Obesity

Performance Analysis of Boosting Classifiers in Recognizing Activities of Daily Living.

Physical activity is essential for physical and mental health, and its absence is highly associated ...

Modelling prognostic trajectories of cognitive decline due to Alzheimer's disease.

Alzheimer's disease (AD) is characterised by a dynamic process of neurocognitive changes from normal...

Crowd of Oz: A Crowd-Powered Social Robotics System for Stress Management.

Coping with stress is crucial for a healthy lifestyle. In the past, a great deal of research has bee...

Expression of Cytokines and Chemokines as Predictors of Stroke Outcomes in Acute Ischemic Stroke.

Ischemic stroke remains one of the most debilitating diseases and is the fifth leading cause of dea...

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment.

Mild cognitive impairment (MCI) is the first sign of dementia among elderly populations and its earl...

Machine learning as new promising technique for selection of significant features in obese women with type 2 diabetes.

Background The global trend of obesity and diabetes is considerable. Recently, the early diagnosis a...

Insulin Resistance Associated with Plasma Xanthine Oxidoreductase Activity Independent of Visceral Adiposity and Adiponectin Level: MedCity21 Health Examination Registry.

BACKGROUND: Higher levels of uric acid production have been reported in individuals with visceral fa...

Unsupervised machine learning for the discovery of latent disease clusters and patient subgroups using electronic health records.

Machine learning has become ubiquitous and a key technology on mining electronic health records (EHR...

Adipocyte Fatty Acid-Binding Protein 4 is Altered in Growth Discordant Dichorionic, but not in Monochorionic Twins.

CONTEXT: The fetal period has a critical and long-lasting impact on the regulation of metabolic proc...

Predicting cognitive behavioral therapy outcome in the outpatient sector based on clinical routine data: A machine learning approach.

The availability of large-scale datasets and sophisticated machine learning tools enables developing...

Analysis of disease comorbidity patterns in a large-scale China population.

BACKGROUND: Disease comorbidity is popular and has significant indications for disease progress and ...

Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test.

Diabetes is a large healthcare burden worldwide. There is substantial evidence that lifestyle modifi...

Using machine learning models to improve stroke risk level classification methods of China national stroke screening.

BACKGROUND: With the character of high incidence, high prevalence and high mortality, stroke has bro...

A Bayesian Shared Control Approach for Wheelchair Robot With Brain Machine Interface.

To enhance the performance of the brain-actuated robot system, a novel shared controller based on Ba...

Comparison of Walking Protocols and Gait Assessment Systems for Machine Learning-Based Classification of Parkinson's Disease.

Early diagnosis of Parkinson's diseases (PD) is challenging; applying machine learning (ML) models t...

Deep Learning Neural Encoders for Motor Cortex.

Intracortical brain-machine interfaces (BMIs) transform neural activity into control signals to driv...

Different spexin level in obese vs normal weight children and its relationship with obesity related risk factors.

BACKGROUND AND AIMS: Spexin (SPX) is a novel peptide recently discovered as an important regulatory ...

: The Impact of Obesity in Patients Undergoing Robotic Partial Nephrectomy by Rosen et al. (J Endourol 2019;33(6):431-437; DOI: 10.1089/end.2019.0018).

Optimized artificial neural network based performance analysis of wheelchair movement for ALS patients.

Individuals with neurodegenerative attacks loose the entire motor neuron movements. These conditions...

Profiling movement behaviours in pre-school children: A self-organised map approach.

Application of machine learning techniques has the potential to yield unseen insights into movement ...

Statistical and machine learning methodology for abdominal aortic aneurysm prediction from ultrasound screenings.

A method of analysis of a database of patients (n = 10 329) screened for an abdominal aortic aneurys...