Metabolic Syndrome

Next-visit prediction and prevention of hypertension using large-scale routine health checkup data.

This paper proposes the use of machine learning models to predict one's risk of having hypertension in the future using their routine health checkup data of their current and past visits to a health checkup center. The large-scale and high-dimensional dataset used in this study comes from MJ Health Research Foundation in Taiwan. The training data for models is separated into 5 folds and used to tr...

Artificial intelligence driven clustering of blood pressure profiles reveals frailty in orthostatic hypertension.

Gravity, an invisible but constant force , challenges the regulation of blood pressure when transitioning between postures. As physiological reserve diminishes with age, individuals grow more susceptible to such stressors over time, risking inadequate haemodynamic control observed in orthostatic hypotension. This prevalent condition is characterized by drops in blood pressure upon standing; howeve...

Grade prediction of lesions in cerebral white matter using a convolutional neural network.

We established a diagnostic method for cerebral white matter lesions using MRI images and examined the relationship between the MRI images and the med...

Enhancing type 2 diabetes mellitus prediction by integrating metabolomics and tree-based boosting approaches.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a global health problem characterized by insulin resistance and hyperglycemia. Early detection and accu...

Predictive modeling of preoperative acute heart failure in older adults with hypertension: a dual perspective of SHAP values and interaction analysis.

BACKGROUND: In older adults with hypertension, hip fractures accompanied by preoperative acute heart failure significantly elevate surgical risks and ...

Enhancing the accuracy of blood-glucose tests by upgrading FTIR with multiple-reflections, quantum cascade laser, two-dimensional correlation spectroscopy and machine learning.

The accuracy of screening diabetes from non-diabetes is drastically enhanced by strategically upgrading the bench-marking infrared spectroscopy techni...

Machine Learning-Based Prediction for Incident Hypertension Based on Regular Health Checkup Data: Derivation and Validation in 2 Independent Nationwide Cohorts in South Korea and Japan.

BACKGROUND: Worldwide, cardiovascular diseases are the primary cause of death, with hypertension as a key contributor. In 2019, cardiovascular disease...

Identification of novel hypertension biomarkers using explainable AI and metabolomics.

BACKGROUND: The global incidence of hypertension, a condition of elevated blood pressure, is rising alarmingly. According to the World Health Organiza...

Adaptive FPGA-Based Accelerators for Human-Robot Interaction in Indoor Environments.

This study addresses the challenges of human-robot interactions in real-time environments with adaptive field-programmable gate array (FPGA)-based acc...

Construction of the miRNA/Pyroptosis-Related Molecular Regulatory Axis in Abdominal Aortic Aneurysm: Evidence From Transcriptome Data Combined With Multiple Machine Learning Approaches Followed by Experiment Validation.

Abdominal aortic aneurysm (AAA) represents a permanent and localized widening of the abdominal aorta, posing a potentially lethal risk of aortic rupt...

Prediction of Incident Diabetic Retinopathy in Adults With Type 1 Diabetes Using Machine Learning Approach: An Exploratory Study.

BACKGROUND: Early detection and intervention are crucial for preventing vision-threatening diabetic retinopathy (DR) in adults with type 1 diabetes (T...

Predicting laboratory aspirin resistance in Chinese stroke patients using machine learning models by GP1BA polymorphism.

This study aims to use machine learning model to predict laboratory aspirin resistance (AR) in Chinese stroke patients by incorporating patient charac...

A Study on Prevalence and Factors Affecting Hypertension in an Iranian Population: Results from the Fasa Cohort Study.

BACKGROUND: In recent years, hypertension has been one of the most important noncommunicable diseases worldwide. In this context, identifying the pred...

Diagnostic performance of single-lead electrocardiograms for arterial hypertension diagnosis: a machine learning approach.

Awareness and early identification of hypertension is crucial in reducing the burden of cardiovascular disease (CVD). Artificial intelligence-based an...

Deep learning assists early-detection of hypertension-mediated heart change on ECG signals.

Arterial hypertension is a major risk factor for cardiovascular diseases. While cardiac ultrasound is a typical way to diagnose hypertension-mediated ...

Modeling health risks using neural network ensembles.

This study aims to demonstrate that demographics combined with biometrics can be used to predict obesity related chronic disease risk and produce a he...

Explainable Machine-Learning Models to Predict Weekly Risk of Hyperglycemia, Hypoglycemia, and Glycemic Variability in Patients With Type 1 Diabetes Based on Continuous Glucose Monitoring.

BACKGROUND AND OBJECTIVE: The aim of this study was to develop and validate explainable prediction models based on continuous glucose monitoring (CGM)...

GloGen: PPG prompts for few-shot transfer learning in blood pressure estimation.

With the rapid advancements in machine learning, its applications in the medical field have garnered increasing interest, particularly in non-invasive...

Comparison between statistical and machine learning methods to detect the hematological indices with the greatest influence on elevated serum levels of low-density lipoprotein cholesterol.

INTRODUCTION: Elevated levels of low-density lipoprotein-cholesterol (LDL-C) is a significant risk factor for the development of cardiovascular diseas...

The Bioprotective Effects of Marigold Tea Polyphenols on Obesity and Oxidative Stress Biomarkers in High-Fat-Sugar Diet-Fed Rats.

The research is aimed at exploring the potential of marigold petal tea (MPT), rich in polyphenol contents, against oxidative stress and obesity in a ...