Cardiovascular

Dyslipidemia

Latest AI and machine learning research in dyslipidemia for healthcare professionals.

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Coupling analysis of heart rate variability and cortical arousal using a deep learning algorithm.

Frequent cortical arousal is associated with cardiovascular dysfunction among people with sleep-diso...

Identifying Reasons for Statin Nonuse in Patients With Diabetes Using Deep Learning of Electronic Health Records.

Background Statins are guideline-recommended medications that reduce cardiovascular events in patien...

A genome-wide association study of childhood adiposity and blood lipids.

The rising prevalence of childhood obesity and dyslipidaemia is a major public health concern due t...

Automated in-depth cerebral arterial labelling using cerebrovascular vasculature reframing and deep neural networks.

Identifying the cerebral arterial branches is essential for undertaking a computational approach to ...

Increasing transparency in machine learning through bootstrap simulation and shapely additive explanations.

Machine learning methods are widely used within the medical field. However, the reliability and effi...

Lorcaserin and phentermine exert anti-obesity effects with modulation of the gut microbiota.

Although drugs have been reported to modulate the gut microbiota, the effects of anti-obesity drugs ...

Mechano-fluorescence actuation in single synaptic vesicles with a DNA framework nanomachine.

Biomimetic machines that can convert mechanical actuation to adaptive coloration in a manner analogo...

Efficient targeted learning of heterogeneous treatment effects for multiple subgroups.

In biomedical science, analyzing treatment effect heterogeneity plays an essential role in assisting...

Aortic Distensibility Measured by Automated Analysis of Magnetic Resonance Imaging Predicts Adverse Cardiovascular Events in UK Biobank.

Background Automated analysis of cardiovascular magnetic resonance images provides the potential to ...

Finding the influential clinical traits that impact on the diagnosis of heart disease using statistical and machine-learning techniques.

In recent years, the omnipresence of cardiac problems has been recognized as an epidemic. With the c...

Gene-gene interaction detection with deep learning.

The extent to which genetic interactions affect observed phenotypes is generally unknown because cur...

[Future of interventional cardiology : Does everything revolve around AI and robotics?].

In recent years, software-assisted imaging systems, such as computed tomography, have contributed to...

Using modern risk engines and machine learning/artificial intelligence to predict diabetes complications: A focus on the BRAVO model.

Management of diabetes requires a multifaceted approach of risk factor reduction; through management...

Development of non-bias phenotypic drug screening for cardiomyocyte hypertrophy by image segmentation using deep learning.

The number of patients with heart failure and related deaths is rapidly increasing worldwide, making...

Automated detection of intracranial artery stenosis and occlusion in magnetic resonance angiography: A preliminary study based on deep learning.

BACKGROUND AND OBJECTIVES: Intracranial atherosclerotic stenosis of a major intracranial artery is t...

Improved Harris Hawks Optimization with Hybrid Deep Learning Based Heating and Cooling Load Prediction on residential buildings.

In digital era, energy efficient building remains a hot research topic because of increasing concern...

A Novel Ground Metric for Optimal Transport-Based Chronological Age Estimation.

Label distribution learning (LDL) is the state-of-the-art approach to dealing with a number of real-...

Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation.

Thanks to large-scale labeled training data, deep neural networks (DNNs) have obtained remarkable su...

Research progress and hotspot of the artificial intelligence application in the ultrasound during 2011-2021: A bibliometric analysis.

Ultrasound, as a common clinical examination tool, inevitably has human errors due to the limitation...

Deep Learning of Coronary Calcium Scores From PET/CT Attenuation Maps Accurately Predicts Adverse Cardiovascular Events.

BACKGROUND: Assessment of coronary artery calcium (CAC) by computed tomographic (CT) imaging provide...

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