ArticleScientific reports2024
Optimal feature selection for heart disease prediction using modified Artificial Bee colony (M-ABC) and K-nearest neighbors (KNN).
Article in Scientific reports, 2024. 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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12 citing papers in PubMed.
- A comparative study of quantum-inspired PSO and EA with their binary variants for heart disease classification.Scientific reports · 2026Article
- Development of AI based behavioral feature patterns on influencing asymptomatic cardiovascular disease attributes: a dataset standardization approach.Scientific reports · 2026Article
- A hybrid feature selection framework combining Artificial Bee Colony and decision trees for CVD risk assessment.Scientific reports · 2026Article
- Clustering-cum-regression based model and performance analysis for early prediction of heart disease.Scientific reports · 2026Article
- Quantum-optimized spatio-temporal transformer for multimodal cardiovascular risk prediction from clinical and wearable data.Frontiers in cardiovascular medicine · 2026Article
- Integrated multiobjective optimization of RFSSW parameters for AA2024-T3 using ANOVA machine learning and NSGA II.Scientific reports · 2025Article
- A Novel Knowledge Fusion Ensemble for Diagnostic Differentiation of Pediatric Pneumonia and Acute Bronchitis.Diagnostics (Basel, Switzerland) · 2025Article
- A novel interpreted deep network for Alzheimer's disease prediction based on inverted self attention and vision transformer.Scientific reports · 2025Article
- IoT driven smart health monitoring for heart disease prediction using quantum kernel enhanced sardine diffusion and CNN.Scientific reports · 2025Article
- Artificial intelligence driven platform for rapid catalytic performance assessment of nanozymes.Scientific reports · 2025Article
- A Predictive Model of Cardiovascular Aging by Clinical and Immunological Markers Using Machine Learning.Diagnostics (Basel, Switzerland) · 2025Article
- BioLake: an RNA expression analysis framework for prostate cancer biomarker powered by data lakehouse.BMC bioinformatics · 2025Article
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8 authors.
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Abstract
Heart disease is a complex and widespread illness that affects a significant number of people worldwide. Machine learning provides a way forward for early heart disease diagnosis. A classification model has been developed for the present study to predict heart disease. The attribute selection was done using a modified bee algorithm. Using the proposed model, practitioners can accurately predict heart disease and make informed decisions about patient health. In our study, we have proposed a framework based on Modified Artificial Bee Colony (M-ABC) and k-Nearest Neighbors (KNN) for predicting the optimal feature selection to obtain better accuracy. Using a modified bee algorithm, this paper focuses on identifying the optimal subset of attributes from the dataset. Specifically, during the classification-training phase, only the features that provide significant information are retained. The proposed study not only improves classification accuracy but also reduces training time for classifiers.
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