Fibromyalgia

Machine learning and SHAP interpretation to identify high-level compassion fatigue among operating room nurses: a multicenter cross-sectional study.

BACKGROUND: Operating room nurses (ORNs) are at high risk for compassion fatigue (CF), which significantly impairs individuals' well-being, undermines the stability of the nursing workforce, and jeopardizes patients' safety. The study aimed to analyze the prevalence and symptom characteristics of CF among ORNs, construct and compare predictive models using machine learning, and determine the relat...

Methodological illustration using machine learning methods to predict cancer-related fatigue in cancer patients.

Supervised machine learning is a popular tool for predictor selection in large data sets. The choice of method is currently either based on theory, subjective preferences, previous general simulation studies, or the best fit of a method to the data, which does not allow evaluating the methods' performance for a specific empirical application. In this article, we illustrate how to select a method t...

Sustainable Synaptic Device with Two-Dimensional Ferroelectric Materials for Neuromorphic Computing.

To overcome the coming big-data era, significant efforts are needed to implement neuromorphic computing that mimics the functional and structural feat...

Divergent neuropsychiatric and systemic toxicity profiles of abemaciclib and palbociclib: a triangulation study integrating pharmacovigilance, genetic epidemiology, and multi-omics profiling.

Cyclin-dependent kinase 4/6 inhibitors improve outcomes in hormone receptor-positive, human epidermal growth factor receptor 2-negative advanced breas...

Adaptive multimodal learning for driver cognitive state monitoring using transformer-based fusion with personalized meta-learning and federated optimization.

Road accidents caused by driver fatigue and cognitive overload remain a significant public safety concern. According to recent traffic safety data, dr...

Topological data analysis improves estimation of muscle fatigue and contraction level from surface electromyography data.

ObjectiveMuscle fatigue affects individuals with neuromuscular disease and elite athletes alike. Muscle fatigue is difficult to reliably assess using ...

Multi-scale data improves performance of machine learning model for long COVID identification.

BACKGROUND: Long COVID affects a substantial proportion of the over 778 million individuals infected with SARS-CoV-2, yet predictive models remain lim...

Multivariate Pattern Analysis Identifies Potential Intertrial Resting-State EEG Biomarkers in Fibromyalgia.

Fibromyalgia involves widespread musculoskeletal pain and hypersensitivity, often accompanied by neurological, cognitive, and affective disturbances. ...

Structural optimization principles for edge AI in motorsport telemetry.

In motorcycle motorsport, engineering decisions are constrained by mass, stiffness, fatigue life, and thermal margins. In a comparable way, deploying ...

AI for Hospital Infection Prevention and Control: Real-World Implementation, Impact, and the Gap Beyond Model Development.

BACKGROUND: Artificial intelligence and machine learning (AI/ML) may strengthen hospital infection prevention and control (IPC) through automated surv...

Assessment models for driving comfort and fatigue status based on heart rate variability.

OBJECTIVES: This study, from an interdisciplinary perspective of human factors engineering and biomedical engineering, aims to develop a real-time ass...

Time-Dynamic AI Models to Predict Quality of Life in Patients With Breast Cancer: Development and Validation Study Using the EORTC BALANCE Cohort.

BACKGROUND: Patients with breast cancer often experience health-related quality of life (HRQoL) impairments that remain difficult to predict on an ind...

Evaluation of basic life support practice skills based on artificial intelligence technology: system construction and evaluation equivalence validation.

BACKGROUND: Basic life support (BLS) skills are the core competencies of healthcare professionals in responding to emergency situations. Traditional m...

The effects of fatigue on the relation between ocular pursuit and interceptive performance in soccer experts.

Accuracy and duration of ocular pursuit of a target object have been linked to interceptive performance. Yet, previous assessments have not examined t...

Identifying Biomarkers Using a Portable, Home-Based Eye-Tracking System to Predict Short-Term Visual Fatigue Deterioration: Prospective Observational Feasibility Study.

BACKGROUND: The escalating prevalence of screen-related eye fatigue has become a health burden in the digital era worldwide, yet routine monitoring re...

The needle study: Machine learning as a new method for case-finding in celiac disease.

OBJECTIVES: Despite a well-defined diagnostic work-up, uncertainties persist regarding celiac disease (CeD) detection strategies in the general popula...

Parametrically upscaled model-based predictive platform for fatigue with location-specific microstructural linkages.

Fatigue in metallic materials is a cost-intensive engineering challenge due to unpredictable occurrences when undergoing cyclic loading. Particularly ...

Artificial intelligence and wearable sensors in sports injury risk prediction: current status and future perspectives.

BACKGROUND: Artificial intelligence (AI) and wearable sensors are increasingly reshaping sports injury risk prediction by enabling continuous, individ...

Long COVID: Deep single-cell immunophenotyping and machine learning reveal a general signature for fatigue.

Cognitive load and pedagogical tension in multi-platform online learning: Evidence from Chinese higher education.

The proliferation of digital tools has transformed higher education into a complex, multi-platform online learning environment. This study investigate...