SBB-Chi2-A2: stacking of bagging-boosting with the blend Chi-square for effective prediction of aortic aneurysm using biomarker profiling

International Journal of Information Technology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 12, 2025

Language: Английский

A comprehensive review of machine learning for heart disease prediction: challenges, trends, ethical considerations, and future directions

Frontiers in Artificial Intelligence, Journal Year: 2025, Volume and Issue: 8

Published: May 13, 2025

This review provides a thorough and organized overview of machine learning (ML) applications in predicting heart disease, covering technological advancements, challenges, future prospects. As cardiovascular diseases (CVDs) are the leading cause global mortality, there is an urgent demand for early precise diagnostic tools. ML models hold considerable potential by utilizing large-scale healthcare data to enhance predictive diagnostics. To systematically investigate this field, literature into five thematic categories such as “Heart Disease Detection Diagnostics,” “Machine Learning Models Algorithms Healthcare,” “Feature Engineering Optimization Techniques,” “Emerging Technologies “Applications AI Across Diseases Conditions.” The incorporates performance benchmarking various models, highlighting that hybrid deep (DL) frameworks, e.g., convolutional neural network-long short-term memory (CNN-LSTM) consistently outperform traditional terms sensitivity, specificity, area under curve (AUC). Several real-world case studies presented demonstrate successful deployment clinical wearable settings. showcases progression approaches from classifiers DL structures federated (FL) frameworks. It also discusses ethical issues, dataset limitations, model transparency. conclusions provide important insights development artificial intelligence (AI) powered, clinically applicable disease prediction systems.

Language: Английский

Optimization of multidimensional feature engineering and data partitioning strategies in heart disease prediction models

Alexandria Engineering Journal, Journal Year: 2024, Volume and Issue: 107, P. 932 - 949

Published: Sept. 19, 2024

Language: Английский