[HTML][HTML] Machine-learning-based disease diagnosis: A comprehensive review
MM Ahsan, SA Luna, Z Siddique - Healthcare, 2022 - mdpi.com
Globally, there is a substantial unmet need to diagnose various diseases effectively. The
complexity of the different disease mechanisms and underlying symptoms of the patient …
complexity of the different disease mechanisms and underlying symptoms of the patient …
Artificial Intelligence in Cardiovascular Imaging: JACC State-of-the-Art Review
Data science is likely to lead to major changes in cardiovascular imaging. Problems with
timing, efficiency, and missed diagnoses occur at all stages of the imaging chain. The …
timing, efficiency, and missed diagnoses occur at all stages of the imaging chain. The …
[HTML][HTML] Comparing machine learning algorithms for predicting COVID-19 mortality
K Moulaei, M Shanbehzadeh… - BMC medical informatics …, 2022 - Springer
Background The coronavirus disease (COVID-19) hospitalized patients are always at risk of
death. Machine learning (ML) algorithms can be used as a potential solution for predicting …
death. Machine learning (ML) algorithms can be used as a potential solution for predicting …
Systems biology in cardiovascular disease: a multiomics approach
Omics techniques generate large, multidimensional data that are amenable to analysis by
new informatics approaches alongside conventional statistical methods. Systems theories …
new informatics approaches alongside conventional statistical methods. Systems theories …
Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network
The electrocardiogram (ECG) is a widely used medical test, consisting of voltage versus time
traces collected from surface recordings over the heart. Here we hypothesized that a deep …
traces collected from surface recordings over the heart. Here we hypothesized that a deep …
Artificial intelligence in precision cardiovascular medicine
Artificial intelligence (AI) is a field of computer science that aims to mimic human thought
processes, learning capacity, and knowledge storage. AI techniques have been applied in …
processes, learning capacity, and knowledge storage. AI techniques have been applied in …
[HTML][HTML] Interpretable prediction of 3-year all-cause mortality in patients with heart failure caused by coronary heart disease based on machine learning and SHAP
K Wang, J Tian, C Zheng, H Yang, J Ren, Y Liu… - Computers in biology …, 2021 - Elsevier
Background This study sought to evaluate the performance of machine learning (ML)
models and establish an explainable ML model with good prediction of 3-year all-cause …
models and establish an explainable ML model with good prediction of 3-year all-cause …
Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging
Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML),
which is a subset of AI wherein machines autonomously acquire information by extracting …
which is a subset of AI wherein machines autonomously acquire information by extracting …
Deep learning in radiology
MP McBee, OA Awan, AT Colucci, CW Ghobadi… - Academic radiology, 2018 - Elsevier
As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data
processing techniques. One such technique, deep learning (DL), has become a remarkably …
processing techniques. One such technique, deep learning (DL), has become a remarkably …
Towards diagnostic aided systems in coronary artery disease detection: a comprehensive multiview survey of the state of the art
Introduction. Coronary artery disease (CAD) is one of the main causes of death all over the
world. One way to reduce the mortality rate from CAD is to predict its risk and take effective …
world. One way to reduce the mortality rate from CAD is to predict its risk and take effective …