Obesity

Exploring domains, clinical implications and environmental associations of a deep learning marker of biological ageing.

Deep Neural Networks (DNN) have been recently developed for the estimation of Biological Age (BA), the hypothetical underlying age of an organism, which can differ from its chronological age (CA). Although promising, these population-specific algorithms warrant further characterization and validation, since their biological, clinical and environmental correlates remain largely unexplored. Here, an...

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 key to improving people's health quality. Middle school students' physical examinations and monitoring work are a surefire way to ensure their healthy development. Poor vision, dental caries, overweight and obesity, and high blood pressure are the most common adverse health outcomes of students cau...

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, less physical exercise, and dietary calcium defic...

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 quantification of MFI requires time-consuming and rater-de...

Human activity recognition using wearable sensors, discriminant analysis, and long short-term memory-based neural structured learning.

Healthcare using body sensor data has been getting huge research attentions by a wide range of researchers because of its good practical applications ...

Machine learning using clinical data at baseline predicts the efficacy of vedolizumab at week 22 in patients with ulcerative colitis.

Predicting the response of patients with ulcerative colitis (UC) to a biologic such as vedolizumab (VDZ) before administration is an unmet need for op...

Estimated Artificial Neural Network Modeling of Maximal Oxygen Uptake Based on Multistage 10-m Shuttle Run Test in Healthy Adults.

We aimed to develop an artificial neural network (ANN) model to estimate the maximal oxygen uptake (VOmax) based on a multistage 10 m shuttle run test...

Towards precision cardiometabolic prevention: results from a machine learning, semi-supervised clustering approach in the nationwide population-based ORISCAV-LUX 2 study.

Given the rapid increase in the incidence of cardiometabolic conditions, there is an urgent need for better approaches to prevent as many cases as pos...

Natural language processing for the assessment of cardiovascular disease comorbidities: The cardio-Canary comorbidity project.

OBJECTIVE: Accurate ascertainment of comorbidities is paramount in clinical research. While manual adjudication is labor-intensive and expensive, the ...

Robotic versus laparoscopic right hemicolectomy: a case-matched study.

The current gold standard surgical treatment for right colonic malignancy is the laparoscopic right hemicolectomy (LRH). However, laparoscopic surgery...

CAFT: a deep learning-based comprehensive abdominal fat analysis tool for large cohort studies.

BACKGROUND: There is increasing appreciation of the association of obesity beyond co-morbidities, such as cancers, Type 2 diabetes, hypertension, and ...

Editorial: The National COVID Cohort Collaborative Consortium Combines Population Data with Machine Learning to Evaluate and Predict Risk Factors for the Severity of COVID-19.

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19) commonly presents with pne...

Data-driven identification of complex disease phenotypes.

Disease interaction in multimorbid patients is relevant to treatment and prognosis, yet poorly understood. In the present work, we combine approaches ...

Virtual Reality-Based Framework to Simulate Control Algorithms for Robotic Assistance and Rehabilitation Tasks through a Standing Wheelchair.

The implementation of control algorithms oriented to robotic assistance and rehabilitation tasks for people with motor disabilities has been of increa...

Future of machine learning in paediatrics.

Machine learning (ML) is a branch of artificial intelligence (AI) that enables computers to learn without being explicitly programmed, through a combi...

PEDF, a pleiotropic WTC-LI biomarker: Machine learning biomarker identification and validation.

Biomarkers predict World Trade Center-Lung Injury (WTC-LI); however, there remains unaddressed multicollinearity in our serum cytokines, chemokines, a...

Support Vector Machine as a Supervised Learning for the Prioritization of Novel Potential SARS-CoV-2 Main Protease Inhibitors.

In the last year, the COVID-19 pandemic has highly affected the lifestyle of the world population, encouraging the scientific community towards a grea...

Real Time Multipurpose Smart Waste Classification Model for Efficient Recycling in Smart Cities Using Multilayer Convolutional Neural Network and Perceptron.

Urbanization is a big concern for both developed and developing countries in recent years. People shift themselves and their families to urban areas f...

Using Wearables and Machine Learning to Enable Personalized Lifestyle Recommendations to Improve Blood Pressure.

Blood pressure (BP) is an essential indicator for human health and is known to be greatly influenced by lifestyle factors, like activity and sleep fa...

Prophylactic effect of . seed extract on inflammatory markers and histopathological changes in high-fat-fed ovariectomized rats.

BACKGROUND AND AIM: L. seeds (TFG) are used as spices in Indian cuisine. In Indian traditional medicine, TFG is used to treat diabetes, dyslipidemia,...