ArticleJournal of medical systems2012
Design of a fuzzy-based decision support system for coronary heart disease diagnosis.
Article in Journal of medical systems, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Validating the Accuracy of a Patient-Facing Clinical Decision Support System in Predicting Lumbar Disc Herniation: Diagnostic Accuracy Study.Diagnostics (Basel, Switzerland) · 2024Article
- A database for using machine learning and data mining techniques for coronary artery disease diagnosis.Scientific data · 2019Article
- A Feature-Driven Decision Support System for Heart Failure Prediction Based onComputational and mathematical methods in medicine · 2019Article
- Automated Diagnosis of Coronary Artery Disease: A Review and Workflow.Cardiology research and practice · 2018Review
- Coronary Heart Disease Preoperative Gesture Interactive Diagnostic System Based on Augmented Reality.Journal of medical systems · 2017Article
- Intelligence System for Diagnosis Level of Coronary Heart Disease with K-Star Algorithm.Healthcare informatics research · 2016Article
- Use of oximetry as a screening tool for obstructive sleep apnea: a case study in Taiwan.Journal of medical systems · 2015Article
- Fuzzy Rule-Based Classification System for Assessing Coronary Artery Disease.Computational and mathematical methods in medicine · 2015Article
- Genetic fuzzy system for mortality risk assessment in cardiac surgery.Journal of medical systems · 2014Article
- Developing a genetic fuzzy system for risk assessment of mortality after cardiac surgery.Journal of medical systems · 2014Article
- A clinical decision support system with an integrated EMR for diagnosis of peripheral neuropathy.Journal of medical systems · 2014Article
- A novel Fuzzy Expert System for the identification of severity of carpal tunnel syndrome.BioMed research international · 2013Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the present paper, a fuzzy rule-based system (FRBS) is designed to serve as a decision support system for Coronary heart disease (CHD) diagnosis that not only considers the decision accuracy of the rules but also their transparency at the same time. To achieve the two above mentioned objectives, we apply a multi-objective genetic algorithm to optimize both the accuracy and transparency of the FRBS. In addition and to help assess the certainty and the importance of each rule by the physician, an extended format of fuzzy rules that incorporates the degree of decision certainty and importance or support of each rule at the consequent part of the rules is introduced. Furthermore, a new way for employing Ensemble Classifiers Strategy (ECS) method is proposed to enhance the classification ability of the FRBS. The results show that the generated rules are humanly understandable while their accuracy compared favorably with other benchmark classification methods. In addition, the produced FRBS is able to identify the uncertainty cases so that the physician can give a special consideration to deal with them and this will result in a better management of efforts and tasks. Furthermore, employing ECS has specifically improved the ability of FRBS to detect patients with CHD which is desirable feature for any CHD diagnosis system.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.