Prevention

Adolescent relational behaviour and the obesity pandemic: A descriptive study applying social network analysis and machine learning techniques.

AIM: To study the existence of subgroups by exploring the similarities between the attributes of the nodes of the groups, in relation to diet and gender and, to analyse the connectivity between groups based on aspects of similarities between them through SNA and artificial intelligence techniques.

-derived postbiotics inhibited digestion of triglycerides, glycerol phospholipids and sterol lipids allosteric regulation of BSSL, PTL and PLA2 to prevent obesity: perspectives on deep learning integrated multi-omics.

The anti-obesity potential of probiotics has been widely reported, however their utilization in high-risk patients and potential adverse reactions have led researchers to focus their attention on postbiotics. Herein, pseudo-targeted lipidomics linked with deep learning-based metabolomics was utilized to dynamically characterize the postbiotic potential of heat-inactivated JCM1134 supplementation ...

Enhancing corn stalk-based anaerobic digestion with different types of zero-valent iron added during the acidification stage: Performance and mechanism.

Anaerobic digestion has been defined as a competitive approach to facilitate the recycling of corn stalks. However, few studies have focused on the ro...

Therapy-based expert system on function and postural stability after anterior cruciate ligament reconstruction: a pilot study.

PURPOSE: Wii Fit exergames have been less commonly used for the rehabilitation of athletes after Anterior Cruciate Ligament Reconstruction (ACLR). Thi...

Artificial intelligence & clinical nutrition: What the future might have in store.

Artificial Intelligence (AI) is a rapidly emerging technology in healthcare that has the potential to revolutionise clinical nutrition. AI can assist ...

FiMec tremor stabilization spoon: design and active stabilization control of two DoF robotic eating devices for hand tremor patients.

This article is about vibration-damping robotic eating devices designed for use by people who have difficulty in eating due to hand tremors due to neu...

Human Activity Prediction Based on Forecasted IMU Activity Signals by Sequence-to-Sequence Deep Neural Networks.

Human Activity Recognition (HAR) has gained significant attention due to its broad range of applications, such as healthcare, industrial work safety, ...

Deep learning model to predict exercise stress test results: Optimizing the diagnostic test selection strategy and reduce wastage in suspected coronary artery disease patients.

BACKGROUND: Cardiac exercise stress testing (EST) offers a non-invasive way in the management of patients with suspected coronary artery disease (CAD)...

Home-based upper limb stroke rehabilitation mechatronics: challenges and opportunities.

Interest in home-based stroke rehabilitation mechatronics, which includes both robots and sensor mechanisms, has increased over the past 12 years. The...

Identification and Classification of Human Body Exercises on Smart Textile Bands by Combining Decision Tree and Convolutional Neural Networks.

In recent years, human activity recognition (HAR) has gained significant interest from researchers in the sports and fitness industries. In this study...

Propensity matched analysis of robotic and laparoscopic operations for mid-low rectal cancer: short-term comparison of anal function and oncological outcomes.

Laparoscopic surgery for rectal cancer, while in some respects equivalent or even preferable to open surgery, is challenged in specific conditions whe...

Integrating Artificial Intelligence and Wearable IoT System in Long-Term Care Environments.

With the rapid advancement of information and communication technology (ICT), big data, and artificial intelligence (AI), intelligent healthcare syste...

Could chatbots help devise the next pandemic virus?

An MIT class exercise suggests AI tools can be used to order a bioweapon, but some are skeptical.

Barriers and facilitators to physical activity and further digital exercise intervention among inactive British adolescents in secondary schools: a qualitative study with physical education teachers.

BACKGROUND: Previous studies indicated that physical education programs in schools were unsuccessful to ameliorate physical activity (PA) behaviors am...

CNN-LSTM Model for Recognizing Video-Recorded Actions Performed in a Traditional Chinese Exercise.

Identifying human actions from video data is an important problem in the fields of intelligent rehabilitation assessment. Motion feature extraction an...

Intentional enterotomies: validation of a novel robotic surgery training exercise.

While laparoscopic simulation-based training is a well-established component of general surgery training, no such requirement or standardized curricul...

Determination of optimum intensity and duration of exercise based on the immune system response using a machine-learning model.

One of the important concerns in the field of exercise immunology is determining the appropriate intensity and duration of exercise to prevent suppres...

The Role of Artificial Intelligence in Deciphering Diet-Disease Relationships: Case Studies.

Modernization of society from a rural, hunter-gatherer setting into an urban and industrial habitat, with the associated dietary changes, has led to a...

Prediction of oxygen uptake kinetics during heavy-intensity cycling exercise by machine learning analysis.

Nonintrusive estimation of oxygen uptake (V̇o) is possible with wearable sensor technology and artificial intelligence. V̇o kinetics have been accurat...

Perioperative comparison between robot-assisted and laparoscopic radical cystectomy: An update meta-analysis.

We conducted this study to explore the efficacy and safety of laparoscopic radical cystectomy (LRC) and robot-assisted radical cystectomy (RARC) for b...