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Fibromyalgia

Latest AI and machine learning research in fibromyalgia for healthcare professionals.

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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 athle...

Chlorfenapyr-related delayed rhabdomyolysis: a case series.

INTRODUCTION: Chlorfenapyr, a broad-spectrum insecticide and acaricide of the pyrrole-class pesticid...

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 py...

Predicting Discharge Destination From Inpatient Rehabilitation Using Machine Learning.

Predicting discharge destination for patients at inpatient rehabilitation facilities is important as...

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 assortmen...

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

The transmission gearbox of military helicopters, such as the H225M, experiences intense dynamic loa...

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...

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 fatig...

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 c...

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 f...

The Transformative Power of Digital Breast Tomosynthesis and Artificial Intelligence in Breast Cancer Diagnosis.

The integration of Digital Breast Tomosynthesis (DBT) and Artificial Intelligence (AI) represents a ...

Enhanced interpretable thyroid disease diagnosis by leveraging synthetic oversampling and machine learning models.

Thyroid illness encompasses a range of disorders affecting the thyroid gland, leading to either hype...

Machine-Learning Mental-Fatigue-Measuring μm-Thick Elastic Epidermal Electronics (MMMEEE).

Electrophysiological (EP) signals are key biomarkers for monitoring mental fatigue (MF) and general ...

Current update on the neurological manifestations of long COVID: more questions than answers.

Since the outbreak of the COVID-19 pandemic, there has been a global surge in patients presenting wi...

Rapid detection of poultry meat quality using S-band to KU-band radio-frequency waves combined with machine learning-A proof of concept.

Rapid changes in consumer preferences for high-quality animal-based protein have driven the poultry ...

Effect of Forsus-assisted mandibular advancement on the adaptation of craniocervical posture - A retrospective study.

BACKGROUND AND OBJECTIVE: Skeletal Class II malocclusion patients frequently exhibit an extended cra...

Risk of crashes among self-employed truck drivers: Prevalence evaluation using fatigue data and machine learning prediction models.

INTRODUCTION: Transportation companies have increasingly shifted their workforce from permanent to o...

Deep learning method for detecting fluorescence spots in cancer diagnostics via fluorescence in situ hybridization.

Fluorescence in Situ Hybridization (FISH) is a technique for macromolecule identification that utili...

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