Pain Management

Machine learning-based risk warning for adolescents' prosocial behavior.

Prosocial behavior plays a positive role in promoting adolescents' mental health and behavioral performance. Guided in ecological systems theory and social cognitive theory, this study used machine learning to identify the risk factors of adolescents' prosocial behavior, and a total of six machine learning algorithms (Logistic Regression, Naive Bayes, Decision Tree, Random Forest, KNN, and LightGB...

Literature Commentary June, 2026.

In this issue, the following 4 articles are reviewed by Drs. Mark L. Moster and Deborah I. Friedman, most of which include authors who are members of NANOS:Pakeerathan T, Davis J, Henderson AD, et al. OCT-based differentiation of first acute optic neuritis: an international study of 111 patients with NMOSD and MOGAD. Neurol Neuroimmunol Neuroinflamm. 2026;13:e200531. Brownlee WJ, Maccarrone D, Nis...

Response to the Letter to the Editor: "The Effectiveness of Artificial Intelligence Health Education Accurately Linking System on Self-Management in Non-Specific Lower Back Pain Patients".

Beyond clinical predictors: Determining the impact of psychosocial factors in chronic pain after spinal cord injury.

UNLABELLED: ▒: Although chronic pain is common after traumatic SCI, prognostic models have traditionally prioritized clinical injury characteristics, ...

An AI-Driven Pipeline for Localization, Segmentation, and Classification of Carpal Tunnel Syndrome Using Ultrasound Images of the Median Nerve.

BACKGROUND: Carpal tunnel syndrome (CTS), the most common peripheral neuropathy, is currently diagnosed by clinical suspicion supported by tools such ...

Circular RNAs in virus-induced cancers: From mechanism to clinical implications.

Viruses, during their lifecycle, are continuously dependent on host machinery for their survival. Sometimes this dependency leads to uncontrolled cell...

Imaging Primary Chronic Pain Syndromes: Current Evidence, Clinical Relevance, and Advances in MRI and PET/CT.

Primary chronic pain syndromes are increasingly understood through advanced neuroimaging techniques, which reveal consistent structural, functional, a...

MRI-based deep learning radiomics model for automated classification of disc degeneration in the lumbar spine.

Disc degeneration in the lumbar spine is a major cause of low back pain (LBP). The accurate grading of disc degeneration on magnetic resonance imaging...

Machine Learning-Based Prediction of Treatment Success, Postoperative Pain, and Analgesic Use After Full Pulpotomy in Permanent Molars with Symptomatic Irreversible Pulpitis.

INTRODUCTION: This study aimed to develop and evaluate machine learning (ML) models for predicting treatment success, postoperative pain, and analgesi...

Predict neuromuscular performance in human epidural electrical stimulation: phase 1 trial interim results.

BACKGROUND: Epidural electrical stimulation (EES) has emerged as a promising therapy for restoring motor function in patients with paralysis. A primar...

MGA-CLIP: A Multigranularity Attribution Framework for Cross-Modal Explainability in CLIP.

The contrastive language-image pretraining (CLIP) model has demonstrated remarkable performance in multimodal tasks, but the interpretability of its s...

MuSL: Multimodal deep learning for generalizable prediction of synthetic lethality from sequence, transcriptomic, and network data.

Synthetic lethality (SL) offers a promising paradigm for identifying selective anticancer targets. How ever, many computational SL prediction methods ...

The role of biopsychosocial factors in classifying pain intensity across various chronic pain conditions.

Chronic pain is a multifaceted condition shaped by biological, psychological, and social factors, which challenges its diagnosis and treatment. While ...

MSTM-Net: a two-stage prostate cancer segmentation network based on swin-transformer-mamba architecture.

BACKGROUND: Magnetic resonance imaging (MRI) has become a core imaging modality for prostate cancer screening and diagnosis. Accurate and automatic se...

Integrating multidimensional nociceptive-related cortical features for unsupervised assessment of anesthesia states in rats.

Accurate anesthesia monitoring remains challenging because current approaches primarily assess consciousness while overlooking nociceptive processing....

Sex-specific molecular and cellular phenotypes during resolution of neuropathic pain in dorsal root ganglia.

The dorsal root ganglion (DRG) is examined for sex-dependent phenotypes in sensory neurons, satellite glial cells (SGCs), and local macrophages follow...

Capturing multi-disease states on a spectrum with machine learning and routine clinical data.

BACKGROUND: Diseases exist on spectra of risk factors, cellular perturbations, organ dysfunction, and clinical manifestations. It is unknown whether t...

Joint trajectories of sleep duration and depressive symptoms and risk of incident multimorbidity: a longitudinal analysis with machine learning prediction.

BACKGROUND: Sleep disturbances and depressive symptoms frequently co-occur in older adults. Both conditions follow distinct, time-varying trajectories...

From Three to Eight Clusters: A Machine Learning-Based Classification of Operated Adult Spinal Deformity Patients.

BACKGROUND: Adult spinal deformity (ASD) is a heterogeneous condition encompassing diverse etiologies, clinical presentations, and surgical challenges...

Idiopathic Intracranial Hypertension Is Characterized by a Distinct Proteomic Profile.

OBJECTIVES: The pathophysiology of idiopathic intracranial hypertension (IIH) is poorly understood and disease-specific biomarkers are lacking. We aim...