Metabolic Syndrome

Effectiveness of Nicotinamide Phosphoribosyltransferase/Pre-B Cell Colony-enhancing Factor/Visfatin in preventing High Glucose-induced Neurotoxicity in an In-vitro Model of Diabetic Neuropathy.

INTRODUCTION: Diabetic neuropathy is a well-known complication of diabetes. Recently, hyperglycemia-induced toxicity has been confirmed to participates in multiple cellular pathways typical for neural deterioration. Nicotinamide phosphoribosyltransferase/pre-b cell colony-enhancing factor (Nampt/PBEF)/visfatin is a novel endogenous ligand that some studies have shown its neuroprotective effects on...

Correlation Between Statin Use and Symptomatic Venous Thromboembolism Incidence in Patients With Ankle Fracture: A Machine Learning Approach.

BACKGROUND: Identifying factors that correlate with the incidence of venous thromboembolism (VTE) has the potential to improve VTE prevention and positively influence decision-making regarding prophylaxis. In this study, we aimed to investigate the correlation between statin consumption and the incidence of VTE in patients who sustained an ankle fracture.

CURATE.AI-assisted dose titration for anti-hypertensive personalized therapy: study protocol for a multi-arm, randomized, pilot feasibility trial using CURATE.AI (CURATE.AI ADAPT trial).

AIMS: Artificial intelligence-driven small data platforms such as CURATE.AI hold potential for personalized hypertension care by assisting physicians ...

Real-time dual prediction of intradialytic hypotension and hypertension using an explainable deep learning model.

Both intradialytic hypotension (IDH) and hypertension (IDHTN) are associated with poor outcomes in hemodialysis patients, but a model predicting dual ...

Insulin signaling in insulin-dysregulated Icelandic horses.

The underlying molecular mechanisms leading to insulin dysregulation are poorly understood in horses. Therefore, this study aimed to determine if insu...

DeepADRA2A: predicting adrenergic α2a inhibitors using deep learning.

Adrenergic α2a (ADRA2A) receptors play a crucial role in modulating various physiological actions, thereby influencing the proper functioning of diffe...

Automated Arrhythmia Classification Using Farmland Fertility Algorithm with Hybrid Deep Learning Model on Internet of Things Environment.

In recent years, the rapid progress of Internet of Things (IoT) solutions has offered an immense opportunity for the collection and dissemination of h...

HDL: Hybrid Deep Learning for the Synthesis of Myocardial Velocity Maps in Digital Twins for Cardiac Analysis.

Synthetic digital twins based on medical data accelerate the acquisition, labelling and decision making procedure in digital healthcare. A core part o...

Blood pressure estimation and classification using a reference signal-less photoplethysmography signal: a deep learning framework.

The markers that help to predict th function of a cardiovascular system are hemodynamic parameters like blood pressure (BP), stroke volume, heart rate...

Osteoporosis in Adrenal Insufficiency: Could Metformin be Protective?

Adrenal insufficiency (AI) is a serious disorder characterized by the adrenal glucocorticoid deficiency. Regardless of the etiology, AI patients need ...

Chronic thromboembolic pulmonary hypertension: realising the potential of multimodal management.

Chronic thromboembolic pulmonary hypertension (CTEPH) is a rare complication of acute pulmonary embolism. Important advances have enabled better under...

A novel CS-NET architecture based on the unification of CNN, SVM and super-resolution spectrogram to monitor and classify blood pressure using photoplethysmography.

CONTEXT: Continuous blood pressure (BP) monitoring plays an important role while treating various cardiovascular diseases and hypertension. A high cor...

Stratification of diabetes in the context of comorbidities, using representation learning and topological data analysis.

Diabetes is a heterogenous, multimorbid disorder with a large variation in manifestations, trajectories, and outcomes. The aim of this study is to val...

Deep learning for deterioration prediction of COVID-19 patients based on time-series of three vital signs.

Unrecognized deterioration of COVID-19 patients can lead to high morbidity and mortality. Most existing deterioration prediction models require a larg...

Predicting blood pressure from face videos using face diagnosis theory and deep neural networks technique.

Hypertension is a major cause of cardiovascular diseases. Accurate and convenient measurement of blood pressure are necessary for the detection, treat...

Hardware-Efficient Scheme for Trailer Robot Parking by Truck Robot in an Indoor Environment with Rendezvous.

Autonomous grounded vehicle-based social assistance/service robot parking in an indoor environment is an exciting challenge in urban cities. There are...

A deep learning method for continuous noninvasive blood pressure monitoring using photoplethysmography.

. The aim of this study is to investigate continuous blood pressure waveform estimation from a plethysmography (PPG) signal, thus providing more human...

Combating hypertension beyond genome-wide association studies: Microbiome and artificial intelligence as opportunities for precision medicine.

The single largest contributor to human mortality is cardiovascular disease, the top risk factor for which is hypertension (HTN). The last two decades...

Deep learning-based measurement of echocardiographic data and its application in the diagnosis of sudden cardiac death.

This study aimed to evaluate the potential of deep learning applied to the measurement of echocardiographic data in patients with sudden cardiac death...

Machine-learning predictive model of pregnancy-induced hypertension in the first trimester.

In the first trimester of pregnancy, accurately predicting the occurrence of pregnancy-induced hypertension (PIH) is important for both identifying hi...