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Cardiovascular Diseases

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Heart age estimated using explainable advanced electrocardiography.

Scientific reports
Electrocardiographic (ECG) Heart Age conveying cardiovascular risk has been estimated by both Bayesian and artificial intelligence approaches. We hypothesised that explainable measures from the 10-s 12-lead ECG could successfully predict Bayesian 5-m...

Cardiovascular Disease Diagnosis from DXA Scan and Retinal Images Using Deep Learning.

Sensors (Basel, Switzerland)
Cardiovascular diseases (CVD) are the leading cause of death worldwide. People affected by CVDs may go undiagnosed until the occurrence of a serious heart failure event such as stroke, heart attack, and myocardial infraction. In Qatar, there is a lac...

Exploration of Black Boxes of Supervised Machine Learning Models: A Demonstration on Development of Predictive Heart Risk Score.

Computational intelligence and neuroscience
Machine learning (ML) often provides applicable high-performance models to facilitate decision-makers in various fields. However, this high performance is achieved at the expense of the interpretability of these models, which has been criticized by p...

ResNet-50 for 12-Lead Electrocardiogram Automated Diagnosis.

Computational intelligence and neuroscience
Nowadays, the implementation of Artificial Intelligence (AI) in medical diagnosis has attracted major attention within both the academic literature and industrial sector. AI would include deep learning (DL) models, where these models have been achiev...

Artificial intelligence applied to cardiovascular imaging, a critical focus on echocardiography: The point-of-view from "the other side of the coin".

Journal of clinical ultrasound : JCU
Cardiovascular imaging has achieved a crucial role in the management of cardiovascular diseases. In this field, echocardiography advantages include wide availability, portability, and affordability, at a relatively low cost. However, echocardiographi...

Very low-volume interval training improves nonalcoholic fatty liver disease fibrosis score and cardiometabolic health in adults with obesity and metabolic syndrome.

Journal of physiology and pharmacology : an official journal of the Polish Physiological Society
Non-alcoholic fatty liver disease (NAFLD) and cardiometabolic disorders are highly prevalent in obese individuals. Physical exercise is an important element in obesity and metabolic syndrome (MetS) treatment. However, the vast majority of individuals...

Research on Disease Prediction Method Based on R-Lookahead-LSTM.

Computational intelligence and neuroscience
Cardiovascular disease is one of the most serious diseases that threaten human health in the world today. Therefore, establishing a high-quality disease prediction model is of great significance for the prevention and treatment of cardiovascular dise...

Deep Learning in mHealth for Cardiovascular Disease, Diabetes, and Cancer: Systematic Review.

JMIR mHealth and uHealth
BACKGROUND: Major chronic diseases such as cardiovascular disease (CVD), diabetes, and cancer impose a significant burden on people and health care systems around the globe. Recently, deep learning (DL) has shown great potential for the development o...

Multi-task Deep Learning of Myocardial Blood Flow and Cardiovascular Risk Traits from PET Myocardial Perfusion Imaging.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: Advanced cardiac imaging with positron emission tomography (PET) is a powerful tool for the evaluation of known or suspected cardiovascular disease. Deep learning (DL) offers the possibility to abstract highly complex patterns to optimize...

A Reliable Machine Intelligence Model for Accurate Identification of Cardiovascular Diseases Using Ensemble Techniques.

Journal of healthcare engineering
Machine intelligence can convert raw clinical data into an informational source that helps make decisions and predictions. As a result, cardiovascular diseases are more likely to be addressed as early as possible before affecting the lifespan. Artifi...