Primary Care

Obesity

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

1,202 articles
Stay Ahead - Weekly Obesity research updates
Subscribe
Browse Specialties
Showing 694-714 of 1,202 articles
The effect of diabetes on major robotic hepatectomy.

Studies regarding the influence of diabetes on perioperative outcomes after major hepatectomy are co...

Should Peritoneal Re-Approximation Be Performed After Transperitoneal Robot-Assisted Radical Prostatectomy?

The aim of the study is to examine the effect of peritoneal re-approximation or non-approximation o...

Prediction of newborn's body mass index using nationwide multicenter ultrasound data: a machine-learning study.

BACKGROUND: This study introduced machine learning approaches to predict newborn's body mass index (...

3D microscopy and deep learning reveal the heterogeneity of crown-like structure microenvironments in intact adipose tissue.

Crown-like structures (CLSs) are adipose microenvironments of macrophages engulfing adipocytes. Thei...

Association Between Coffee Intake and Incident Heart Failure Risk: A Machine Learning Analysis of the FHS, the ARIC Study, and the CHS.

BACKGROUND: Coronary heart disease, heart failure (HF), and stroke are complex diseases with multipl...

Assessing Dry Weight of Hemodialysis Patients via Sparse Laplacian Regularized RVFL Neural Network with L-Norm.

Dry weight is the normal weight of hemodialysis patients after hemodialysis. If the amount of water ...

Risk factors analysis of COVID-19 patients with ARDS and prediction based on machine learning.

COVID-19 is a newly emerging infectious disease, which is generally susceptible to human beings and ...

Supervised mutational signatures for obesity and other tissue-specific etiological factors in cancer.

Determining the etiologic basis of the mutations that are responsible for cancer is one of the funda...

Deep CHORES: Estimating Hallmark Measures of Physical Activity Using Deep Learning.

Wrist accelerometers for assessing hallmark measures of physical activity (PA) are rapidly growing w...

Ranking of a wide multidomain set of predictor variables of children obesity by machine learning variable importance techniques.

The increased prevalence of childhood obesity is expected to translate in the near future into a con...

Asthma-prone areas modeling using a machine learning model.

Nowadays, owing to population growth, increasing environmental pollution, and lifestyle changes, the...

A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence.

COVID-19 has infected 77.4 million people worldwide and has caused 1.7 million fatalities as of Dece...

Body Mass Index Variable Interpolation to Expand the Utility of Real-world Administrative Healthcare Claims Database Analyses.

INTRODUCTION: Administrative claims data provide an important source for real-world evidence (RWE) g...

Screening of sleep apnea based on heart rate variability and long short-term memory.

PURPOSE: Sleep apnea syndrome (SAS) is a prevalent sleep disorder in which apnea and hypopnea occur ...

An artificial intelligence-derived tool proposal to ease disordered eating screening in people with obesity.

PURPOSE: In people with obesity, food addiction (FA) tends to be associated with poorer outcomes. It...

Validation of the Khorana Score for Prediction of Venous Thromboembolism After Robot-Assisted Radical Cystectomy.

The Khorana score (KS) is used to predict the risk of venous thromboembolism (VTE) for cancer patie...

Laparoscopic cryoablation for small renal masses: Oncological outcomes at 5-year follow-up.

: To evaluate the oncological outcome at 5-year follow-up after laparoscopic cryoablation (LCA) for ...

Assessing the signal quality of electrocardiograms from varied acquisition sources: A generic machine learning pipeline for model generation.

BACKGROUND AND OBJECTIVE: Long-term electrocardiogram monitoring comes at the expense of signal qual...

The Utility of Artificial Neural Networks for the Non-Invasive Prediction of Metabolic Syndrome Based on Personal Characteristics.

This study investigated the diagnostic accuracy of using an artificial neural network (ANN) for the ...

Browse Specialties