Hypertension

Vitamin D and COVID-19 - Let's Explore the Relationship!

Vitamin D plays a protective role against COVID-19. Patients with deficiency of vitamin D are more prone to severe SARS-CoV-2 infections. It is known to enhance human β-defensin 2 and antimicrobial peptide. Vitamin D can easily stabilise and manage immunological reactions against SARS-CoV-2. It can also suppress the cytokine storm by boosting the innate system. RT-PCR confirmed COVID-19 positive ...

A Deep Learning Approach to Predict Blood Pressure from PPG Signals.

Blood Pressure (BP) is one of the four primary vital signs indicating the status of the body's vital (life-sustaining) functions. BP is difficult to continuously monitor using a sphygmomanometer (i.e. a blood pressure cuff), especially in everyday-setting. However, other health signals which can be easily and continuously acquired, such as photoplethysmography (PPG), show some similarities with th...

Automatic Onsets and Systolic Peaks Detection and Segmentation of Arterial Blood Pressure Waveforms using Fully Convolutional Neural Networks.

Arterial blood pressure (ABP) waveform is a common physiological signal that contains a wealth of cardiovascular information. According to the cardiac...

Mortality risk stratification using artificial intelligence-augmented electrocardiogram in cardiac intensive care unit patients.

AIMS: An artificial intelligence-augmented electrocardiogram (AI-ECG) algorithm can identify left ventricular systolic dysfunction (LVSD). We sought t...

Verification and comparison of three prediction models of ischemic stroke in young adults based on the back propagation neural networks.

This work aims to explore risk factors for ischemic stroke in young adults and analyze the Traditional Vascular Risk Factors Model based on age, hyper...

The Effectiveness of a Deep Learning Model to Detect Left Ventricular Systolic Dysfunction from Electrocardiograms.

Deep learning models can be applied to electrocardiograms (ECGs) to detect left ventricular (LV) dysfunction. We hypothesized that applying a deep lea...

The Role of Chronic Renal Disease on the Linking Obesity/Hypertension.

Obesity is accompanied by several disorders. This study investigated the role of chronic renal disease on the linking obesity/hypertension (HTN). It a...

Artificial Intelligence and Hypertension: Recent Advances and Future Outlook.

Prevention and treatment of hypertension (HTN) are a challenging public health problem. Recent evidence suggests that artificial intelligence (AI) has...

Assessment and prediction of restless leg syndrome (RLS) in patients with diabetes mellitus type II through artificial intelligence (AI).

This study aimed to diagnose the incidence of restless leg syndrome (RLS) in patients with diabetes mellitus (DM) type-2, thorough artificial intellig...

Machine Learning Assessment of Left Ventricular Diastolic Function Based on Electrocardiographic Features.

BACKGROUND: Left ventricular (LV) diastolic dysfunction is recognized as playing a major role in the pathophysiology of heart failure; however, clinic...

Constructing Inpatient Pressure Injury Prediction Models Using Machine Learning Techniques.

The incidence rate of pressure injury is a critical nursing quality indicator in clinic care; consequently, factors causing pressure injury are divers...

An Empirical Method of Automatic Pattern Extraction for Clinical Text Classification.

Clinical text classification is an indispensable and extensively studied problem in medical text processing. Existing research primarily employs machi...

Machine Learning and Deep Neural Network Applications in the Thorax: Pulmonary Embolism, Chronic Thromboembolic Pulmonary Hypertension, Aorta, and Chronic Obstructive Pulmonary Disease.

The radiologic community is rapidly integrating a revolution that has not fully entered daily practice. It necessitates a close collaboration between ...

Adverse drug event rates in pediatric pulmonary hypertension: a comparison of real-world data sources.

OBJECTIVE: Real-world data (RWD) are increasingly used for pharmacoepidemiology and regulatory innovation. Our objective was to compare adverse drug e...

A Machine Learning-Based Model to Predict Acute Traumatic Coagulopathy in Trauma Patients Upon Emergency Hospitalization.

Acute traumatic coagulopathy (ATC) is an extremely common but silent murderer; this condition presents early after trauma and impacts approximately 30...

Diastolic Function Evaluation: What Can We Learn From Machine Learning?

Retinopathy Analysis Based on Deep Convolution Neural Network.

At medical checkups or mass screenings, the fundus examination is effective for early detection of systemic hypertension, arteriosclerosis, diabetic r...

Evaluating the Effect of Dexmedetomidine on Hemodynamic Status of Patients with Septic Shock Admitted to Intensive Care Unit: A Single-Blind Randomized Controlled Trial.

Septic shock, known as the most severe complication of sepsis, is a serious medical condition that can lead to death. Clinical symptoms of sepsis incl...

Accuracy of Kalman Filtering in Forecasting Visual Field and Intraocular Pressure Trajectory in Patients With Ocular Hypertension.

IMPORTANCE: Techniques that properly identify patients in whom ocular hypertension (OHTN) is likely to progress to open-angle glaucoma can assist clin...

Relationship of soluble ST2 to pulmonary hypertension severity in patients undergoing cardiac resynchronization therapy.

BACKGROUND: Pulmonary hypertension (PH) is an adverse prognostic marker in patients undergoing cardiac resynchronization therapy (CRT). We sought to d...