ArticleJournal of medical systems2019
A Hybrid Scheme for Heart Disease Diagnosis Using Rough Set and Cuckoo Search Technique.
Article in Journal of medical systems, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Heart disease prediction using rough neutrosophic sets and dual-attention neural networks: RNS-OptiDANet.Frontiers in artificial intelligence · 2026Article
- Reliable machine learning models in genomic medicine using conformal prediction.Frontiers in bioinformatics · 2025Review
- Empirical exploration of whale optimisation algorithm for heart disease prediction.Scientific reports · 2024Article
- Handling of uncertainty in medical data using machine learning and probability theory techniques: a review of 30 years (1991-2020).Annals of operations research · 2021Article
- Identification of the Framingham Risk Score by an Entropy-Based Rule Model for Cardiovascular Disease.Entropy (Basel, Switzerland) · 2020Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large volumes of raw data are created from the digital world every day. Acquiring useful information from these data is challenging, and it turned into a prime zone of momentum explore. More research is done in this direction. Further, in disease diagnosis, many uncertainties are involved in the information system. To handle such uncertainties, intelligent techniques are employed. In this paper, we present an integrated scheme for heart disease diagnosis. The proposed model integrates cuckoo search and rough set for inferencing decision rules. At the underlying phase, we employ a cuckoo search to discover the main features. Further, these main features are analyzed using rough set generating rules. An empirical analysis is carried out on heart disease. Besides, a comparative study is also presented. The comparative study demonstrates the feasibility of the proposed model.
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