Cardiovascular

Metabolic Syndrome

Latest AI and machine learning research in metabolic syndrome for healthcare professionals.

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Tinnitus Frequency is Higher in Patients with Chronic Heart Failure with Reduced Ejection Fraction and is Closely Related to NT-proBNP Level.

There is not enough information about tinnitus and related parameters in patients with heart failure...

Development of a Wearable Camera and AI Algorithm for Medication Behavior Recognition.

As many as 40% to 50% of patients do not adhere to long-term medications for managing chronic condit...

Regression plane concept for analysing continuous cellular processes with machine learning.

Biological processes are inherently continuous, and the chance of phenotypic discovery is significan...

Prediction of brain age from routine T2-weighted spin-echo brain magnetic resonance images with a deep convolutional neural network.

Our study investigated the feasibility and clinical relevance of brain age prediction using axial T2...

Pre-existing and machine learning-based models for cardiovascular risk prediction.

Predicting the risk of cardiovascular disease is the key to primary prevention. Machine learning has...

A fused-image-based approach to detect obstructive sleep apnea using a single-lead ECG and a 2D convolutional neural network.

Obstructive sleep apnea (OSA) is a common chronic sleep disorder that disrupts breathing during slee...

Machine learning algorithm for characterizing risks of hypertension, at an early stage in Bangladesh.

BACKGROUND AND AIMS: Hypertension has become a major public health issue as the prevalence and risk ...

Using CNN and HHT to Predict Blood Pressure Level Based on Photoplethysmography and Its Derivatives.

According to the WTO, there were 1.13 billion hypertension patients worldwide in 2015. The WTO encou...

Artificial Intelligence in Hypertension: Seeing Through a Glass Darkly.

Hypertension remains the largest modifiable cause of mortality worldwide despite the availability of...

Blood Pressure Morphology Assessment from Photoplethysmogram and Demographic Information Using Deep Learning with Attention Mechanism.

Arterial blood pressure (ABP) is an important vital sign from which it can be extracted valuable inf...

Assessment of Thoracic Pain Using Machine Learning: A Case Study from Baja California, Mexico.

Thoracic pain is a shared symptom among gastrointestinal diseases, muscle pain, emotional disorders,...

Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients.

Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that ma...

Risk factors analysis of COVID-19 patients with ARDS and prediction based on machine learning.

COVID-19 is a newly emerging infectious disease, which is generally susceptible to human beings and ...

Associated factors of white matter hyperintensity volume: a machine-learning approach.

To identify the most important parameters associated with cerebral white matter hyperintensities (WM...

Prediction of death status on the course of treatment in SARS-COV-2 patients with deep learning and machine learning methods.

BACKGROUND AND OBJECTIVE: The new type of Coronavirus (2019-nCov) epidemic spread rapidly, causing m...

Risk Stratification for Early Detection of Diabetes and Hypertension in Resource-Limited Settings: Machine Learning Analysis.

BACKGROUND: The impending scale up of noncommunicable disease screening programs in low- and middle-...

Network machine learning maps phytochemically rich "Hyperfoods" to fight COVID-19.

In this paper, we introduce a network machine learning method to identify potential bioactive anti-C...

Predicting mortality in critically ill patients with diabetes using machine learning and clinical notes.

BACKGROUND: Diabetes mellitus is a prevalent metabolic disease characterized by chronic hyperglycemi...

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