Understanding the bias in machine learning systems for cardiovascular disease risk assessment: The first of its kind review
Abstract Background Artificial Intelligence (AI), in particular, machine learning (ML) has
shown promising results in coronary artery disease (CAD) or cardiovascular disease (CVD) …
shown promising results in coronary artery disease (CAD) or cardiovascular disease (CVD) …
Machine learning applied to diagnosis of human diseases: A systematic review
N Caballé-Cervigón, JL Castillo-Sequera… - Applied Sciences, 2020 - mdpi.com
Human healthcare is one of the most important topics for society. It tries to find the correct
effective and robust disease detection as soon as possible to patients receipt the …
effective and robust disease detection as soon as possible to patients receipt the …
Machine learning-based marker for coronary artery disease: derivation and validation in two longitudinal cohorts
Background Binary diagnosis of coronary artery disease does not preserve the complexity of
disease or quantify its severity or its associated risk with death; hence, a quantitative marker …
disease or quantify its severity or its associated risk with death; hence, a quantitative marker …
A soft voting ensemble classifier for early prediction and diagnosis of occurrences of major adverse cardiovascular events for STEMI and NSTEMI during 2-year follow …
SWA Sherazi, JW Bae, JY Lee - PloS one, 2021 - journals.plos.org
Objective Some researchers have studied about early prediction and diagnosis of major
adverse cardiovascular events (MACE), but their accuracies were not high. Therefore, this …
adverse cardiovascular events (MACE), but their accuracies were not high. Therefore, this …
Social determinants in machine learning cardiovascular disease prediction models: a systematic review
Introduction Cardiovascular disease is the leading cause of death worldwide, and
cardiovascular disease burden is increasing in low-resource settings and for lower …
cardiovascular disease burden is increasing in low-resource settings and for lower …
[HTML][HTML] Cardiovascular diseases prediction by machine learning incorporation with deep learning
It is yet unknown what causes cardiovascular disease (CVD), but we do know that it is
associated with a high risk of death, as well as severe morbidity and disability. There is an …
associated with a high risk of death, as well as severe morbidity and disability. There is an …
Machine learning for diabetes clinical decision support: a review
Type 2 diabetes has recently acquired the status of an epidemic silent killer, though it is non-
communicable. There are two main reasons behind this perception of the disease. First, a …
communicable. There are two main reasons behind this perception of the disease. First, a …
Prediction of cardiac disease using supervised machine learning algorithms
RJP Princy, S Parthasarathy, PSH Jose… - … and control systems …, 2020 - ieeexplore.ieee.org
The healthcare industry is dealing with billions of patients all over the world and producing
massive data. The machine learning-based models are dissecting the multidimensional …
massive data. The machine learning-based models are dissecting the multidimensional …
A hybrid deep learning paradigm for carotid plaque tissue characterization and its validation in multicenter cohorts using a supercomputer framework
SS Skandha, A Nicolaides, SK Gupta… - Computers in biology …, 2022 - Elsevier
Background Early and automated detection of carotid plaques prevents strokes, which are
the second leading cause of death worldwide according to the World Health Organization …
the second leading cause of death worldwide according to the World Health Organization …
Machine learning versus conventional clinical methods in guiding management of heart failure patients—a systematic review
Abstract Machine learning (ML) algorithms “learn” information directly from data, and their
performance improves proportionally with the number of high-quality samples. The aim of …
performance improves proportionally with the number of high-quality samples. The aim of …