NDLI: Fusion of risk assessment models with application to coronary artery disease patients

Content Provider	IEEE Xplore Digital Library
Author	Paredes, S. Rocha, T. de Carvalho, P. Henriques, J. Rasteiro, D. Morals, J. Ferreira, J. Mendes, M.
Copyright Year	2011
Description	Author affiliation: CISUC, Departamento de Engenharia Informática, Universidade de, Coimbra, Pólo II, 3030-290 Coimbra (de Carvalho, P.; Henriques, J.) \|\| Serviço de Cardiologia, Hospital Santo André, EPE Rua das Olhalvas, 2410-197 Leiria (Morals, J.) \|\| Serviço de Cardiologia, Hospital Santa Cruz, Lisboa (Ferreira, J.; Mendes, M.) \|\| Instituto Politécnico de Coimbra, Departamento de Física e Matemática, Coimbra (Rasteiro, D.) \|\| Instituto Politécnico de Coimbra, Departamento de Engenharia, Informática e de Sistemas, Rua Pedro Nunes, 3030-199 Coimbra (Paredes, S.; Rocha, T.)
Abstract	Several risk score models are available in literature to predict death/myocardial infarction event for coronary artery disease (CAD) patients, within a short period of time. However, the choice of the most adequate model is not straightforward since there might not be a consensus about the best model to use in clinical practice Moreover, individually, these models present some weaknesses, such as the inability to deal with missing information. This work addresses these problems, proposing a Bayesian classifier strategy enabling the simultaneous use of several models (models' fusion). Thus, a higher number of risk factors can be used in the common model, while it can deal with missing information. The validation of the strategy is carried out through the combination of three current risk score models (GRACE, TIMI, PURSUIT). Results were obtained based on a dataset that comprises 460 consecutive patients admitted to the Cardiology Department of Santa Cruz Hospital, Lisbon, from 1999 to 2001. A comparison with the voting scheme, which considers exclusively the outputs of models to combine (models output combination) is also carried out. The proposed Bayesian approach had very satisfactory results, confirming the potential of its application to the clinical practice.
Starting Page	872
Ending Page	875
File Size	299808
Page Count	4
File Format	PDF
ISBN	9781424441211
ISSN	1557170X
e-ISBN	9781457715891
e-ISBN	9781424441228
DOI	10.1109/IEMBS.2011.6090227
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Solid modeling Bayesian methods Biological system modeling Heart Optimization Myocardium Europe
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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