Fibromyalgia

Rapidly self-healing electronic skin for machine learning-assisted physiological and movement evaluation.

Emerging electronic skins (E-Skins) offer continuous, real-time electrophysiological monitoring. However, daily mechanical scratches compromise their functionality, underscoring urgent need for self-healing E-Skins resistant to mechanical damage. Current materials have slow recovery times, impeding reliable signal measurement. The inability to heal within 1 minute is a major barrier to commerciali...

Artificial intelligence-assisted diagnosis of early gastric cancer: present practice and future prospects.

Gastric cancer (GC) occupies the first few places in the world among tumors in terms of incidence and mortality, causing serious harm to human health, and at the same time, its treatment greatly consumes the health care resources of all countries in the world. The diagnosis of GC is usually based on histopathologic examination, and it is very important to be able to detect and identify cancerous l...

Subjective recovery in professional soccer players: A machine learning and mediation approach.

Coaches often ask players to judge their recovery status (subjective recovery). We aimed to explore potential determinants of subjective recovery in 1...

EEG-based fatigue state evaluation by combining complex network and frequency-spatial features.

BACKGROUND: The proportion of traffic accidents caused by fatigue driving is increasing year by year, which has aroused wide concerns for researchers....

Application of Wearable Insole Sensors in In-Place Running: Estimating Lower Limb Load Using Machine Learning.

Musculoskeletal injuries induced by high-intensity and repetitive physical activities represent one of the primary health concerns in the fields of pu...

A Deep Learning Approach for Mental Fatigue State Assessment.

This study investigates mental fatigue in sports activities by leveraging deep learning techniques, deviating from the conventional use of heart rate ...

Acrobatics at the insect scale: A durable, precise, and agile micro-aerial robot.

Aerial insects are exceptionally agile and precise owing to their small size and fast neuromotor control. They perform impressive acrobatic maneuvers ...

Machine learning and multi-omics in precision medicine for ME/CFS.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex and multifaceted disorder that defies simplistic characterisation. Traditiona...

Application of Additive Manufacturing and Deep Learning in Exercise State Discrimination.

With the rapid development of sports technology, smart wearable devices play a crucial role in athletic training and health management. Sports fatigue...

Chlorfenapyr-related delayed rhabdomyolysis: a case series.

INTRODUCTION: Chlorfenapyr, a broad-spectrum insecticide and acaricide of the pyrrole-class pesticides, can induce dizziness, fatigue, profuse sweatin...

PFSH-Net: Parallel frequency-spatial hybrid network for segmentation of kidney stones in pre-contrast computed tomography images of dogs.

Kidney stone is a common urological disease in dogs and can lead to serious complications such as pyelonephritis and kidney failure. However, manual d...

Predicting Discharge Destination From Inpatient Rehabilitation Using Machine Learning.

Predicting discharge destination for patients at inpatient rehabilitation facilities is important as it facilitates transitions of care and can improv...

Development and validation of a machine learning-based predictive model for compassion fatigue in Chinese nursing interns: a cross-sectional study utilizing latent profile analysis.

BACKGROUND: Compassion fatigue is a significant issue in nursing, affecting both registered nurses and nursing students, potentially leading to burnou...

Comparison of the composition, immunological activity and anti-fatigue effects of different parts in sika deer antler.

BACKGROUND: Sika deer (, 1838) antler is a highly esteemed tonic renowned for its abundant assortment of polypeptides, polysaccharides, amino acids, a...

Addressing Gearbox Health Monitoring Challenges for Helicopters: A Machine Learning Approach.

The transmission gearbox of military helicopters, such as the H225M, experiences intense dynamic loads, leading to the detachment of ferromagnetic par...

STCNet: Spatio-Temporal Cross Network with subject-aware contrastive learning for hand gesture recognition in surface EMG.

This paper introduces the Spatio-Temporal Cross Network (STCNet), a novel deep learning architecture tailored for robust hand gesture recognition in s...

Semantically-Enhanced Feature Extraction with CLIP and Transformer Networks for Driver Fatigue Detection.

Drowsy driving is a leading cause of commercial vehicle traffic crashes. The trend is to train fatigue detection models using deep neural networks on ...

Real-Time Fatigue Detection Algorithms Using Machine Learning for Yawning and Eye State.

Drowsiness while driving is a major factor contributing to traffic accidents, resulting in reduced cognitive performance and increased risk. This arti...

Cross-sectional Study on Medical Attitude Towards Artificial Intelligence Use in Fibromyalgia: Insights From the Annual Thinking Lab on Fibromyalgia Syndrome (ATLAS 2024).

BACKGROUND: The integration of artificial intelligence (AI) in healthcare has the potential to revolutionize clinical practice, particularly in the ma...

Integrating lightweight YOLOv5s and facial 3D keypoints for enhanced fatigued-driving detection.

Several factors cause vehicle accidents during driving, such as driver negligence, drowsiness, and fatigue. These accidents can be prevented if driver...