A powerful paradigm for cardiovascular risk stratification using multiclass, multi-label, and ensemble-based machine learning paradigms: A narrative review
Abstract Background and Motivation: Cardiovascular disease (CVD) causes the highest
mortality globally. With escalating healthcare costs, early non-invasive CVD risk assessment …
mortality globally. With escalating healthcare costs, early non-invasive CVD risk assessment …
Detection of cardiovascular diseases in ECG images using machine learning and deep learning methods
MB Abubaker, B Babayiğit - IEEE transactions on artificial …, 2022 - ieeexplore.ieee.org
Cardiovascular diseases (heart diseases) are the leading cause of death worldwide. The
earlier they can be predicted and classified; the more lives can be saved. Electrocardiogram …
earlier they can be predicted and classified; the more lives can be saved. Electrocardiogram …
5g-nidd: A comprehensive network intrusion detection dataset generated over 5g wireless network
With a plethora of new connections, features, and services introduced, the 5th generation
(5G) wireless technology reflects the development of mobile communication networks and is …
(5G) wireless technology reflects the development of mobile communication networks and is …
Visual analysis of cardiac arrest prediction using Machine learning algorithms: A health education awareness initiative
A visual analysis may accurately predict cardiac arrest, making it a potent educational tool
for raising public awareness of health issues. By predicting cardiac arrest earlier …
for raising public awareness of health issues. By predicting cardiac arrest earlier …
Impact of categorical and numerical features in ensemble machine learning frameworks for heart disease prediction
Cardiovascular disease (CVD) or heart disease is one of the most fatal diseases of the world
that has been observed through-out the last decade. The prediction of CVD in majority of …
that has been observed through-out the last decade. The prediction of CVD in majority of …
Machine learning approaches for early detection of non-alcoholic steatohepatitis based on clinical and blood parameters
This study aims to develop a machine learning approach leveraging clinical data and blood
parameters to predict non-alcoholic steatohepatitis (NASH) based on the NAFLD Activity …
parameters to predict non-alcoholic steatohepatitis (NASH) based on the NAFLD Activity …
Advancing thyroid care: An accurate trustworthy diagnostics system with interpretable AI and hybrid machine learning techniques
The worldwide prevalence of thyroid disease is on the rise, representing a chronic condition
that significantly impacts global mortality rates. Machine learning (ML) approaches have …
that significantly impacts global mortality rates. Machine learning (ML) approaches have …
Heart Disease Diagnostics Using Meta‐Learning‐Based Hybrid Feature Selection
K Dissanayake, MG Md Johar - … Computational Intelligence and …, 2024 - Wiley Online Library
Heart disease, encompassing a range of conditions affecting the heart, remains a leading
cause of morbidity and mortality worldwide. The urgent need for precise diagnostic …
cause of morbidity and mortality worldwide. The urgent need for precise diagnostic …
Prototype Learning for Medical Time Series Classification via Human–Machine Collaboration
Deep neural networks must address the dual challenge of delivering high-accuracy
predictions and providing user-friendly explanations. While deep models are widely used in …
predictions and providing user-friendly explanations. While deep models are widely used in …
[HTML][HTML] Wireless-based portable device heart rate measurement as biomedical devices for stress detection
C Kuncoro, A Efendi, WJ Luo, MM Sakanti… - AIP Advances, 2024 - pubs.aip.org
Stress can increase the heart rate, causing dangerous conditions that cause significant harm
and even death. Therefore, managing stress well to control the heart rate is vital. Monitoring …
and even death. Therefore, managing stress well to control the heart rate is vital. Monitoring …