Evaluation of a Dental Caries Clinical Decision Support System

Michel Bessani, Daniel Rodrigues de Lima, Emery Cleiton Cabral Correia Lins, Carlos Dias Maciel

Abstract

Decision Support Systems (DSSs) aims to support professionals decision process. A specific area of application is the Clinical one, resulting in Clinical Decision Support Systems (CDSSs), focusing on Clinical Decision problems, like oncology, geriatrics, and dentistry. DSSs integrate expert knowledge through pattern-based approaches. Bayesian Networks are probabilistic graph models that allow representation and inference on complex scenarios. BNs are used in different decision-making fields, e.g., Clinical Decision Support Systems. Traditionally, such models are learned using established databases. However, in situations where such data set is unavailable, the BN can be manually constructed converting expert knowledge in conditional probabilities. In this paper, we evaluate a Dental Caries Clinical Decision Support System which uses a BN to provide suggestions and represent clinical patterns. The evaluation methodology uses forward sampling to generated data from the BN. The generated data are separated into three groups, and each one is analyzed. The results show the certainty of the Bayesian Network for some scenarios. The analysis of the CDSS BN indicates that the system efficiently infers according to the pattern presented in the literature.

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Paper Citation


in Harvard Style

Bessani M., de Lima D., Cleiton Cabral Correia Lins E. and Maciel C. (2017). Evaluation of a Dental Caries Clinical Decision Support System . In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2017) ISBN 978-989-758-212-7, pages 198-204. DOI: 10.5220/0006168301980204


in Bibtex Style

@conference{biosignals17,
author={Michel Bessani and Daniel Rodrigues de Lima and Emery Cleiton Cabral Correia Lins and Carlos Dias Maciel},
title={Evaluation of a Dental Caries Clinical Decision Support System},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2017)},
year={2017},
pages={198-204},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006168301980204},
isbn={978-989-758-212-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2017)
TI - Evaluation of a Dental Caries Clinical Decision Support System
SN - 978-989-758-212-7
AU - Bessani M.
AU - de Lima D.
AU - Cleiton Cabral Correia Lins E.
AU - Maciel C.
PY - 2017
SP - 198
EP - 204
DO - 10.5220/0006168301980204