Metabolic Syndrome

Deep Learning-Based Prediction of Cardiopulmonary Disease in Retinal Images of Premature Infants.

IMPORTANCE: Bronchopulmonary dysplasia (BPD) and pulmonary hypertension (PH) are leading causes of morbidity and mortality in premature infants. OBJECTIVE: To determine whether images obtained as part of retinopathy of prematurity (ROP) screening might contain features associated with BPD and PH in infants and whether a multimodal model integrating imaging features with demographic risk factors mi...

How do chronic diseases affect personal and household income? A double debiased machine learning analysis of the China health and retirement longitudinal study (CHARLS) in older adults.

OBJECTIVES: This study aimed to investigate the impacts of chronic diseases such as hypertension, dyslipidaemia and diabetes on personal and household income among ageing Chinese adults. The primary hypothesis was that these chronic diseases have differential effects on the socioeconomic status of individuals and households, with gender and age influencing these relationships. DESIGN: Prospective ...

The discordance of remnant cholesterol and low-density lipoprotein cholesterol as a predictor of diabetes, diabetic microvascular diseases, and cardiovascular disease.

BACKGROUND: The impact of discordance between remnant cholesterol (RC) and low-density lipoprotein cholesterol (LDL-c) on diabetes, diabetic kidney di...

Patient-specific deep offline artificial pancreas for blood glucose regulation in type 1 diabetes.

Due to insufficient insulin secretion, patients with type 1 diabetes mellitus (T1DM) are prone to blood glucose fluctuations ranging from hypoglycemia...

Machine Learning Prediction of Pharmacogenetic Testing Uptake Among Opioid-Prescribed Patients Using Electronic Health Records: Retrospective Cohort Study.

BACKGROUND: Opioids are a widely prescribed class of medication for pain management. However, they have variable efficacy and adverse effects among pa...

Preoperative Neuroimaging Markers, Clinical Severity Measures, and Shunt Characteristics for Predicting Shunt Revision in Idiopathic Intracranial Hypertension: An Explainable Machine-Learning Study.

BACKGROUND AND PURPOSE: Surgical shunt placement is a common treatment for idiopathic intracranial hypertension (IIH) but is hampered by high revision...

Head-to-head comparison of the ability of the cardiometabolic index and triglyceride-glucose index to predict 3-year major adverse cardiovascular events in patients with atrial fibrillation: insights from a community cohort.

BACKGROUND: Atrial fibrillation (AF) represents the most common sustained cardiac arrhythmia and confers an elevated risk of major adverse cardiovascu...

Vascular cognitive impairment and dementia: Prevention, treatments, mechanisms and management options for the future.

Vascular Cognitive Impairment and Dementia (VCID), the second most common form of dementia, is becoming increasingly prevalent worldwide. However, cur...

Unveiling the relationship between stress-hyperglycemia ratio and cardiometabolic multimorbidity risk using interpretable machine learning.

BACKGROUND: Cardiometabolic multimorbidity (CMM) is the simultaneous manifestation of multiple cardiovascular and metabolic diseases, and it has arise...

Continuous Glucose Monitoring-Based Machine Learning Identification of Diurnal Glycemic Patterns and Diabetes Distress in Type 2 Diabetes.

BACKGROUND: To identify diurnal glycemic patterns in adults with type 2 diabetes (T2D) using continuous glucose monitoring (CGM)-based machine learnin...

Machine learning and SHAP values for predicting coronary artery disease risk in Xinjiang, China.

BACKGROUND: Accurate individual risk assessment is crucial for guiding and improving the prevention of atherosclerotic cardiovascular disease (ASCVD)....

Prediction model for cardiovascular mortality risk in asthma patients based on machine learning.

BackgroundAsthma is a common chronic respiratory disease, cardiovascular disease (CVD) mortality constitutes a major public health concern. At present...

Non-invasive blood pressure monitoring using wearables for cardiovascular risk assessment: a systematic review.

PURPOSE: Cardiovascular diseases are the leading causes of mortality in women worldwide, with hypertension being a major risk factor. While traditiona...

Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review.

BACKGROUND: Renal cell carcinoma (RCC) is a common, often lethal kidney cancer that originates in the renal cortex. Its incidence is rising, and major...

AI-assisted multimodal assessment for right ventricular function from echocardiography predicts mortality in patients with pulmonary hypertension and right heart failure.

Right ventricular (RV) strain is an important factor in evaluating RV function. This study aimed to predict mortality in patients with pulmonary hyper...

Stress hyperglycemia ratio improves machine learning-based mortality risk prediction in critically ill COVID-19 patients: a multicenter retrospective study.

Properties of AgNPs stabilized with polyvinylpyrrolidone relevant to antidiabetic agents.

Type 2 diabetes mellitus (DM2) is a chronic metabolic disease. Silver nanoparticles (AgNPs) show promise in their treatment. This study assessed the p...

Artificial intelligence based retinal imaging for cardiovascular risk and statin guidance in retinal vein occlusion.

Joint processing technology of laser radar and optical image for power distribution.

Due to the unpredictability of loads and the complexity of fault propagation, modern power distribution networks require advanced technologies for fau...

Systematic Review on Deep Learning Algorithms for Blood Glucose Forecasting in Type 1 Diabetes.

Type 1 Diabetes (T1D) is a chronic metabolic disease characterized by elevated blood glucose (BG) concentrations, resulting from the immune-mediated d...