Cardiovascular

Metabolic Syndrome

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

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Future possibilities for artificial intelligence in the practical management of hypertension.

The use of artificial intelligence in numerous prediction and classification tasks, including clinic...

A Machine Learning Approach for Predicting Early Phase Postoperative Hypertension in Patients Undergoing Carotid Endarterectomy.

BACKGROUND: This study aimed to establish and validate a machine learning-based model for the predic...

Fatal case of hospital-acquired hypernatraemia in a neonate: lessons learned from a tragic error.

A 3-week-old boy with viral gastroenteritis was by error given 200 mL 1 mmol/mL hypertonic saline in...

An artificial neural network approach for predicting hypertension using NHANES data.

This paper focus on a neural network classification model to estimate the association among gender, ...

Near-optimal insulin treatment for diabetes patients: A machine learning approach.

Blood glycemic control is crucial for minimizing severe side effects in diabetes mellitus. Currently...

Continuous blood pressure measurement from one-channel electrocardiogram signal using deep-learning techniques.

Continuous blood pressure (BP) measurement is crucial for reliable and timely hypertension detection...

Improving blood glucose level predictability using machine learning.

This study was designed to improve blood glucose level predictability and future hypoglycemic and hy...

Accelerating massively parallel hemodynamic models of coarctation of the aorta using neural networks.

Comorbidities such as anemia or hypertension and physiological factors related to exertion can influ...

Leisure time physical activity is associated with improved HDL functionality in high cardiovascular risk individuals: a cohort study.

AIMS: Physical activity has consistently been shown to improve cardiovascular health and high-densit...

Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques.

Hypertension is a potentially unsafe health ailment, which can be indicated directly from the blood ...

A size-invariant convolutional network with dense connectivity applied to retinal vessel segmentation measured by a unique index.

BACKGROUND AND OBJECTIVES: Retinal vessel segmentation (RVS) helps in diagnosing diseases such as hy...

Identification of Risk Factors Associated with Obesity and Overweight-A Machine Learning Overview.

Social determining factors such as the adverse influence of globalization, supermarket growth, fast ...

Artificial intelligence for early prediction of pulmonary hypertension using electrocardiography.

BACKGROUND: Screening and early diagnosis of pulmonary hypertension (PH) are critical for managing p...

Predicting Optimal Hypertension Treatment Pathways Using Recurrent Neural Networks.

BACKGROUND: In ambulatory care settings, physicians largely rely on clinical guidelines and guidelin...

Value of a Machine Learning Approach for Predicting Clinical Outcomes in Young Patients With Hypertension.

Risk stratification of young patients with hypertension remains challenging. Generally, machine lear...

Stroke Prediction with Machine Learning Methods among Older Chinese.

Timely stroke diagnosis and intervention are necessary considering its high prevalence. Previous stu...

Exploring the effect of hypertension on retinal microvasculature using deep learning on East Asian population.

Hypertension is the leading risk factor of cardiovascular disease and has profound effects on both t...

A proposed health monitoring system using fuzzy inference system.

Due to the busy schedule of every human being in today's world, consciousness towards one's health h...

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