Primary Care

Obesity

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

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Role of Deep Learning in Predicting Aging-Related Diseases: A Scoping Review.

Aging refers to progressive physiological changes in a cell, an organ, or the whole body of an indiv...

Social Robots for Evaluating Attention State in Older Adults.

Sustained attention is essential for older adults to maintain an active lifestyle, and the deficienc...

Intelligent type 2 diabetes risk prediction from administrative claim data.

Type 2 diabetes is a chronic, costly disease and is a serious global population health problem. Yet,...

Predicting obesity and smoking using medication data: A machine-learning approach.

PURPOSE: Administrative health datasets are widely used in public health research but often lack inf...

Risk factor assessments of temporomandibular disorders via machine learning.

This study aimed to use artificial intelligence to determine whether biological and psychosocial fac...

Artificial neural network and decision tree models of post-stroke depression at 3 months after stroke in patients with BMI ≥ 24.

OBJECTIVE: Previous studies have shown that excess weight (including obesity and overweight) can inc...

Predicting the Risk of Hypertension Based on Several Easy-to-Collect Risk Factors: A Machine Learning Method.

Hypertension is a widespread chronic disease. Risk prediction of hypertension is an intervention tha...

Skeletal muscle myostatin gene expression and sarcopenia in overweight and obese middle-aged and older adults.

BACKGROUND: Myostatin (MSTN) is a key negative regulator of muscle mass in humans and animals, havin...

Mutations of PHOX2B Gene in Patients of Obesity Hypoventilation Syndrome in Central India.

 Paired-like homeobox 2B (PHOX2B) gene on chromosome 4p12 codes for a transcription factor having a...

Multi-Class brain normality and abnormality diagnosis using modified Faster R-CNN.

BACKGROUND AND OBJECTIVE: The detection and analysis of brain disorders through medical imaging tech...

Does adoption of new technology increase surgical volume? The robotic inguinal hernia repair model.

Robotic Inguinal Hernia repair has been associated with higher costs but shorter length of stay. Rob...

A machine learning-based biological aging prediction and its associations with healthy lifestyles: the Dongfeng-Tongji cohort.

This study aims to establish a biological age (BA) predictor and to investigate the roles of lifesty...

Contemporary Pure Laparoscopic Robot-Assisted Laparoscopic Radical Nephrectomy: Is the Transition Worth It?

The proportion of robotic procedures continues to rise. The literature reinforces that robotic proc...

Deep learning multimodal fNIRS and EEG signals for bimanual grip force decoding.

Non-invasive brain-machine interfaces (BMIs) offer an alternative, safe and accessible way to intera...

Sociodemographic risk factors of under-five stunting in Bangladesh: Assessing the role of interactions using a machine learning method.

This paper aims to demonstrate the importance of studying interactions among various sociodemographi...

Prediction Algorithm of Young Students' Physical Health Risk Factors Based on Deep Learning.

Young people's physical and mental health is the foundation of society's overall development and the...

Risk factors of osteoporosis in soldiers of the Armed Forces: A cross-sectional study from Western India.

BACKGROUND: Osteoporosis may result from risk factors such as smoking, alcohol, low body mass index,...

Multi-muscle deep learning segmentation to automate the quantification of muscle fat infiltration in cervical spine conditions.

Muscle fat infiltration (MFI) has been widely reported across cervical spine disorders. The quantifi...

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