Prevention

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...

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 hyperphenylalani...

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...

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. Numerou...

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, disabiliti...

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 unhealt...

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 per...

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 injur...

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 Auth...

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 fr...

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...

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. Acc...

Advancing geospatial preconception health research in primary care through medical informatics and artificial intelligence.

Established life course approaches suggest that health status in adulthood can be influenced by even...

Kinematics-Based Predictions of External Loads during Handcycling.

The increased risk of cardiovascular disease in people with spinal cord injuries motivates work to i...

Feedback control of heart rate during robotics-assisted tilt table exercise in patients after stroke: a clinical feasibility study.

BACKGROUND: Patients with neurological disorders including stroke use rehabilitation to improve cogn...

Artificial Intelligence and Health Inequities in Dietary Interventions on Atherosclerosis: A Narrative Review.

Poor diet is the top modifiable mortality risk factor globally, accounting for 11 million deaths ann...

Machine learning prediction of pulmonary oxygen uptake from muscle oxygen in cycling.

The purpose of this study was to test whether a machine learning model can accurately predict VO acr...

EGCN++: A New Fusion Strategy for Ensemble Learning in Skeleton-Based Rehabilitation Exercise Assessment.

Skeleton-based exercise assessment focuses on evaluating the correctness or quality of an exercise p...

A Computational Framework for Predicting Novel Drug Indications Using Graph Convolutional Network With Contrastive Learning.

Inferring potential drug indications plays a vital role in the drug discovery process. It can be tim...

Optimizing postprandial glucose prediction through integration of diet and exercise: Leveraging transfer learning with imbalanced patient data.

BACKGROUND: In recent years, numerous methods have been introduced to predict glucose levels using m...