEC 2015) - HEALTHINF
TI - Model-based Clustering of Ischemic Stroke Patients
SN - 978-989-758-068-0
IS - 2184-4305
AU - Kabir, A.
AU - Ruiz, C.
AU - Alvarez, S.
AU - Riaz, N.
AU - Moonis, M.
PY - 2015
SP - 172
EP - 181
DO - 10.5220/0005278101720181
PB - SciTePress

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