Hypertension

T2D-LVDD: neural network-based predictive models for left ventricular diastolic dysfunction in type 2 diabetes.

Cardiovascular disease complications are the leading cause of morbidity and mortality in patients with Type 2 diabetes (T2DM). Left ventricular diastolic dysfunction (LVDD) is one of the earliest myocardial characteristics of diabetic cardiac dysfunction. Therefore, we aimed to develop an LVDD-risk predictive model to diagnose cardiac dysfunction before severe cardiovascular complications arise. W...

Prediction of Poor Visual Outcomes at Idiopathic Intracranial Hypertension Diagnosis Using a Supervised Machine Learning Algorithm.

BACKGROUND: Idiopathic intracranial hypertension (IIH) is a vision-threatening disorder mainly affecting women of a reproductive age. Prompt diagnosis and intervention are vital to prevent vision loss, but validated tools to predict visual outcomes are lacking. The purpose of this study was to create a machine learning algorithm predicting poor visual outcomes at the time that the diagnosis of IIH...

Semi-quantitative analysis of Right Ventricular Myocardial First-pass Perfusion Using Cardiac Magnetic Resonance Imaging in Systemic Sclerosis and Pulmonary Arterial Hypertension.

BACKGROUND: Right ventricular (RV) myocardial perfusion has been touted as a primary mechanism to understand impairment in RV function in patients wit...

Mitral annular plane systolic excursion to left atrial volume ratio - a strainless relation with left ventricular filling pressures.

Left atrial reservoir strain (LASr) offers diagnostic and prognostic value in patients with heart failure. However, LASr may be technically challengin...

Hydroalcoholic extract from Syagrus cocoides Martius almonds (ariri coconut) induces diuretic effects in rodents.

BACKGROUND: Recent studies point to the great biotechnological potential of Syagrus cocoides as a tool for treating cardiovascular disorders.

Prediction of perimetric progression in ocular hypertension and open angle glaucoma based on corneal biomechanics.

PurposeTo identify parameters that are significant risk predictors of visual field (VF) progression in patients with ocular hypertension (OHT) or earl...

Predicting Visual Acuity after Retinal Vein Occlusion Anti-VEGF Treatment: Development and Validation of an Interpretable Machine Learning Model.

Accurate prediction of post-treatment visual acuity in macular edema secondary to retinal vein occlusion (RVO-ME) is critical for optimizing anti-VEGF...

Retinal Ischemic Perivascular Lesions (RIPLs) as Potential Biomarkers for Systemic Vascular Diseases: A Narrative Review of the Literature.

Retinal ischemic perivascular lesions (RIPLs) are characteristic focal thinning of the inner nuclear layer, with an upward expansion of the outer nucl...

Risk for ocular hypertension progression to early glaucoma: A predictive model and key predictors.

BACKGROUND: Ocular hypertension (OHT) is the most significant risk factor for glaucoma. We aimed to develop a model for predicting OHT progression to ...

Exploring hypoxia driven subtypes of pulmonary arterial hypertension through transcriptomics single cell sequencing and machine learning.

Pulmonary arterial hypertension (PAH) is a progressive cardiovascular disease characterized by elevated pulmonary arterial pressure, leading to right ...

GDM-BC: Non-invasive body composition dataset for intelligent prediction of Gestational Diabetes Mellitus.

Gestational Diabetes Mellitus (GDM) refers to any degree of impaired glucose tolerance with onset or first recognition during pregnancy. As a high-pre...

Diagnostic MicroRNA Signatures to Support Classification of Pulmonary Hypertension.

BACKGROUND: Patients with pulmonary hypertension (PH) are classified based on disease pathogenesis and hemodynamic drivers. Classification informs tre...

Predicting mortality and risk factors of sepsis related ARDS using machine learning models.

Sepsis related acute respiratory distress syndrome (ARDS) is a common and serious disease in clinic. Accurate prediction of in-hospital mortality of p...

Predicting cerebral infarction and transient ischemic attack in healthy individuals and those with dysmetabolism: a machine learning approach combined with routine blood tests.

Ischemic cerebral infarction is the most prevalent type of stroke, causing significant disability and death worldwide. Transient ischemic attack (TIA)...

Comparing machine learning models for predicting preoperative DVT incidence in elderly hypertensive patients with hip fractures: a retrospective analysis.

Hip fractures in the elderly present a significant public health challenge globally, especially among patients with hypertension, who are at an increa...

Risk Factors and Outcomes of Hemorrhagic Transformation in Acute Ischemic Stroke Following Thrombolysis: Analysis of a Single-Center Experience and Review of the Literature.

: This is a retrospective study conducted at the Clinical County Hospital of Craiova, Romania, providing valuable insights into hemorrhagic transforma...

Deep learning models for segmenting phonocardiogram signals: a comparative study.

Cardiac auscultation requires the mechanical vibrations occurring on the body's surface, which carries a range of sound frequencies. These sounds are ...

Peripheral blood immune landscape and NXPE3 as a novel biomarker for hypertensive intracerebral hemorrhage risk prediction and targeted therapy.

We employed bulk RNA-seq and scRNA-seq techniques to analyze the immune dysregulation in patients with intracerebral hemorrhage (ICH). The study revea...

Machine learning integration of multimodal data identifies key features of circulating NT-proBNP in people without cardiovascular diseases.

N-Terminal Pro-Brain Natriuretic Peptide (NT-proBNP) is important for diagnosing and predicting heart failure or many other diseases. However, few stu...

Is artificial intelligence superior to traditional regression methods in predicting prognosis of adult traumatic brain injury?

Traumatic brain injury (TBI) is a significant global health issue with high morbidity and mortality rates. Recent studies have shown that machine lear...