Metabolic Syndrome

AI-Enabled Accurate Non-Invasive Assessment of Pulmonary Hypertension Progression via Multi-Modal Echocardiography

Echocardiographers can detect pulmonary hypertension using Doppler echocardiography; however, accurately assessing its progression often proves challenging. Right heart catheterization (RHC), the gold standard for precise evaluation, is invasive and unsuitable for routine use, limiting its practicality for timely diagnosis and monitoring of pulmonary hypertension progression. Here, we propose Me...

[Pulmonary vascular interventions: innovating through adaptation and advancing through differentiation].

Pulmonary vascular intervention technology, with its minimally invasive and precise advantages, has been a groundbreaking advancement in the treatment of pulmonary vascular diseases. Techniques such as balloon pulmonary angioplasty (BPA), pulmonary artery stenting, and percutaneous pulmonary artery denervation (PADN) have significantly improved the prognoses for conditions such as chronic thromboe...

Lipid Ratios for Diagnosis and Prognosis of Pulmonary Hypertension.

RATIONALE: Pulmonary hypertension (PH) poses a significant health threat. Current biomarkers for PH lack specificity and have poor prognostic capabili...

Construction of disability risk prediction model for the elderly based on machine learning.

The study aimed to develop a predictive model using machine learning algorithms, providing healthcare professionals with a novel tool for assessing di...

Combined assessment of stress hyperglycemia ratio and glycemic variability to predict all-cause mortality in critically ill patients with atherosclerotic cardiovascular diseases across different glucose metabolic states: an observational cohort study with machine learning.

BACKGROUND: Stress hyperglycemia ratio (SHR) and glycemic variability (GV) reflect acute glucose elevation and fluctuations, which correlate with adve...

Eliciting the Impact of Metformin and Statins on Prostate Cancer Outcomes from a Real-life National Database Analysis.

Several large analyses have revealed contradictory results regarding the association between prostate cancer (PC) survival and the use of statins pres...

A Conjoint Graph Representation Learning Framework for Hypertension Comorbidity Risk Prediction

The comorbidities of hypertension impose a heavy burden on patients and society. Early identification is necessary to prompt intervention, but it re...

Integrating Artificial Intelligence in the Diagnosis and Management of Metabolic Syndrome: A Comprehensive Review.

BACKGROUND: Metabolic syndrome (MetS) is a progressive chronic pathophysiological state characterised by abdominal obesity, hypertension, hyperglycaem...

Artificial intelligence-based echocardiography assessment to detect pulmonary hypertension.

BACKGROUND: Tricuspid regurgitation jet velocity (TRJV) on echocardiography is used for screening patients with suspected pulmonary hypertension (PH)....

Expert consensus document on artificial intelligence of the Italian Society of Cardiology.

Artificial intelligence (AI), a branch of computer science focused on developing algorithms that replicate intelligent behaviour, has recently been us...

Glucagon and insulin production in pancreatic cells modeled using Petri nets and Boolean networks

Diabetes is a civilization chronic disease characterized by a constant elevated concentration of glucose in the blood. Many processes are involved i...

GlyTwin: Digital Twin for Glucose Control in Type 1 Diabetes Through Optimal Behavioral Modifications Using Patient-Centric Counterfactuals

Frequent and long-term exposure to hyperglycemia (i.e., high blood glucose) increases the risk of chronic complications such as neuropathy, nephropa...

SydneyScapes: Image Segmentation for Australian Environments

Autonomous Vehicles (AVs) are being partially deployed and tested across various global locations, including China, the USA, Germany, France, Japan,...

Deep Learning for Cardiovascular Risk Assessment: Proxy Features from Carotid Sonography as Predictors of Arterial Damage

In this study, hypertension is utilized as an indicator of individual vascular damage. This damage can be identified through machine learning techni...

Maternal and Fetal Health Status Assessment by Using Machine Learning on Optical 3D Body Scans

Monitoring maternal and fetal health during pregnancy is crucial for preventing adverse outcomes. While tests such as ultrasound scans offer high ac...

Predicting Prostate Cancer Diagnosis Using Machine Learning Analysis of Healthcare Utilization Patterns.

This study investigated healthcare utilization patterns prior to prostate cancer diagnoses, aiming to develop machine learning models for early predic...

Automated Bi-Ventricular Segmentation and Regional Cardiac Wall Motion Analysis for Rat Models of Pulmonary Hypertension.

Artificial intelligence-based cardiac motion mapping offers predictive insights into pulmonary hypertension (PH) disease progression and its impact on...

Integrating Large Language Models with Human Expertise for Disease Detection in Electronic Health Records

Objective: Electronic health records (EHR) are widely available to complement administrative data-based disease surveillance and healthcare performa...

Diagnosis of Pulmonary Hypertension by Integrating Multimodal Data with a Hybrid Graph Convolutional and Transformer Network

Early and accurate diagnosis of pulmonary hypertension (PH) is essential for optimal patient management. Differentiating between pre-capillary and p...

Identification of hypertension subtypes using microRNA profiles and machine learning.

OBJECTIVE: Hypertension is a major cardiovascular risk factor affecting about 1 in 3 adults. Although the majority of hypertension cases (∼90%) are cl...