Cardiovascular

Metabolic Syndrome

Latest AI and machine learning research in metabolic syndrome for healthcare professionals.

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Predicting depression severity using machine learning models: Insights from mitochondrial peptides and clinical factors.

Depression presents a significant challenge to global mental health, often intertwined with factors ...

Analyzing Demographic Grocery Purchase Patterns in Kenyan Supermarkets Through Unsupervised Learning Techniques.

Kenya is experiencing a significant increase in the prevalence of non-communicable diseases (NCDs) s...

StackAHTPs: An explainable antihypertensive peptides identifier based on heterogeneous features and stacked learning approach.

Hypertension, often known as high blood pressure, is a major concern to millions of individuals glob...

Application of machine learning algorithms in predicting new onset hypertension: a study based on the China Health and Nutrition Survey.

BACKGROUND: Hypertension is a serious chronic disease that can significantly lead to various cardiov...

Risk prediction of integrated traditional Chinese and western medicine for diabetes retinopathy based on optimized gradient boosting classifier model.

In order to take full advantage of traditional Chinese medicine (TCM) and western medicine, combined...

Machine Learning Reveals the Contribution of Lipoproteins to Liver Triglyceride Content and Inflammation.

CONTEXT: Metabolic dysfunction-associated steatotic liver disease (MASLD) is currently the most comm...

Determinants of developing cardiovascular disease risk with emphasis on type-2 diabetes and predictive modeling utilizing machine learning algorithms.

This research aims to enhance our comprehensive understanding of the influence of type-2 diabetes on...

Primary care research on hypertension: A bibliometric analysis using machine-learning.

Hypertension is one of the most important chronic diseases worldwide. Hypertension is a critical con...

Identification of fatty acid metabolism signature genes in patients with pulmonary arterial hypertension using WGCNA and machine learning.

OBJECTIVE: To investigate the signature genes of fatty acid metabolism and their association with im...

Bridging Gaps with Generative AI: Enhancing Hypertension Monitoring Through Patient and Provider Insights.

This study introduces a Generative Artificial Intelligence (GenAI) assistant designed to address key...

Machine Learning Approaches for Blood Pressure Classification from Photoplethysmogram: A Comparative Analysis.

The cuffless estimation of blood pressure (BP) has become a prominent area of research in recent yea...

Advancements in Continuous Glucose Monitoring: Integrating Deep Learning and ECG Signal.

This paper presents a novel approach to noninvasive hyperglycemia monitoring utilizing electrocardio...

DeLIVR: a deep learning approach to IV regression for testing nonlinear causal effects in transcriptome-wide association studies.

Transcriptome-wide association studies (TWAS) have been increasingly applied to identify (putative) ...

Deep learning to assess right ventricular ejection fraction from two-dimensional echocardiograms in precapillary pulmonary hypertension.

BACKGROUND: Precapillary pulmonary hypertension (PH) is characterized by a sustained increase in rig...

Comparison of machine learning models to predict complications of bariatric surgery: A systematic review.

Due to changes in lifestyle, bariatric surgery is expanding worldwide. However, this surgery has nu...

HTNpedia: A Knowledge Base for Hypertension Research.

BACKGROUND: Hypertension is notably a serious public health concern due to its high prevalence and s...

Antihypertensive prescribing patterns in non-dialysis dependent chronic kidney disease: Findings from the Salford Kidney Study.

BACKGROUND: Hypertension is commonly observed in patients living with chronic kidney disease (CKD). ...

H2Opred: a robust and efficient hybrid deep learning model for predicting 2'-O-methylation sites in human RNA.

2'-O-methylation (2OM) is the most common post-transcriptional modification of RNA. It plays a cruci...

DETERMINATION OF THE PRA POSITIVITY PERCENTAGE IN MALE PATIENTS WITH CHRONIC KIDNEY DISEASE BY USING FLOW CYTOMETRY TECHNIQUE.

The antibodies directed against human leukocyte antigen (HLA) molecules, which play a crucial role i...

Assessing the Generalizability of a Deep Learning-based Automated Atrial Fibrillation Algorithm.

Automated detection of atrial fibrillation (AF) from electrocardiogram (ECG) traces remains a challe...

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