Latest AI and machine learning research in sports medicine for healthcare professionals.
ObjectiveTo investigate how varying workload intensity and personalized conditions influence physiological stress responses and task efficiency in human-robot collaboration (HRC).BackgroundHRC is increasingly used to enhance productivity and reduce physical demands, yet workers' mental and physiological strain remains unaddressed. High workload intensity, often induced by robot pacing, can elevate...
Hydrogel sensors have gained significant attention in recent years due to their ability to detect various stimuli. This work first employs a "one-pot method" to construct a semi-interpenetrating network (sIPN) gel composed of polyvinyl alcohol (PVA) and pullulan polysaccharide (PUL), combined with potassium chloride (KCl) and MXene to establish an electrically conductive network. Then, the hydroge...
Advancements in computer vision and deep learning have revolutionized sports video analysis, enabling automated and precise data labeling. However, th...
As the world's population ages, ensuring the safety of older adult pedestrians has become an urgent priority in transportation planning. However, most...
Blepharospasm-related dry eye is a complex multifactorial comorbidity involving neural, ocular surface, and psychological factors, currently facing co...
Oral cancer and oral potentially malignant disorders (OPMDs) remain a significant challenge in diagnosis and therapy, primarily due to inherent limita...
By integrating the principles of kirigami cutting and data-driven modeling, this study aims to develop a personalized, rapid, and low-cost design and ...
OBJECTIVES: To examine the emotional, cognitive and dispositional experience of children and adolescents undergoing Lokomat rehabilitation by integrat...
AIMS: We applied unsupervised machine learning clustering to a large cohort of hypertensive patients undergoing echocardiography with strain imaging t...
OBJECTIVE: This study aimed to develop and validate stratified machine learning models for early prediction of anti-tuberculosis drug-induced liver in...
The advancement of personalized medicine is increasingly reliant on wearable health monitoring technologies. While hydrogels offer great promise for s...
BACKGROUND: Low back pain (LBP) is a leading cause of global disability. Most cases are non-specific (NSLBP) and lack identifiable causes. Early activ...
Cardiogenic shock (CS) remains a leading cause of death in intensive cardiac care. Outcomes are limited by delayed recognition of hypoperfusion, heter...
High-fidelity surface electromyography (sEMG) acquisition under dynamic conditions is critical for rehabilitation, sports monitoring, and human-machin...
PURPOSE: The tibial slope is a well-known risk factor for anterior cruciate ligament (ACL) injury. As machine learning continues to progress, it has b...
The causes of endurance running-related injury (RRI) are multifactorial, yet little research has been conducted which utilizes multidisciplinary risk ...
BACKGROUND: We aimed to develop a novel cardiac magnetic resonance (CMR)-based method for quantifying myocardial synchrony and evaluate its diagnostic...
Piperine is a common anti-ischemic compound and an active ingredient of herbal medicine for various ailments. It is widely sourced and affordable. How...
INTRODUCTION: Artificial intelligence (AI) technologies are increasingly being integrated into pulmonary rehabilitation (PR) to improve individualizat...
PURPOSE OF REVIEW: Achieving long-term survival after lung transplantation remains a major challenge. Outcome determinants have expanded beyond pathop...