Prevention

The artificial intelligence revolution...in unethical publishing: Will AI worsen our dysfunctional publishing system?

Scholarly publishing has been shaped by the pressure of a liquid economy to become an exercise in branding more than a vehicle for the advancement of science. The current revolution in artificial intelligence (AI) is poised to make matters worse. The new generation of large language models (LLMs) have shown impressive capabilities in text generation and are already being used to write papers, gran...

Enhancing dietary analysis: Using machine learning for food caloric and health risk assessment.

In the wake of growing concerns regarding diet-related health issues, this study investigates the application of machine learning methods to estimate the energy content and classify the health risks of foods based on the USDA National Nutrient Database. The caloric content of foods was estimated using the nutritional composition (i.e., carbohydrates, protein, total lipid, and total sugar content) ...

The Bioprotective Effects of Marigold Tea Polyphenols on Obesity and Oxidative Stress Biomarkers in High-Fat-Sugar Diet-Fed Rats.

The research is aimed at exploring the potential of marigold petal tea (MPT), rich in polyphenol contents, against oxidative stress and obesity in a ...

Estimating intra- and inter-subject oxygen consumption in outdoor human gait using multiple neural network approaches.

Oxygen consumption ([Formula: see text]) is an important measure for exercise test, such as walking and running, that can be measured outdoors using p...

Maternal dietary practices during pregnancy and obesity of neonates: a machine learning approach towards hierarchical and nested relationships in a Tibet Plateau cohort study.

Studies on obesity and risk factors from a life-course perspective among residents in the Tibet Plateau with recent economic growth and increasing obe...

Effect and optimal exercise prescription of robot-assisted gait training on lower extremity motor function in stroke patients: a network meta-analysis.

OBJECTIVE: This study aimed to evaluate the effectiveness of robot-assisted gait training (RAGT) and explore the optimal exercise prescription using a...

Development and validation of machine-learning models of diet management for hyperphenylalaninemia: a multicenter retrospective study.

BACKGROUND: Assessing dietary phenylalanine (Phe) tolerance is crucial for managing hyperphenylalaninemia (HPA) in children. However, traditionally, a...

Suitability of different machine learning algorithms for the classification of the proportion of grassland-based forages at the herd level using mid-infrared spectral information from routine milk control.

As the call for an international standard for milk from grassland-based production systems continues to grow, so too do the monitoring and evaluation ...

The role of artificial intelligence in the development of anticancer therapeutics from natural polyphenols: Current advances and future prospects.

Natural polyphenols, abundant in the human diet, are derived from a wide variety of sources. Numerous preclinical studies have demonstrated their sign...

Artificial neural network inference analysis identified novel genes and gene interactions associated with skeletal muscle aging.

BACKGROUND: Sarcopenia is an age-related muscle disease that increases the risk of falls, disabilities, and death. It is associated with increased mus...

Unveiling the potential of machine learning approaches in predicting the emergence of stroke at its onset: a predicting framework.

A stroke is a dangerous, life-threatening disease that mostly affects people over 65, but an unhealthy diet is also contributing to the development of...

From data to decision: Machine learning determination of aerobic and anaerobic thresholds in athletes.

Lactate analysis plays an important role in sports science and training decisions for optimising performance, endurance, and overall success in sports...

Machine learning-powered wearable interface for distinguishable and predictable sweat sensing.

The constrained resources on wearable devices pose a challenge in meeting the demands for comprehensive sensing information, and current wearable non-...

Evaluation of online chat-based artificial intelligence responses about inflammatory bowel disease and diet: correspondence.

Therapeutic Exercise Recognition Using a Single UWB Radar with AI-Driven Feature Fusion and ML Techniques in a Real Environment.

Physiotherapy plays a crucial role in the rehabilitation of damaged or defective organs due to injuries or illnesses, often requiring long-term superv...

Artificial intelligence-based data extraction for next generation risk assessment: Is fine-tuning of a large language model worth the effort?

To underpin scientific evaluations of chemical risks, agencies such as the European Food Safety Authority (EFSA) heavily rely on the outcome of system...

Neural network analysis of pharyngeal sounds can detect obstructive upper respiratory disease in brachycephalic dogs.

Brachycephalic obstructive airway syndrome (BOAS) is a highly prevalent respiratory disease affecting popular short-faced dog breeds such as Pugs and ...

Artificial Intelligence-Based Classification of CT Images Using a Hybrid SpinalZFNet.

The kidney is an abdominal organ in the human body that supports filtering excess water and waste from the blood. Kidney diseases generally occur due ...

A preliminary study on the effects of long-term robot suit exercise training on gait function and quality of life in patients with spinal and bulbar muscular atrophy.

Spinal and bulbar muscular atrophy (SBMA) progressively impairs gait function, resulting in the need for patients to use a wheelchair approximately 20...

Accurate PM urban air pollution forecasting using multivariate ensemble learning Accounting for evolving target distributions.

Over the past decades, air pollution has caused severe environmental and public health problems. According to the World Health Organization (WHO), fin...