The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Automated Diagnosis of Coronary Artery Disease Based on Data Mining and Fuzzy Modeling
Abstract
A fuzzy rule-based decision support system (DSS) is presented for the diagnosis of coronary artery disease (CAD). The system is automatically generated from an initial annotated dataset, using a four stage methodology: 1) induction of a decision tree from the data; 2) extraction of a set of rules from the decision tree, in disjunctive normal form and formulation of a crisp model; 3) transformation of the crisp set of rules into a fuzzy model; and 4) optimization of the parameters of the fuzzy model. The dataset used for the DSS generation and evaluation consists of 199 subjects, each one characterized by 19 features, including demographic and history data, as well as laboratory examinations. Tenfold cross validation is employed, and the average sensitivity and specificity obtained is 62% and 54%, respectively, using the set of rules extracted from the decision tree (first and second stages), while the average sensitivity and specificity increase to 80% and 65%, respectively, when the fuzzification and optimization stages are used. The system offers several advantages since it is automatically generated, it provides CAD diagnosis based on easily and noninvasively acquired features, and is able to provide interpretation for the decisions made.
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Cites
Laurent, S., Boutouyrie, P., Asmar, R., Gautier, I., Laloux, B., Guize, L., Ducimetiere, P., & Benetos, A. (2001) · Hypertension · doi:10.1161/01.hyp.37.5.1236 · Cited by 3,856
Impact of Aortic Stiffness on Survival in End-Stage Renal Disease
Blacher, J., Guerin, A. P., Pannier, B., Marchais, S. J., Safar, M. E., & London, G. M. (1999) · Circulation · doi:10.1161/01.cir.99.18.2434 · Cited by 2,138
Hjemdahl, P., & Friberg, P. (1996) · Journal of Hypertension · doi:10.1097/00004872-199602000-00001 · Cited by 196
Cited by
Arabasadi, Z., Alizadehsani, R., Roshanzamir, M., Moosaei, H., & Yarifard, A. A. (2017) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2017.01.004 · Cited by 499
A Systematic Review on Healthcare Analytics: Application and Theoretical Perspective of Data Mining
Islam, M. S., Hasan, M. M., Wang, X., Germack, H. D., & Noor-E-Alam, M. (2018) · Healthcare · doi:10.3390/healthcare6020054 · Cited by 267
Shah, S. M. S., Batool, S., Khan, I., Ashraf, M. U., Abbas, S. H., & Hussain, S. A. (2017) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/j.physa.2017.04.113 · Cited by 150
Vijayashree, J., & Sultana, H. P. (2018) · Programming and Computer Software · doi:10.1134/s0361768818060129 · Cited by 130
An Ontology-Based Interpretable Fuzzy Decision Support System for Diabetes Diagnosis
El-Sappagh, S., Alonso, J. M., Ali, F., Ali, A., Jang, J.-H., & Kwak, K.-S. (2018) · IEEE Access · doi:10.1109/access.2018.2852004 · Cited by 79
Metadata
- Authors
- Tsipouras, M. G., Exarchos, T. P., Fotiadis, D. I., Kotsia, A. P., Vakalis, K. V., Naka, K. K., & Michalis, L. K.
- Venue
- IEEE Transactions on Information Technology in Biomedicine
- Published
- 2008-07
- Volume
- 12
- Issue
- 4
- Pages
- 447-458
- ISSN
- 1089-7771 (ISSN-L)
- OpenAlex
- W2165687409
- Cited by
- 189
- References
- 3
- FWCI
- 11.58
- Type
- journal article
- Language
- en
- Open access
- closed
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- Tsipouras, M. G., Exarchos, T. P., Fotiadis, D. I., Kotsia, A. P., Vakalis, K. V., Naka, K. K., & Michalis, L. K. (2008). Automated Diagnosis of Coronary Artery Disease Based on Data Mining and Fuzzy Modeling. IEEE Transactions on Information Technology in Biomedicine. https://doi.org/10.1109/titb.2007.907985
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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