Cardiovascular

Metabolic Syndrome

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

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Peripheral blood immune landscape and NXPE3 as a novel biomarker for hypertensive intracerebral hemorrhage risk prediction and targeted therapy.

We employed bulk RNA-seq and scRNA-seq techniques to analyze the immune dysregulation in patients wi...

Development of an explainable prediction model for portal vein system thrombosis post-splenectomy in patients with cirrhosis.

BACKGROUND: Portal vein system thrombosis (PVST) is a common and potentially life-threatening compli...

Gender Differences in Predicting Metabolic Syndrome Among Hospital Employees Using Machine Learning Models: A Population-Based Study.

BACKGROUND: Metabolic syndrome (MetS) is a complex condition that captures several markers of dysreg...

Machine learning combined with infrared spectroscopy for detection of hypertension pregnancy: towards newborn and pregnant blood analysis.

Biochemical changes in the cervix during labor are not well understood. This gap in knowledge is sig...

Predicting Risk for Patent Ductus Arteriosus in the Neonate: A Machine Learning Analysis.

: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mor...

Microscope-Assisted Hypertensive Retinopathy Diagnosis Using Deep Learning Models.

The retina is the most crucial part of the human eye, and it can be affected due to hypertension. Ho...

Which approach better predicts diabetes: Traditional econometric methods or machine learning? Evidence from a cross-sectional study in South Korea.

To prevent chronic disease from getting worse, it is important to detect and predict it at an early ...

Predicting intra-abdominal hypertension using anthropometric measurements and machine learning.

Almost one in four critically ill patients suffer from intra-abdominal hypertension (IAH). Currently...

Machine learning reveals distinct neuroanatomical signatures of cardiovascular and metabolic diseases in cognitively unimpaired individuals.

Comorbid cardiovascular and metabolic risk factors (CVM) differentially impact brain structure and i...

Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management.

Hypertension presents the largest modifiable public health challenge due to its high prevalence, its...

Tlalpan 2020 Case Study: Enhancing Uric Acid Level Prediction with Machine Learning Regression and Cross-Feature Selection.

Uric acid is a key metabolic byproduct of purine degradation and plays a dual role in human health....

Establishment and validation of a ResNet-based radiomics model for predicting prognosis in cervical spinal cord injury patients.

Cervical spinal cord injury (cSCI) poses a significant challenge due to the unpredictable nature of ...

Prediction of Hypertension in the Pediatric Population Using Machine Learning and Transfer Learning: A Multicentric Analysis of the SAYCARE Study.

OBJECTIVE: To develop a machine learning (ML) model utilizing transfer learning (TL) techniques to p...

Early prediction of cardiovascular events following treatments in female breast cancer patients: Application of real-world data and artificial intelligence.

• Application of real-world data and artificial intelligence in detecting cardiotoxicity following c...

Intelligent risk stratification of hypertension based on ambulatory blood pressure monitoring and machine learning algorithms.

. Risk stratification of hypertension plays a crucial role in the treatment decisions and medication...

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