ArticleComputational intelligence and neuroscience2021
Prediction of Heart Disease Using a Combination of Machine Learning and Deep Learning.
Article in Computational intelligence and neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.
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Who cites it
54 citing papers in PubMed.
- Leakage-Safe Precision-Aware Dual-Branch FT-Transformer for Population-Scale Heart Disease Risk Prediction.Sensors (Basel, Switzerland) · 2026Article
- Comparative evaluation of deep learning models for cardiovascular disease diagnosis and classification.Scientific reports · 2026Article
- Comparative performance of machine learning and deep learning models for heart disease prediction in a small clinical dataset.American journal of cardiovascular disease · 2026Article
- Biodata-centric cardiovascular disease prediction using multi-objective genetic algorithm-driven deep ensembles.Scientific reports · 2025Article
- A comprehensive survey of artificial intelligence methods for cardiovascular disease detection: Recent advances and future challenges.MethodsX · 2025Review
- An ideally designed deep trust network model for heart disease prediction based on seagull optimization and Ruzzo Tompa algorithm.Scientific reports · 2025Article
- Clustering-based binary Grey Wolf Optimisation model with 6LDCNNet for prediction of heart disease using patient data.Scientific reports · 2025Article
- Enhancing stroke disease classification through machine learning models via a novel voting system by feature selection techniques.PloS one · 2025Article
- Article
- Machine learning techniques for improved prediction of cardiovascular diseases using integrated healthcare data.Frontiers in artificial intelligence · 2025Article
- Transfer Learning Strategies for Cardiovascular Disease Detection in ECG Imagery.Biomedical engineering and computational biology · 2025Article
- A feature selection method utilizing path accumulation cost, redundancy minimization, and interaction maximization for the diagnosis of coronary heart disease.PeerJ. Computer science · 2025Article
- H-DSAE: a hybrid technique to recognize heart disease.Frontiers in physiology · 2025Article
- Transfer learning-based hybrid VGG16-machine learning approach for heart disease detection with explainable artificial intelligence.Frontiers in artificial intelligence · 2025Article
- A medical disease assisted diagnosis method based on lightweight fuzzy SZGWO-ELM neural network model.Scientific reports · 2024Article
- Predictive Analytics in Heart Failure Risk, Readmission, and Mortality Prediction: A Review.Cureus · 2024Review
- Article
- A Neoteric Feature Extraction Technique to Predict the Survival of Gastric Cancer Patients.Diagnostics (Basel, Switzerland) · 2024Article
- AttGRU-HMSI: enhancing heart disease diagnosis using hybrid deep learning approach.Scientific reports · 2024Article
- Empirical exploration of whale optimisation algorithm for heart disease prediction.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The correct prediction of heart disease can prevent life threats, and incorrect prediction can prove to be fatal at the same time. In this paper different machine learning algorithms and deep learning are applied to compare the results and analysis of the UCI Machine Learning Heart Disease dataset. The dataset consists of 14 main attributes used for performing the analysis. Various promising results are achieved and are validated using accuracy and confusion matrix. The dataset consists of some irrelevant features which are handled using Isolation Forest, and data are also normalized for getting better results. And how this study can be combined with some multimedia technology like mobile devices is also discussed. Using deep learning approach, 94.2% accuracy was obtained.
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