Latest AI and machine learning research in fibromyalgia for healthcare professionals.
Internal medicine involves high-stakes, time-sensitive decisions (such as triaging acute illnesses, escalating care, providing thromboprophylaxis, planning discharges, and managing chronic diseases) often under uncertainty. Risk stratification tools convert limited bedside data into actionable categories. Predictive analytics, by contrast, draws on richer electronic health record data streams to e...
BACKGROUND: Traditional linear approaches may not adequately capture the non-linear relationships and interactions among laboratory-derived sprint test metrics. This study aimed to predict flying sprint performance of elite-level male track cyclists using multiple linear regression and random forest models based on anaerobic ergometer metrics. METHODS: A total of 333 elite male track cyclists comp...
OBJECTIVES: Effective dose management in computed tomography is impeded by 2 key operational challenges: error-prone manual protocol mapping and the h...
This study introduces a simulation-based wearable biomechanical sensor network framework intended to support real-time fatigue monitoring and performa...
Tick bites in Australia are associated with a poorly understood syndrome known as Debilitating Symptom Complexes Attributed to Ticks (DSCATT), however...
OBJECTIVE: To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self-management and identify patterns asso...
BACKGROUND: Occupational fatigue is a major safety and health risk across work sectors. Because fatigue accumulates and fluctuates over time, effectiv...
INTRODUCTION: Long COVID is a multisystem condition with challenging diagnosis. Nurse-navigation, a patient-centered intervention, can enhance educati...
Post-COVID-19 syndrome encompasses persistent cognitive, neurological, and psychiatric symptoms following SARS-CoV-2 infection, profoundly affecting g...
We present a curated dataset of planar displacement fields from eight fatigue crack growth experiments obtained via full-field digital image correlati...
In real-world occupational settings, mental fatigue commonly emerges from the combination of sleep deprivation with prolonged cognitive and physical w...
INTRODUCTION: Falls are a significant concern for older adults, particularly those with neurological, vestibular, cognitive and post-viral conditions,...
BackgroundThe surgical workforce in the United States is aging while artificial intelligence (AI) tools are increasingly integrated into clinical prac...
INTRODUCTION: Cellular senescence, involving cell-cycle arrest and inflammatory factor release, may play a role in Long COVID development. We investig...
As generative artificial intelligence (AI), particularly large language model-based tools, is increasingly integrated into diagnosis, triage, decision...
INTRODUCTION: Evidence from head-to-head comparisons of biologic/targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) on patient-repo...
INTRODUCTION: OSAS is a common yet underdiagnosed condition, particularly among patients with head and neck cancers (HNC). Anatomical changes caused b...
Scientific exercise monitoring is significant for injury risk prevention and training outcome promotion. Wearable biosensing technologies have emerged...
This systematic review examined the use of surface electromyography (sEMG) for the neuromuscular assessment of individuals with Amyotrophic Lateral Sc...
BACKGROUND: Artificial intelligence models for acute kidney injury (AKI) prediction achieve strong discriminative accuracy, yet clinical adoption rema...