Chaotic gradient based optimization with fuzzy temporal optimized CNN for heart failure prediction Article Swipe
Gireesh Kumar
,
S. Muthurajkumar
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41598-025-88277-w
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41598-025-88277-w
Heart failure is a leading cause of premature death, especially among individuals with a sedentary lifestyle. Early and accurate detection is essential to prevent the progression of this situation. However, many existing prediction systems failed to detect early and accurately, also taking more time to detect. To address these issues, we propose an advanced heart failure detection model that combines one-dimensional chaotic maps and a Gradient-Based Optimizer (GBO) called Chaotic Gradient-Based Optimizer (CGBO). This approach improves feature selection by effectively selecting the most crucial features related to the risk of heart failure. Additionally, we introduce the Fuzzy Temporal Optimized Convolutional Neural Network (FTOCNN) classifier that incorporates CGBO and fuzzy temporal rules to enhance detection accuracy. The proposed model is evaluated using the UCI heart dataset and Electronic Health Records (EHRs) and its performance is assessed through statistical measures, classification metrics, and a Wilcoxon rank-sum p-test. Furthermore, a tenfold cross-validation process ensures a comprehensive evaluation and the proposed method outperforms different Machine Learning (ML) / Deep Learning (DL) classifiers. The experimental findings reveal that CGBO significantly improves the predictive performance of the FTOCNN classifier by achieving 94% accuracy in EHR and enhances the reliability of heart failure detection compared to existing systems.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s41598-025-88277-w
- OA Status
- gold
- Cited By
- 1
- References
- 44
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4407045404
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4407045404Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1038/s41598-025-88277-wDigital Object Identifier
- Title
-
Chaotic gradient based optimization with fuzzy temporal optimized CNN for heart failure predictionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-01-31Full publication date if available
- Authors
-
Gireesh Kumar, S. MuthurajkumarList of authors in order
- Landing page
-
https://doi.org/10.1038/s41598-025-88277-wPublisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1038/s41598-025-88277-wDirect OA link when available
- Concepts
-
Computer science, Artificial intelligence, Convolutional neural network, Classifier (UML), Machine learning, Wilcoxon signed-rank test, Chaotic, Fuzzy logic, Data mining, Feature selection, Pattern recognition (psychology), Statistics, Mathematics, Mann–Whitney U testTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
- References (count)
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44Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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