Obesity

Exploring the genetic characteristics of overweight-related osteoarthritis using machine learning.

This investigation employed a synergistic approach integrating bioinformatics and machine learning methodologies to scrutinize overweight-related osteoarthritis characteristic genes (OROCGs). The research team procured gene expression profiles from osteoarthritis (OA) patients' cartilage and meniscus, derived from GEO database datasets GSE98918 and GSE117999. These profiles underwent meticulous ex...

MicroRNA signature predicts post operative atrial fibrillation after coronary artery bypass grafting.

Early detection of atrial fibrillation (AFib) is crucial for altering its natural progression and complication profile. Traditional demographic and lifestyle factors often fail as predictors of AFib. This study investigated pre-operative, circulating microRNAs (miRNAs) as potential biomarkers for post-operative AFib (POAF) in patients undergoing coronary artery bypass grafting (CABG). We used an a...

Radiomic and proteomic signatures of body mass index on brain ageing and Alzheimer's-like patterns of brain atrophy.

BACKGROUND: The impact of high body mass index (BMI) states and associated proteomic factors on brain ageing and Alzheimer's disease (AD) remains uncl...

Automated Body Composition Analysis Using DAFS Express on 2D MRI Slices at L3 Vertebral Level.

Body composition analysis is vital in assessing health conditions such as obesity, sarcopenia, and metabolic syndromes. MRI provides detailed images o...

Type 2 Diabetes in Taiwan: Unmasking Influential Factors Through Advanced Predictive Modeling.

Type 2 diabetes (T2D) is influenced by lifestyle, genetics, and environmental conditions. By utilizing machine learning techniques, we can enhance th...

Novel machine learning models for the prediction of acute respiratory distress syndrome after liver transplantation.

Early prediction of acute respiratory distress syndrome (ARDS) after liver transplantation (LT) facilitates timely intervention. We aimed to develop a...

Enhancing liver disease diagnosis with hybrid SMOTE-ENN balanced machine learning models-an empirical analysis of Indian patient liver disease datasets.

INTRODUCTION: The liver is one of the vital organs of human body that performs some of the most crucial biological processes such as protein and bioch...

Comparison of seven machine learning models in hypertension classification using photoplethysmographic and anthropometric data.

This study presents an algorithm for classifying individuals into four hypertension categories (healthy, prehypertension, Stage 1, and Stage 2) using ...

EEG Connectivity as Predictor of ICAN ADHD Children's Improvement After Completion of Theta Beta Ratio Neurofeedback: Machine Learning Analyses.

Attention deficit hyperactivity disorder is a prevalent syndrome that costs billions of dollars annually. Finding meaningful interventions based upon ...

Two birds with one stone: pre-TAVI coronary CT angiography combined with FFR helps screen for coronary stenosis.

OBJECTIVES: Since coronary artery disease (CAD) is a common comorbidity in patients with aortic valve stenosis, invasive coronary angiography (ICA) ca...

Computational Risk Stratification of Preclinical Alzheimer's in Younger Adults.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that often begins decades before clinical symptoms manifest. Early detection rem...

Continuous glucose monitoring combined with artificial intelligence: redefining the pathway for prediabetes management.

Prediabetes represents an early stage of glucose metabolism disorder with significant public health implications. Although traditional lifestyle inter...

Skeletal Muscle Density as a Predictive Marker for Pathologic Complete Response in Triple-Negative Breast Cancer Treated with Neoadjuvant Chemoimmunotherapy.

: The predictive value of muscle-related indicators in triple-negative breast cancer (TNBC) patients undergoing neoadjuvant chemotherapy (NAC) remains...

Development of a Heart Rate Variability Based Ambulatory Stress Detection Model for Clinical Populations.

Biosensor-based, real-time stress detection has generated clinical interest for the purpose of driving just-in-time interventions that support recover...

Exploring voice as a digital phenotype in adults with ADHD.

Current diagnostic procedures for attention deficit hyperactivity disorder (ADHD) are mainly subjective and prone to bias. While research on potential...

Accuracy of Using Weight and Length in Children under 24 mo to Screen for Early Childhood Obesity: A Systematic Review.

The global increase in early childhood overweight and obesity has prompted interest in early prediction of overweight and obesity to allow timely inte...

Mechanisms underlying obesity-malignancy connection: a systematic narrative review.

The association between obesity and cancer risk carries substantial public health ramifications as obesity promotes cancer advancement via many cellul...

Performance of Machine Learning Models in Predicting 30-Day General Medicine Readmissions Compared to Traditional Approaches in Australian Hospital Setting.

: Hospital readmissions are a key quality metric impacting both patient outcomes and healthcare costs. Traditional logistic regression models, includi...

Cardiovascular, Kidney, Liver, and Metabolic Interactions in Heart Failure: Breaking Down Silos.

Over the past few decades, the rising burden of metabolic disease, including type 2 diabetes, prediabetes, obesity, and metabolic dysfunction-associat...

Transcriptome combined with Mendelian randomization to identify key genes related to polyamine metabolism in childhood obesity and elucidate their molecular regulatory mechanisms.

Currently, research has found a close correlation between childhood obesity (CO) and elevated levels of polyamines in the bloodstream. Thus, the ident...