Pain Management

Electrophysiological-based automatic subgroups diagnosis of patients with chronic dysimmune polyneuropathies.

BACKGROUND: Chronic Dysimmune Polyneuropathies (CDP) encompass a group of conditions characterized by autoimmune etiology targeting myelin and/or axonal components. Subgroups include Chronic Inflammatory Demyelinating Polyneuropathy (CIDP) and paraproteinemic neuropathies associated with IgM monoclonal gammopathy of undetermined significance, with anti-MAG antibodies (IgM-MGUS anti-MAG+) and witho...

Spatio-temporal transformer and graph convolutional networks based traffic flow prediction.

Traffic flow prediction is a core component of intelligent transportation systems, providing accurate decision support for traffic management and urban planning. Traffic flow data exhibits highly complex spatiotemporal characteristics due to the intricate spatial correlations between nodes and the significant temporal dependencies across different time intervals. Despite substantial progress in th...

Improving prediction of fragility fractures in postmenopausal women using random forest.

Osteoporosis is a chronic disease characterized by a progressive decline in bone density and quality, leading to increased bone fragility and a higher...

Ultrasound Imaging and Machine Learning to Detect Missing Hand Motions for Individuals Receiving Targeted Muscle Reinnervation for Nerve-Pain Prevention.

Targeted muscle reinnervation (TMR) was initially developed as a technique for bionic prosthetic control but has since become a widely adopted strateg...

Precise metabolic dependencies of cancer through deep learning and validations.

Cancer cells exhibit metabolic reprogramming to sustain proliferation, creating metabolic vulnerabilities absent in normal cells. While prior studies ...

The value of triglyceride-glucose index-related indices in evaluating migraine: perspectives from multi-centre cross-sectional studies and machine learning models.

BACKGROUND: This study employed representative data from the U.S. and China to delve into the correlation among migraine prevalence, the triglyceride‒...

Regional anaesthesia in combat settings: a position paper from military physicians.

Regional anaesthesia (RA) is a powerful tool in combat casualty care. As contemporary warfare evolves towards major engagements and delayed evacuation...

Optic nerve sheath diameter in the prognosis of patients with traumatic optic neuropathy: Evaluation and predictive efficacy.

The purpose of this study was to evaluate and predict visual prognosis in patients with traumatic optic neuropathy by measuring the optic nerve sheath...

Advanced multiscale machine learning for nerve conduction velocity analysis.

This paper presents an advanced machine learning (ML) framework for precise nerve conduction velocity (NCV) analysis, integrating multiscale signal pr...

Using graph machine learning to identify functioning in patients with low back pain in terms of ICF.

As a comprehensive perspective on functioning is useful in patient assessments, the WHO developed the International Classification of Functioning, Dis...

Advanced machine learning applications in fibromyalgia to assess the relationship between 3D spinal alignment with clinical outcomes.

This study leveraged machine learning (ML) models to explore the relationship between three-dimensional (3D) spinal alignment parameters and clinical ...

A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques.

In this paper, three Double Machine Learning (DML) models are proposed to enhance the accuracy of breast cancer detection using machine learning techn...

Artificial intelligence-enhanced pain management: the NXTSTIM EcoAI platform.

Chronic pain affects approximately 20% of the global population, leading to significant disability and economic burden. Traditional management strateg...

Orbital CT deep learning models in thyroid eye disease rival medical specialists' performance in optic neuropathy prediction in a quaternary referral center and revealed impact of the bony walls.

PURPOSE: To develop and evaluate orbital CT deep learning (DL) models in optic neuropathy (ON) prediction in patients diagnosed with thyroid eye disea...

Recent Advances in Analytical Methods for Aconitine Alkaloid in Natural Products: A Systematic Review.

INTRODUCTION: Aconitine, the main toxic and active compound in Aconitum species, is a key component of Traditional Chinese Medicine (TCM), valued for ...

Multi-modal and Multi-view Cervical Spondylosis Imaging Dataset.

Multi-modal and multi-view imaging is essential for diagnosis and assessment of cervical spondylosis. Deep learning has increasingly been developed to...

Machine learning analysis of kinematic movement features during functional tasks to discriminate chronic neck pain patients from asymptomatic controls.

This study evaluated the discriminative potential of a machine learning model using movement features during functional tasks to distinguish between p...

Machine learning of time series data using persistent homology.

This study proposes a novel method for time-series analysis based on persistent homology. Traditional time-series analysis techniques based on persist...

Predicting diabetic peripheral neuropathy through advanced plantar pressure analysis: a machine learning approach.

Diabetic foot Ulceration (DFU) is a severe complication of diabetic foot syndrome, often leading to amputation. In patients with neuropathy, ulcer for...

Automatic pain classification in older patients with hip fracture based on multimodal information fusion.

Given the limitations of unimodal pain recognition approaches, this study aimed to develop a multimodal pain recognition system for older patients wit...