Fibromyalgia

System for activity-aware fatigue evaluation (SAFE) framework: Predictive fatigue modelling for occupational tasks.

The SAFE (System for Activity-aware Fatigue Evaluation) framework integrates wearable sensing, biomechanical modelling, and task detection to enable monitoring of operator endurance and ergonomic risk. In this feasibility study, the framework was evaluated offline in a laboratory environment with 10 participants performing industry-type tasks, combining inertial measurement units (IMUs), pressure ...

DETERIO-LLM: enhancing traditional deterioration risk scores with clinical context and advanced reasoning.

OBJECTIVES: Accurate and timely prediction of physiological deterioration in hospitalized patients is essential, but existing deep learning models, which rely solely on structured electronic health record (EHR) data, generate high false-positive rates by missing crucial contextual information in clinical notes. We present DETERIO-LLM, a hybrid prediction model that selectively integrates large lan...

Natural language processing identifies symptoms predicting complete coronary artery occlusion in patients with NSTEMI.

AIMS: One in 10 patients present to the emergency department (ED) with symptoms of acute coronary syndrome (ACS). The 13-item ACS Symptom Checklist is...

Tree-based machine learning models recover rule-based flare labels from virtual symptom diaries in pediatric Behçet's disease: an in silico proof-of-concept study.

Behçet's disease (BD) in childhood is characterised by recurrent inflammatory flares that can result in significant morbidity, most notably with ocula...

Disease-modifying antirheumatic drugs (DMARDs) for rheumatoid arthritis after failure of biologic or targeted synthetic therapy: a systematic review and network meta-analysis.

RATIONALE: After inadequate response to first-line biologic or targeted synthetic (b/ts) disease-modifying antirheumatic drug (DMARD) therapy in adult...

Wearable fatigue detection system for wheelchair propulsion: Identifying key muscles via an attention-based LSTM Model.

Fatigue induces adverse short- and long-term health risks in wheelchair users. This study aimed to develop a machine learning approach to predict fati...

fAI-BRO: a multimodal AI decision-support system to address diagnostic delay in fibromyalgia syndrome.

OBJECTIVE: To evaluate the diagnostic accuracy and patient acceptability of fAI-BRO (Fibromyalgia AI-Based Rheumatology Observer), a multimodal artifi...

Artificial Intelligence Cannot Replace Peer Reviewers but May Help Editors Triage: A Comparative Analysis of a Large Language Model and Human Reviewer Recommendations at the American Journal of Sports Medicine.

BACKGROUND: The peer review system faces increasing strain from rising manuscript volumes, reviewer fatigue, and well-documented interreviewer disagre...

Skyer: a novel benchmark for evaluating the effectiveness of large language models in emergency department triage.

OBJECTIVES: Emergency department (ED) overcrowding causes diagnostic challenges, prolonged wait times, and impairs appropriate triage, often due to hu...

Motor-free hip exosuit via high-output fibrous dielectric elastomer actuators.

Exosuits can assist gait and reduce fatigue for both healthy and pathological populations, yet their bulky, rigid actuators (usually motors or pneumat...

Development and validation of an AI-driven multimodal system for assessing aerobic gymnastics training using video analysis, motion capture, and physiological signals.

This research developed and validated a comprehensive multimodal assessment system integrating artificial intelligence for aerobic gymnastics training...

Structure-aware fatigue modeling in foot deformities: A digital health framework for tissue-specific running injury risk prediction using multi-modal data.

Hallux Valgus (HV) is a common deformity in runners that reflects altered foot morphology and thereby redistributes mechanical loads along the lower l...

Brain network correlates of fatigue, depression, and anxiety in patients with Crohn's Disease in different disease states.

BACKGROUND: Symptoms of fatigue, depression or anxiety are frequent in Crohn's Disease (CD) and may relate to disturbed brain-gut interactions. While ...

AI-driven diagnostic algorithm enhances early detection of paroxysmal nocturnal hemoglobinuria in real-world settings.

Paroxysmal nocturnal haemoglobinuria (PNH) is a rare, life-threatening hematologic disease with diagnostic delays exceeding 5 years in 24% of cases. W...

Multimodal health monitoring and theranostics based on functionalized hydrogels and artificial intelligence.

Functionalized hydrogels are ideal flexible interfaces for multimodal health monitoring and integrated diagnosis-therapy systems, owing to their tissu...

Injury prediction in elite women's football: an integrative machine learning-based decision-support framework.

Injuries in elite sports disrupt team performance, shorten careers, and incur significant financial costs, highlighting the critical need for accurate...

Using Machine Learning for Identification of Athlete Availability Predictors in a Multisport Elite Female Athlete Cohort.

Moore, SR, Cantú, EI, Brantner, CL, Britton, ME, DelBiondo, GM, Blue, MNM, Bruinvels, G, Hackney, AC, Register-Mihalik, JK, and Smith-Ryan, AE. Using ...

Dual-stream learning with inverted transformer and BiGRU for rolling bearing remaining useful life prediction.

Predicting the remaining useful life (RUL) of rolling bearings is essential for ensuring the reliability and safety of rotating machinery. However, ac...

From muscles to motion: the role of sensor layout and physiological factors in hand motion decoding.

Despite substantial progress in decoding biosignals for human motion prediction, the influence of participant- and experiment-related factors on the d...

Post-stroke rehabilitation in inflammatory rheumatic diseases: outcome measures, digital tools, and patient education perspectives.

Inflammatory rheumatic diseases (IRDs) represent a significant risk factor for cerebrovascular events, independent of traditional cardiovascular risk ...