Pain Management

Construction of a multi-dimensional predictive model for college students' academic performance based on deep learning.

Academic performance (AP) prediction is crucial for recognizing at-risk students and enhancing learning outcomes. Traditional statistical models often fail to capture temporal and behavioral patterns. Deep learning (DL) approaches offer improved accuracy and adaptability by leveraging multi-dimensional student data for predictive analysis. The objective is to advance a robust predictive model that...

A synergistic framework integrating CPO-VMD with BiLSTM-TimesNet for accurate prediction of nonlinear and nonstationary runoff time series.

Accurate runoff prediction is essential for effective water resource management, yet the complex characteristics of runoff sequences-such as nonlinearity, non-stationarity, and intricate temporal dependencies-pose significant challenges. This study proposes a hybrid prediction framework that integrates the Crested Porcupine Optimizer (CPO), Variational Mode Decomposition (VMD), Bidirectional Long ...

Artificial intelligence in pain assessment and management for older adults: A scoping review.

INTRODUCTION: Conventional pain management strategies often fall short in addressing the complex needs of older adults with pain. Artificial intellige...

Machine learning analysis of physical factors associated with low back pain in male high school soft tennis players: Emphasis on nondominant hip internal rotation.

OBJECTIVE: Low back pain (LBP) is common among adolescent racket sport athletes; however, simultaneous assessment of multiple sport-specific physical ...

Osteoarthritis phenotypes: advancing precision medicine through clinical, structural, and molecular stratification.

PURPOSE: Osteoarthritis (OA) is now understood as a heterogeneous syndrome driven by diverse biological, biomechanical, metabolic, genetic, and molecu...

Artificial intelligence for left ventricular strain.

PURPOSE OF REVIEW: To review recent advances in artificial intelligence (AI) for left ventricular (LV) strain echocardiography, with emphasis on studi...

Spectral clustering identifies patterns of chiropractic care in a national longitudinal cohort.

OBJECTIVE: Characterise longitudinal patterns of chiropractic visits for neck pain or low back pain by using machine learning (ML) methods and explain...

An interpretable machine learning model for predicting emergence agitation in children: a multicenter development and validation study.

BACKGROUND: Postoperative agitation (EA) is a common complication in pediatric patients, and its early identification is crucial for improving periope...

Gaussian Adaptive Patching Powered Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data.

Multivariate Time-Series (MTS) data is crucial across diverse domains. With its sequential and multi-source (e.g., sensors) properties, MTS data inher...

Cardiovascular Disease Events and Life Expectancy Lost Attributable to Machine Learning-Derived Dietary Networks: Evidence from Canadian National Nutrition Survey Linked to Routinely Collected Administrative Databases.

BACKGROUND: Artificial intelligence and machine learning (ML) are transforming nutritional epidemiology by revealing dietary network structures invisi...

Inflammatory-neurodegenerative crosstalk in pediatric severe traumatic brain injury: a multi-domain plasma proteomic study.

BACKGROUND: Pediatric severe traumatic brain injury (sTBI) remains a leading cause of death and long-term disability, yet its molecular characterizati...

Microfluidic co-culture system for synaptically segregated neural networks to explore astrocyte-driven neural pathology.

Investigating astrocyte-neuron communication in the absence of neuron-to-neuron signalling is challenging using traditional culture systems due to the...

Adrenal gland dysfunction in males with cluster headache.

BACKGROUND: Cluster headache is associated with compensated hypogonadism in males, suggesting impaired testicular steroidogenesis. It is unknown if ad...

Impaired glymphatic function and advanced brain age gap in chronic migraine: a multimodal MRI study.

OBJECTIVES: This study investigated whether the coupling between cortical blood-oxygen-level-dependent (BOLD) signals and cerebrospinal fluid (CSF) fl...

Prediction of postoperative desaturation and bradycardia in neonates undergoing laparoscopic inguinal hernia repair: a retrospective cohort study.

BACKGROUND: Ex-premature infants have a high risk of postoperative apnea and bradycardia. This study aimed to develop a predictive model for postopera...

EEG-Based Clustering Shows Distinct Separation of Chronic Pain Patients Before Spinal Cord Stimulation Surgery.

Chronic pain is associated with disrupted cortical activity, yet individual variability in these neural patterns remains poorly understood. Electroenc...

Sensory nerves protect against preclinical tendinopathic changes through FGF1 signaling.

Chronic tendinopathy is typified by persistent tendon-associated pain, transmitted by local nociceptive neurons. However, the regulatory function of s...

Prediction of Oswestry Disability Index and Numeric Rating Scale scores after lumbar spine surgery: machine learning model development and fairness assessment.

BACKGROUND: One-third of patients operated for degenerative conditions in the lumbar spine do not report substantial improvement after 12 months. Most...

A deep learning ECG model for identification and localization of occlusion myocardial infarction.

Rapid identification and localization of an acute coronary occlusion are vital to prevent myocardial damage, yet reliance on ST-segment ECG criteria m...

Quantitative sensory testing and classical pain model dataset in 127 healthy volunteers.

Experimental pain models are integral to human pain research and the development of analgesic drugs. Of many options available, it is possible to iden...