Cardiovascular

Metabolic Syndrome

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

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Finerenone Modulates PANoptosis to Improve Immune Microenvironment in Diabetic Nephropathy: A Machine Learning-Based Mechanistic Analysis.

Diabetic nephropathy (DN) is characterized by nephron degeneration induced by hyperglycemia, driven ...

Drug repurposing for osteoarthritis disease modification in the Early 21 Century.

Osteoarthritis (OA) is a leading cause of disability worldwide, significantly impacting patient mobi...

Thermodynamic analysis and intelligent modeling of statin drugs solubility in supercritical carbon dioxide.

Evaluating the solubility of various drugs in supercritical CO is a fundamental step in developing a...

Enhanced stroke risk prediction in hypertensive patients through deep learning integration of imaging and clinical data.

BACKGROUND: Stroke is one of the leading causes of death and disability worldwide, with a significan...

In silico analysis of atrial fibrillation and hypertension mechanism of action secondary to ibrutinib/acalabrutinib in chronic lymphocytic leukemia.

Ibrutinib and acalabrutinib are first- and next-generation Bruton Tyrosine Kinase inhibitors (BTKi),...

Machine learning-based high-benefit approach versus traditional high-risk approach in statin therapy: the Shizuoka Kokuho database study.

Statins are widely prescribed for the primary prevention of cardiovascular diseases, yet individual ...

Candesartan Mitigates Perioperative Neurocognitive Disorders by Modulating Hypertension-Linked Neuroinflammatory Factor.

Perioperative neurocognitive disorders (PND) are linked to neuroinflammation, a key factor in hypert...

PDSNet: Patient-Disease Dual Spatial Similarity Neural Networks for Predicting Heart Failure Risk Using Short Electronic Health Records.

Heart failure (HF) is a complex and heterogeneous syndrome caused by diverse factors, such as atrial...

Differential effects of demographics and risk factors on the nonlinear orthotropic mechanical properties of human femoropopliteal arteries.

Understanding how demographics and risk factors differentially affect the nonlinear orthotropic mech...

An integrated approach for novel PTP1B inhibitor screening: combining machine learning models, molecular docking, molecular and dynamics simulations.

Diabetes mellitus, particularly type 2 diabetes (T2DM), is a major global health challenge character...

A multimodal dataset for training deep learning models aimed at detecting and analyzing sleep apnea.

Sleep Apnea Syndrome (SAS) is a serious respiratory disorder that can lead to a range of complicatio...

Artificial intelligence-based diabetes risk prediction from longitudinal DXA bone measurements.

Diabetes mellitus (DM) is a serious global health concern that poses a significant threat to human l...

APOE ε4 carriers share immune-related proteomic changes across neurodegenerative diseases.

The APOE ε4 genetic variant is the strongest genetic risk factor for late-onset Alzheimer's disease ...

ML enhanced bioactivity prediction for angiotensin II receptor: A potential anti-hypertensive drug target.

The process of drug discovery is intricate, and encompasses a series of detailed phases of research,...

Identification of diagnostic biomarkers and dissecting immune microenvironment with crosstalk genes in the POAG and COVID-19 nexus.

An underlying association between primary open-angle glaucoma (POAG) and COVID-19 has been hypothesi...

Identification of right ventricular dysfunction with LogNNet based diagnostic model: A comparative study with supervised ML algorithms.

Right ventricular dysfunction (RVD) is strongly associated with increased mortality in patients with...

Assessment and management of portal hypertension in patients with MASLD: advances and caveats.

INTRODUCTION: Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly gaini...

Prediction of Cerebrospinal Fluid (CSF) Pressure with Generative Adversarial Network Synthetic Plasma-CSF Biomarker Pairing.

Non-invasive intracranial pressure (ICP) monitoring can help clinicians safely and efficiently monit...

Unsupervised learning using EHR and census data to identify distinct subphenotypes of newly diagnosed hypertension patients.

BACKGROUND: Hypertension (HTN) is a complex condition with significant heterogeneity in presentation...

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