Obesity

Prediction and Experimental Confirmation of Novel Peripheral Cannabinoid-1 Receptor Antagonists.

Small molecules targeting peripheral CB1 receptors have therapeutic potential in a variety of disorders including obesity-related, hormonal, and metabolic abnormalities, while avoiding the psychoactive effects in the central nervous system. We applied our in-house algorithm, iterative stochastic elimination, to produce a ligand-based model that distinguishes between CB1R antagonists and random mol...

Machine Learning to Understand the Immune-Inflammatory Pathways in Fibromyalgia.

Fibromyalgia (FM) is a chronic syndrome characterized by widespread musculoskeletal pain, and physical and emotional symptoms. Although its pathophysiology is largely unknown, immune-inflammatory pathways may be involved. We examined serum interleukin (IL)-6, high sensitivity C-reactive protein (hs-CRP), CXCL-8, and IL-10 in 67 female FM patients and 35 healthy women while adjusting for age, body ...

Predicting Drug-Disease Associations via Using Gaussian Interaction Profile and Kernel-Based Autoencoder.

Computational drug repositioning, designed to identify new indications for existing drugs, significantly reduced the cost and time involved in drug de...

Strategies to Tackle the Global Burden of Diabetic Retinopathy: From Epidemiology to Artificial Intelligence.

Diabetes is a global public health disease projected to affect 642 million adults by 2040, with about 75% residing in low- and middle-income countries...

Automatic extraction and assessment of lifestyle exposures for Alzheimer's disease using natural language processing.

INTRODUCTION: Previous biomedical studies identified many lifestyle exposures that could possibly represent risk factors for dementia in general or de...

Construct validation of machine learning in the prediction of short-term postoperative complications following total shoulder arthroplasty.

BACKGROUND: We aimed to demonstrate that supervised machine learning (ML) models can better predict postoperative complications after total shoulder a...

Phenotyping Women Based on Dietary Macronutrients, Physical Activity, and Body Weight Using Machine Learning Tools.

Nutritional phenotyping can help achieve personalized nutrition, and machine learning tools may offer novel means to achieve phenotyping. The primary ...

Disability in multiple sclerosis is associated with age and inflammatory, metabolic and oxidative/nitrosative stress biomarkers: results of multivariate and machine learning procedures.

The aim of this study was to evaluate the immune-inflammatory, metabolic, and nitro-oxidative stress (IM&NO) biomarkers as predictors of disability in...

Demographic, psychological, behavioral, and cognitive correlates of BMI in youth: Findings from the Adolescent Brain Cognitive Development (ABCD) study.

BACKGROUND: Previous research has implicated demographic, psychological, behavioral, and cognitive variables in the onset and maintenance of pediatric...

Wearable IoT Smart-Log Patch: An Edge Computing-Based Bayesian Deep Learning Network System for Multi Access Physical Monitoring System.

According to the survey on various health centres, smart log-based multi access physical monitoring system determines the health conditions of humans ...

HyperFoods: Machine intelligent mapping of cancer-beating molecules in foods.

Recent data indicate that up-to 30-40% of cancers can be prevented by dietary and lifestyle measures alone. Herein, we introduce a unique network-base...

Healthcare uses of artificial intelligence: Challenges and opportunities for growth.

Forms of Artificial Intelligence (AI), like deep learning algorithms and neural networks, are being intensely explored for novel healthcare applicatio...

Identifying pre-disease signals before metabolic syndrome in mice by dynamical network biomarkers.

The establishment of new therapeutic strategies for metabolic syndrome is urgently needed because metabolic syndrome, which is characterized by severa...

Time to Move On: The Impending Need for a New Disease-specific Comorbidity Index for Bladder Cancer Patients Undergoing Robot-assisted Radical Cystectomy.

The Charlson comorbidity index is an outdated comorbidity assessment tool which is not disease specific and is not applicable to contemporary BCa pati...

Promising Artificial Intelligence-Machine Learning-Deep Learning Algorithms in Ophthalmology.

The lifestyle of modern society has changed significantly with the emergence of artificial intelligence (AI), machine learning (ML), and deep learning...

Quantitative CMR population imaging on 20,000 subjects of the UK Biobank imaging study: LV/RV quantification pipeline and its evaluation.

Population imaging studies generate data for developing and implementing personalised health strategies to prevent, or more effectively treat disease....

Predicting nationwide obesity from food sales using machine learning.

The obesity epidemic progresses everywhere across the globe, and implementing frequent nationwide surveys to measure the percentage of obese populatio...

Effects of obesity on breast size, thoracic spine structure and function, upper torso musculoskeletal pain and physical activity in women.

PURPOSE: This study investigated the effects of obesity on breast size, thoracic spine structure and function, upper torso musculoskeletal pain and ph...

Directional Relationship Between Vitamin D Status and Prediabetes: A New Approach from Artificial Neural Network in a Cohort of Workers with Overweight-Obesity.

Despite the increasing literature on the association of diabetes with inflammation, cardiovascular risk, and vitamin D (25(OH)D) concentrations, stro...

Predicting childhood obesity using electronic health records and publicly available data.

BACKGROUND: Because of the strong link between childhood obesity and adulthood obesity comorbidities, and the difficulty in decreasing body mass index...