Primary Care

Obesity

Latest AI and machine learning research in obesity for healthcare professionals.

1,198 articles
Stay Ahead - Weekly Obesity research updates
Subscribe
Browse Specialties
Showing 295-315 of 1,198 articles
Non-invasive brain-machine interface control with artificial intelligence copilots.

Motor brain-machine interfaces (BMIs) decode neural signals to help people with paralysis move and c...

Modeling health risks using neural network ensembles.

This study aims to demonstrate that demographics combined with biometrics can be used to predict obe...

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 co...

Exploring key factors influencing depressive symptoms among middle-aged and elderly adult population: A machine learning-based method.

OBJECTIVE: This paper aims to investigate the key factors, including demographics, socioeconomics, p...

Development of the machine learning model that is highly validated and easily applicable to predict radiographic knee osteoarthritis progression.

Many models using the aid of artificial intelligence have been recently proposed to predict the prog...

Enhancing severe hypoglycemia prediction in type 2 diabetes mellitus through multi-view co-training machine learning model for imbalanced dataset.

Patients with type 2 diabetes mellitus (T2DM) who have severe hypoglycemia (SH) poses a considerable...

Visualization obesity risk prediction system based on machine learning.

Obesity is closely associated with various chronic diseases.Therefore, accurate, reliable and cost-e...

Explainable biology for improved therapies in precision medicine: AI is not enough.

Technological advances and high-throughput bio-chemical assays are rapidly changing ways how we form...

The revolution in high-throughput proteomics and AI.

The recent capability to measure thousands of plasma proteins from a tiny blood sample has provided ...

Applying machine learning approaches for predicting obesity risk using US health administrative claims database.

INTRODUCTION: Body mass index (BMI) is inadequately recorded in US administrative claims databases. ...

Prediction of Fatty Acid Intake from Serum Fatty Acid Levels Using Machine Learning Technique in Women Living in Toyama Prefecture.

Preventing lifestyle-related diseases requires understanding and managing the intake of total fats a...

Effect of Deep Learning Image Reconstruction on Image Quality and Pericoronary Fat Attenuation Index.

To compare the image quality and fat attenuation index (FAI) of coronary artery CT angiography (CCTA...

Unsupervised Machine Learning to Identify Risk Factors of Pyeloplasty Failure in Ureteropelvic Junction Obstruction.

In adult patients with ureteropelvic junction obstruction (UPJO), little data exist on predicting p...

Prediction of individual weight loss using supervised learning: findings from the CALERIE 2 study.

BACKGROUND: Predicting individual weight loss (WL) responses to lifestyle interventions is challengi...

Comorbidity-based framework for Alzheimer's disease classification using graph neural networks.

Alzheimer's disease (AD), the most prevalent form of dementia, requires early prediction for timely ...

Digital therapeutics in hypertension: How to make sustainable lifestyle changes.

Various digital therapeutic products have been validated and approved since 2017. They have demonstr...

Mesocorticolimbic and Cardiometabolic Diseases-Two Faces of the Same Coin?

The risk behaviors underlying the most prevalent chronic noncommunicable diseases (NCDs) encompass a...

Metabolic syndrome predictive modelling in Bangladesh applying machine learning approach.

Metabolic syndrome (MetS) is a cluster of interconnected metabolic risk factors, including abdominal...

Deep Learning-Based Obesity Identification System for Young Adults Using Smartphone Inertial Measurements.

Obesity recognition in adolescents is a growing concern. This study presents a deep learning-based o...

Browse Specialties