Obesity

What's new in IBD therapy: An "omics network" approach.

The industrial revolution that began in the late 1800s has resulted in dramatic changes in the environment, human lifestyle, dietary habits, social structure, and so on. Almost certainly because this rapid evolution has outpaced the ability of the body to adapt to a number of environmental and behavioral changes, there has been a parallel emergence of several chronic inflammatory diseases, among w...

Identification of Risk Factors Associated with Obesity and Overweight-A Machine Learning Overview.

Social determining factors such as the adverse influence of globalization, supermarket growth, fast unplanned urbanization, sedentary lifestyle, economy, and social position slowly develop behavioral risk factors in humans. Behavioral risk factors such as unhealthy habits, improper diet, and physical inactivity lead to physiological risks, and "obesity/overweight" is one of the consequences. "Obes...

Measurement and identification of mental workload during simulated computer tasks with multimodal methods and machine learning.

This study attempted to multimodally measure mental workload and validate indicators for estimating mental workload. A simulated computer work compose...

Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea.

Herein, we aim to assess mortality risk prediction in peritoneal dialysis patients using machine-learning algorithms for proper prognosis prediction. ...

Improving an Intelligent Detection System for Coronary Heart Disease Using a Two-Tier Classifier Ensemble.

Coronary heart disease (CHD) is one of the severe health issues and is one of the most common types of heart diseases. It is the most frequent cause o...

Current Developments in Digital Quantitative Volume Estimation for the Optimisation of Dietary Assessment.

Obesity is a global health problem with wide-reaching economic and social implications. Nutrition surveillance systems are essential to understanding ...

Artificial Intelligence: The Future for Diabetes Care.

Artificial intelligence (AI) is a fast-growing field and its applications to diabetes, a global pandemic, can reform the approach to diagnosis and man...

Contemporary Rates and Predictors of Open Conversion During Minimally Invasive Radical Prostatectomy for Nonmetastatic Prostate Cancer.

To test contemporary rates and predictors of open conversion at minimally invasive (laparoscopic or robotic) radical prostatectomy (MIRP). Within th...

Deep Learning Predicts Total Knee Replacement from Magnetic Resonance Images.

Knee Osteoarthritis (OA) is a common musculoskeletal disorder in the United States. When diagnosed at early stages, lifestyle interventions such as ex...

Deep Learning to Unveil Correlations between Urban Landscape and Population Health.

The global healthcare landscape is continuously changing throughout the world as technology advances, leading to a gradual change in lifestyle. Severa...

Detection of hip osteoarthritis by using plain pelvic radiographs with deep learning methods.

OBJECTIVE: The incidence of osteoarthritis is gradually increasing in public due to aging and increase in obesity. Various imaging methods are used in...

Robot-Assisted Radical Prostatectomy Associated with Decreased Persistent Postoperative Opioid Use.

Minimally invasive surgery offers reduced pain and opioid use postoperatively compared with open surgery, but large-scale comparative studies are lac...

Food Liking-Based Diet Quality Indexes (DQI) Generated by Conceptual and Machine Learning Explained Variability in Cardiometabolic Risk Factors in Young Adults.

The overall pattern of a diet (diet quality) is recognized as more important to health and chronic disease risk than single foods or food groups. Inde...

SAEROF: an ensemble approach for large-scale drug-disease association prediction by incorporating rotation forest and sparse autoencoder deep neural network.

Drug-disease association is an important piece of information which participates in all stages of drug repositioning. Although the number of drug-dise...

High-throughput quantitative histology in systemic sclerosis skin disease using computer vision.

BACKGROUND: Skin fibrosis is the clinical hallmark of systemic sclerosis (SSc), where collagen deposition and remodeling of the dermis occur over time...

Stroke Prediction with Machine Learning Methods among Older Chinese.

Timely stroke diagnosis and intervention are necessary considering its high prevalence. Previous studies have mainly focused on stroke prediction with...

Retrospective Cohort Analysis from a High-Volume Center of Prognostic Factors Affecting Biochemical Relapse in Patients with Encapsulated, Margin-Negative, Isolated Seminal Vesicle Invasion After Robot-Assisted Laparoscopic Prostatectomy: A Novel Study.

Specimen pathology findings collectively impact the long-term outcomes of robot-assisted laparoscopic prostatectomy. Since seminal vesicle invasion (...

Data-driven translational prostate cancer research: from biomarker discovery to clinical decision.

Prostate cancer (PCa) is a common malignant tumor with increasing incidence and high heterogeneity among males worldwide. In the era of big data and a...

CHD Risk Minimization through Lifestyle Control: Machine Learning Gateway.

Studies on the influence of a modern lifestyle in abetting Coronary Heart Diseases (CHD) have mostly focused on deterrent health factors, like smoking...

Machine learning-based motor assessment of Parkinson's disease using postural sway, gait and lifestyle features on crowdsourced smartphone data.

OBJECTIVES: Remote assessment of gait in patients' homes has become a valuable tool for monitoring the progression of Parkinson's disease (PD). Howeve...