Pain Management

CSA-Kansformer : Cross-scale aggregation and Kansformer network for hyperspectral image classification.

Hyperspectral image (HSI) classification is essential in remote sensing, leveraging rich spectral and spatial information. Convolutional neural networks (CNNs) excel at extracting local features, while transformers capture global semantic information. However, CNNs struggle with global dependencies, and transformers face high computational costs for hyperspectral data. To combine the strengths of ...

Automating wound assessment: convolutional neural network-based mobile application for SINBAD classification system.

INTRODUCTION: Diabetic foot ulcer (DFU) assessment using the SINBAD system is essential for clinical decision-making but often limited by access to specialists. This study presents a mobile application powered by a lightweight Convolutional Neural Networks (MobileNetV3 Small) to automate DFU classification. METHODS: A dataset of 996 clinician-labeled DFU images was used to train the model to class...

The Application Effect of Robot-Assisted Therapy for Hand Dysfunction After Stroke: A Scoping Literature Review.

This scoping review was designed to address the core question: In the field of poststroke hand function rehabilitation, what is the current status of ...

SPP1-CD44 signaling contributes to the mechanisms and therapeutic implications in intervertebral disc degeneration.

BACKGROUND: Intervertebral disc degeneration (IVDD) is a major pathological cause of chronic back pain and reduced mobility. Among emerging molecular ...

An Unsupervised Learning Approach for Multimodal Low Back Pain Stratification.

STUDY DESIGN: Cross-sectional study. OBJECTIVE: This study proposes a novel stratification framework for individuals with low back pain (LBP). The met...

Integrated metabolomics and transcriptomics reveal biomarkers for detecting fentanyl analog abuse through machine learning.

Fentanyl analogs' (FA) rampant proliferation causes widespread abuse, fatalities, and severe social issues globally. Their high toxicity, rapid metabo...

Wirelessly transmitted subthalamic nucleus signals decode endogenous pain levels in Parkinson's disease patients.

Pain is a prominent non-motor symptom of Parkinson's disease (PD); it may appear in various levels (elevated or diminished) during waking hours and su...

Exploring spatiotemporal heterogeneity and nonlinear effects in electric vehicle crash risk prediction: A hybrid modeling approach.

Electric vehicle (EV)-related risk and uncertainty pose critical challenges for urban traffic management. Fine-grained crash risk prediction at 1 km ×...

Multi-scale feature enhancement in multi-task learning for medical image analysis.

Traditional deep learning approaches in medical image analysis usually focus on either segmentation or classification, which limits their ability to e...

Identification of alkaline phosphatase as a putative biomarker of anti-NGF treatment-associated arthropathies: Machine learning-assisted analyses of clinical trial data.

OBJECTIVE: Nerve growth factor (NGF) inhibitors have been shown to provide pain relief in patients with osteoarthritis but are associated with adjudic...

Deep learning-based assessment of paraspinal muscle degeneration and its relationships to muscle function and disability outcomes in chronic low back pain: a prospective study.

OBJECTIVES: To investigate deep-learning (DL) model accuracy in quantifying multifidus (MF) and erector spinae (ES) fat fraction (FF) compared to Dixo...

Resting-state fMRI analysis of functional connectivity and temporal dynamics differences between cocaine users and healthy controls.

Understanding alterations in functional connectivity among individuals with substance use disorder (SUD) is critical for elucidating the neural mechan...

Cerebral blood flow and modern approaches for clinical assessment & monitoring: a view to the future.

Cerebral blood flow (CBF) is under homeostatic control via cerebral autoregulation, maintaining a constant blood supply to brain parenchyma by integra...

Literature-informed ensemble machine learning for three-year diabetic kidney disease risk prediction in type 2 diabetes: Development, validation, and deployment of the PSMMC NephraRisk model.

INTRODUCTION: Diabetic kidney disease (DKD) and diabetic nephropathy (DN) affect around 40% of diabetic patients but lack accurate risk prediction too...

mModPoEs: Multimodal posture estimation and feedback-driven correction of load-bearing human movements using wearable sensors and computer vision.

OBJECTIVE: Improper spinal posture during activities of daily living such as seated posture, upright stance, and ambulation, particularly under load-b...

Performance of ChatGPT versus spine surgeons as an emergency department spine call consultant.

BACKGROUND: Large language models (LLMs) like ChatGPT are increasingly being recognized as credible tools for use across diverse healthcare settings. ...

Artificial intelligence and machine learning applications in ambulatory surgery - A systematic review.

BACKGROUND: We aimed to systematically review applications of artificial intelligence (AI) technologies for ambulatory surgical patients. METHODS: We ...

Patellofemoral pain is associated with complex gait deviations captured by an artificial intelligence-derived gait index.

BACKGROUND: Patellofemoral pain (PFP) in active women is associated with gait adaptations. The Movement Deviation Profile (MDP) summarises deviations ...

Machine Learning-Based Prediction for Axial Pain Following Expansive Unilateral Open-Door Laminoplasty: A Retrospective Cohort Study.

INTRODUCTION: Axial pain is a common complication following expansive unilateral open-door laminoplasty (ELAP); however, traditional statistical metho...

AI-powered intestinal ultrasound in inflammatory bowel disease: Advancing toward automated disease assessment.

The management of inflammatory bowel disease (IBD) relies on accurate disease assessment and close monitoring to guide therapy and evaluate treatment ...