Exercise & Fitness

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 deficiency. The risk of osteoporosis fractures can be reduced with lifestyle changes, which include diet, exercise, and preventing falls. The present study is an effort to measure the burden of risk factors of osteoporosis in adult male soldiers in the Ar...

Personalized Exercise Programs Based upon Remote Assessment of Motor Fitness: A Pilot Study among Healthy People Aged 65 Years and Older.

BACKGROUND: The World Health Organization has recently updated exercise guidelines for people aged >65 years, emphasizing the inclusion of multiple fitness components. However, without adequate recognition of individual differences, these guidelines may be applied using an approach that "one-size-fits-all." Within the shifting paradigm toward an increasingly personalized approach to medicine and h...

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...

Feature selection for unsupervised machine learning of accelerometer data physical activity clusters - A systematic review.

BACKGROUND: Identifying clusters of physical activity (PA) from accelerometer data is important to identify levels of sedentary behaviour and physical...

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...

LPWAN and Embedded Machine Learning as Enablers for the Next Generation of Wearable Devices.

The penetration of wearable devices in our daily lives is unstoppable. Although they are very popular, so far, these elements provide a limited range ...

A robot goes to rehab: a novel gamified system for long-term stroke rehabilitation using a socially assistive robot-methodology and usability testing.

BACKGROUND: Socially assistive robots (SARs) have been proposed as a tool to help individuals who have had a stroke to perform their exercise during t...

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...

Learning Carbohydrate Digestion and Insulin Absorption Curves Using Blood Glucose Level Prediction and Deep Learning Models.

Type 1 diabetes is a chronic disease caused by the inability of the pancreas to produce insulin. Patients suffering type 1 diabetes depend on the appr...

Analysis of Body Behavior Characteristics after Sports Training Based on Convolution Neural Network.

The use of artificial intelligence technology to analyze human behavior is one of the key research topics in the world. In order to detect and analyze...

Evaluation of Mechanical Properties of Materials Based on Genetic Algorithm Optimizing BP Neural Network.

In the 21 century, with the increasingly urgent requirements for lightweight in the fields of aviation, aerospace, and electronics, especially automob...

Artificial Intelligence and COVID-19: A Systematic umbrella review and roads ahead.

Artificial Intelligence (AI) has played a substantial role in the response to the challenges posed by the current pandemic. The growing interest in us...

PyPEF-An Integrated Framework for Data-Driven Protein Engineering.

Data-driven strategies are gaining increased attention in protein engineering due to recent advances in access to large experimental databanks of prot...

Machine Learning to Identify Metabolic Subtypes of Obesity: A Multi-Center Study.

BACKGROUND AND OBJECTIVE: Clinical characteristics of obesity are heterogenous, but current classification for diagnosis is simply based on BMI or met...

Design and Implementation of Human Motion Recognition Information Processing System Based on LSTM Recurrent Neural Network Algorithm.

With the comprehensive development of national fitness, men, women, young, and old in China have joined the ranks of fitness. In order to increase the...

Targeted muscle effort distribution with exercise robots: Trajectory and resistance effects.

The objective of this work is to relate muscle effort distributions to the trajectory and resistance settings of a robotic exercise and rehabilitation...