Pain Management

Identification of small-molecule TNF-α inhibitor candidates using machine learning-guided screening and multiscale molecular modelling.

Lumbar disc herniation (LDH) is a major cause of chronic low back pain, in which tumor necrosis factor-alpha (TNF-α) plays a central role in inflammation and pain signaling. While biologic TNF-α inhibitors have shown therapeutic benefit, their systemic administration, high cost, and limited penetration into the avascular disc environment restrict their clinical utility. In this study, we present a...

Vestibular cortex-related effective connectivity signatures: characterization and differentiation of vestibular migraine patients via magnetic resonance imaging and machine learning.

BACKGROUND: Neuroimaging studies of vestibular migraine (VM) have revealed abnormal functional connectivity in the central vestibular system. However, it remains to be determined whether effective connectivity (EC) of the vestibular cortex is specifically disrupted in VM and whether this brain measure can aid in the differential diagnosis of VM patients. METHODS: In 56 VM patients, 58 episodic mig...

Outer nuclear layer thinning as an in vivo biomarker for discriminating probable FTLD-tau from probable FTLD-TDP with PET-supported subtyping.

BACKGROUND AND OBJECTIVES: Outer nuclear layer (ONL) thinning has been identified in frontotemporal lobar degeneration (FTLD); however, its utility fo...

Development and psychometric analysis of 5-item Artificial Intelligence Attitude (AIAT-5) for students.

In the context of accelerating integration of artificial intelligence (AI) technologies into education, rapidly assessing students' AI attitude is cru...

CTE has multiple pathologic variants that might relate to different clinical symptom presentation.

Chronic traumatic encephalopathy (CTE) is a progressive neurodegenerative disease found in individuals with a history of repetitive head injury (RHI) ...

An interpretable machine learning model for diabetic foot risk classification in patients with diabetes.

Diabetic foot is a severe chronic complication of diabetes, mainly resulting from peripheral neuropathy and vasculopathy, and may progress to ulcers, ...

Integrating neurobiological markers to prospectively predict adolescent non-suicidal self-injury and suicide attempts: a machine learning approach.

BACKGROUND: Suicide attempts (SA) and non-suicidal self-injury (NSSI) are closely related phenomena, both common in adolescent clinical samples. This ...

Archetypal analysis quantifies changes in patterns of visual field loss in eyes with acute non-arteritic anterior ischaemic optic neuropathy.

AIMS: We characterised visual field (VF) spatial loss patterns in acute non-arteritic anterior ischaemic optic neuropathy (NAION) using archetypal ana...

Predicting persistent pain after total knee arthroplasty using different machine learning algorithms.

BACKGROUND AND PURPOSE:  After total knee arthroplasty (TKA), 10-20% of patients remain unsatisfied. Well-performing clinical prediction models can pr...

Potential of Digital Tools for Chronic Pain Management.

Chronic pain is notoriously complex to manage and treat. In this News and Perspectives article, JMIR Correspondent Vanessa Nirode reports on several d...

AAPM Consensus Guidelines on Neuromodulation Technologies and Neurocomputer Interfaces for Pain Management and Functional Recovery.

OBJECTIVE: To provide an evidence-based framework for healthcare professionals to use neuromodulation technologies to restore neuromuscular function a...

Development of Data-Driven Models for Just-in-Time Digital Self-Management Advice to Improve Physical Functioning in Hip and Knee Osteoarthritis: Protocol for the e-cOAch Cross-Over Study.

BACKGROUND: Clinical guidelines recommend a stepped-care strategy for patients with hip and knee osteoarthritis that begins with nonoperative approach...

Protocol for assessment of pain biomarkers in orthopaedic patients undergoing total knee arthroplasty in a tertiary care hospital and neuroimmunopharmacology laboratory in South Australia: a cross-sectional matched-subject observational study.

INTRODUCTION: Knee osteoarthritis is a leading cause of pain and disability and frequently results in total knee arthroplasty (TKA). Decisions about s...

Cross-attention guided explainable deep transformer model for multi-level classification of rare neurological disorders using MRI images.

Neurological disorders (ND) impact a significant number of the population all over the world, affecting the brain, spinal cord, and peripheral nerves....

Enhancing stock market price prediction through FinGPT-driven sentiment analysis, technical indicators, historical price data, and attention-based hybrid deep learning models.

Accurate stock price forecasting is increasingly dependent on models that can integrate heterogeneous market signals beyond traditional quantitative i...

A smart nutrition system for vitamin B12 deficiency management from sensing to precision intervention.

Vitamin B12 is essential for neural function, red blood cell formation, and DNA synthesis, yet its deficiency persists as a global health burden drivi...

Nanoelectronic Detection of Opioids: Machine Learning-Powered Screening With Carbon Nanotube Field-Effect Transistor Sensor Array.

The development of inexpensive, portable, and rapid opioid screening techniques is urgently needed because of the ongoing opioid crisis in the United ...

Integrating Psychosocial Factors into Artificial Intelligence Models for Predicting Addiction Treatment Outcomes: A Systematic Review.

INTRODUCTION: The integration of artificial intelligence (AI) into addiction research has expanded rapidly, yet it remains unclear how psychosocial, b...

Development and validation of an interpretable model for pre-chemotherapy triage of fatigue-pain-sleep disturbance burden in lung cancer.

PURPOSE: The aim of the study is to develop an interpretable machine learning model that can effectively identify patients at risk of high fatigue-pai...

Capturing Finer-grained Long-range Dependency for Dense Prediction in Medical Images: An Empirical Investigation of MLPs.

Dense prediction is a fundamental problem in medical image analysis. As Convolutional Neural Networks (CNNs) are limited by the intrinsic locality of ...