A systematic review on machine learning approaches for cardiovascular disease prediction using medical big data
There is a considerable rise in cardiovascular diseases in the world. It is pertinently
essential to make cardiovascular prediction accurate to the maximum. A forecast based on …
essential to make cardiovascular prediction accurate to the maximum. A forecast based on …
hyOPTXg: OPTUNA hyper-parameter optimization framework for predicting cardiovascular disease using XGBoost
P Srinivas, R Katarya - Biomedical Signal Processing and Control, 2022 - Elsevier
Cardiovascular disease is a dangerous disorder that causes the most significant number of
deaths across the world. In the past years, researchers proposed several automated …
deaths across the world. In the past years, researchers proposed several automated …
Advances in the Applications of Bioinformatics and Chemoinformatics
MA Raslan, SA Raslan, EM Shehata, AS Mahmoud… - Pharmaceuticals, 2023 - mdpi.com
Chemoinformatics involves integrating the principles of physical chemistry with computer-
based and information science methodologies, commonly referred to as “in silico …
based and information science methodologies, commonly referred to as “in silico …
Heart disease risk prediction using machine learning classifiers with attribute evaluators
Cardiovascular diseases (CVDs) kill about 20.5 million people every year. Early prediction
can help people to change their lifestyles and to ensure proper medical treatment if …
can help people to change their lifestyles and to ensure proper medical treatment if …
Heart disease detection using feature extraction and artificial neural networks: A sensor-based approach
AB Naeem, B Senapati, D Bhuva, A Zaidi… - IEEE …, 2024 - ieeexplore.ieee.org
This study presents a novel technique for identifying individuals using feature extraction
methods and signal processing approaches. It uses an artificial neural network (ANN) …
methods and signal processing approaches. It uses an artificial neural network (ANN) …
Heart disease risk prediction using deep learning techniques with feature augmentation
MT García-Ordás, M Bayón-Gutiérrez… - Multimedia Tools and …, 2023 - Springer
Cardiovascular diseases state as one of the greatest risks of death for the general
population. Late detection in heart diseases highly conditions the chances of survival for …
population. Late detection in heart diseases highly conditions the chances of survival for …
[HTML][HTML] Machine learning-based smart wearable system for cardiac arrest monitoring using hybrid computing
Every year, the percentage of people affected by cardiovascular diseases increases
drastically. Out of them, a heart attack is the most prominent and painful disease. According …
drastically. Out of them, a heart attack is the most prominent and painful disease. According …
A Novel Blending Approach for Smoking Status Prediction in Hidden Smokers to Reduce Cardiovascular Disease Risk
Smoking has a serious complicated impact on Cardiovascular Health (CVH), which makes it
an easily controlled risk factor for Cardiovascular Disease (CVD). The importance of early …
an easily controlled risk factor for Cardiovascular Disease (CVD). The importance of early …
[PDF][PDF] A Review of Machine Learning Techniques Used in the Prediction of Heart Disease
Heart disease stands as a principal cause of death worldwide, and its early prediction is
essential for effective patient management and the reduction of healthcare expenditures. In …
essential for effective patient management and the reduction of healthcare expenditures. In …
A Hybrid Feature Selection and Ensemble Stacked Learning Models on Multi-Variant CVD Datasets for Effective Classification
Predicting cardiac or heart disease has emerged as a formidable challenge in the medical
domain recently. It is recognized as a major global health concern, and stands as one of the …
domain recently. It is recognized as a major global health concern, and stands as one of the …