Understanding the bias in machine learning systems for cardiovascular disease risk assessment: The first of its kind review

JS Suri, M Bhagawati, S Paul, A Protogeron… - Computers in biology …, 2022 - Elsevier
Abstract Background Artificial Intelligence (AI), in particular, machine learning (ML) has
shown promising results in coronary artery disease (CAD) or cardiovascular disease (CVD) …

[HTML][HTML] Artificial intelligence in the risk prediction models of cardiovascular disease and development of an independent validation screening tool: a systematic review

Y Cai, YQ Cai, LY Tang, YH Wang, M Gong, TC Jing… - BMC medicine, 2024 - Springer
Background A comprehensive overview of artificial intelligence (AI) for cardiovascular
disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external …

[Retracted] Clinical Data Analysis for Prediction of Cardiovascular Disease Using Machine Learning Techniques

RG Nadakinamani, A Reyana, S Kautish… - Computational …, 2022 - Wiley Online Library
Cardiovascular disease is difficult to detect due to several risk factors, including high blood
pressure, cholesterol, and an abnormal pulse rate. Accurate decision‐making and optimal …

[HTML][HTML] A heart disease prediction model based on feature optimization and smote-Xgboost algorithm

J Yang, J Guan - Information, 2022 - mdpi.com
In today's world, heart disease is the leading cause of death globally. Researchers have
proposed various methods aimed at improving the accuracy and efficiency of the clinical …

[HTML][HTML] Machine learning-based diagnosis and risk factor analysis of cardiocerebrovascular disease based on KNHANES

T Oh, D Kim, S Lee, C Won, S Kim, J Yang, J Yu… - Scientific reports, 2022 - nature.com
The prevalence of cardiocerebrovascular disease (CVD) is continuously increasing, and it is
the leading cause of human death. Since it is difficult for physicians to screen thousands of …

[HTML][HTML] Trends and challenges of wearable multimodal technologies for stroke risk prediction

YH Chen, M Sawan - Sensors, 2021 - mdpi.com
We review in this paper the wearable-based technologies intended for real-time monitoring
of stroke-related physiological parameters. These measurements are undertaken to prevent …

DASMcC: Data Augmented SMOTE Multi-class Classifier for prediction of Cardiovascular Diseases using time series features

N Sinha, MAG Kumar, AM Joshi… - IEEE Access, 2023 - ieeexplore.ieee.org
One of the leading causes of mortality worldwide is cardiovascular disease (CVD).
Electrocardiography (ECG) is a noninvasive and cost-effective tool to diagnose the heart's …

A metaheuristic-enabled training system for ensemble classification technique for heart disease prediction

PT Sheeba, D Roy, MH Syed - Advances in Engineering Software, 2022 - Elsevier
Various conditions that affect the muscles, blood arteries, heart, valves, or internal electrical
pathways that regulate muscle contraction are referred to as" heart diseases." This work …

[HTML][HTML] Many Models, Little Adoption—What Accounts for Low Uptake of Machine Learning Models for Atrial Fibrillation Prediction and Detection?

Y Kawamura, A Vafaei Sadr, V Abedi… - Journal of Clinical …, 2024 - mdpi.com
(1) Background: Atrial fibrillation (AF) is a major risk factor for stroke and is often
underdiagnosed, despite being present in 13–26% of ischemic stroke patients. Recently, a …

An extensive approach towards heart stroke prediction using machine learning with ensemble classifier

D Paikaray, AK Mehta - Proceedings of the International Conference on …, 2022 - Springer
Heart stroke remains one of the eminent diseases which has a great impact on the mortality
rate. Besides the other diseases which may be diagnosed and treated, heart stroke is mostly …