Pain Management

Distinct transcriptional signatures of large-scale functional gradient organization in acute and chronic low back-related leg pain.

Low back-related leg pain (LBLP)-a severe subtype marked by radicular symptoms and high chronicity rates-implicates central nervous system reorganization, yet the large-scale functional gradient organization principles governing brain-wide functional shifts during chronicization remain unknown. Here, we used "Functional Gradient-Transcriptomics" analysis to characterize hierarchical brain reorgani...

The emerging role of oligodendrocytes in Alzheimer's disease: Integrating bibliometric insights with molecular pathogenesis.

BackgroundOligodendrocytes (OLs) have received relatively limited attention in Alzheimer's disease (AD) research; however, recent studies highlight their significant role in AD pathology, particularly in neuroinflammation and myelin integrity.ObjectiveTo bibliometrically analyze oligodendrocyte research in AD.MethodsLiterature was retrieved from Web of Science and Scopus on July 8, 2025. CiteSpace...

Multimodal Deep Learning for Benign vs Malignant Eyelid Lesion Classification Using Optical Coherence Tomography and Clinical Images.

PURPOSE: To evaluate the performance of deep learning models using optical coherence tomography (OCT) volumes, clinical photographs, and their multimo...

An enhanced hypergraph CNN with adaptive focal loss for automated ECG heartbeat classification.

Deep learning techniques have shown significant promise for the automated diagnosis of CVD using ECG analysis. Nevertheless, several critical challeng...

Diagnosing morphology-vitality relationships through multifractal urban form metrics and explainable machine learning.

Understanding how urban morphology is associated with urban vitality is important for sustainable urban regeneration, yet conventional density-based i...

DADWMorph: A Global-Local Collaborative Network for Deformable Medical Image Registration.

Deformable image registration enables spatial alignment across sequential scans for longitudinal disease monitoring, multi-modal fusion in treatment p...

'Man vs. Machine: can ML algorithms diagnose headaches as accurately as clinicians? A systematic review.'.

BACKGROUND: Headache disorders are frequently misdiagnosed. We aimed to systematically evaluate the diagnostic accuracy, methodological quality, and c...

Metabolic Health is Highly Predictive of Chronic Pain Among Non-Obese Adults: Evidence from the NHANES and CHARLS Studies.

OBJECTIVE: To investigate the predictive value of the estimated glucose disposal rate (eGDR) for chronic pain (CP) and to evaluate its consistency as ...

Machine Learning Model Predicts Clinical Adverse Events of Small Molecule Kinase Inhibitors in Cancer Patients Using On-/Off-Target Engagement and Tissue Selectivity.

Adverse events (AEs) of small molecule kinase inhibitors (SMKIs) at therapeutic doses in cancer patients are largely unpredictable in phase I-III stud...

OCT-based optic neuropathy diagnosis using explainable and privacy-preserving machine learning.

Glaucoma shares similarities with neurodegenerative conditions like dementia, Parkinson's disease, and ischaemic optic neuropathy, which affect ocular...

Benchmarking Multi-Modal Artificial Intelligence Models Against Student Performance: The Role of Question Characteristics in Objective Structured Practical Dental Examinations.

BACKGROUND: Objective Structured Practical Dental Examinations (OSPDEs) are high-stakes assessments in dental education. This study compared the perfo...

Exploring osteoporosis risk in breast cancer patients after comprehensive treatment via explainable artificial intelligence algorithms.

BACKGROUND: Osteoporosis is a common complication among long-term breast cancer (BC) survivors. Assessment of osteoporosis risk of patients before the...

Classification of familial and non-familial ADHD using auto-encoding network and binary hypothesis testing.

Family heritage is one of the most powerful risk factors for attention-deficit/hyperactivity disorder (ADHD). Children with familial ADHD (ADHD-F) and...

Effects of peripheral nerve damage on promoting maladaptive plasticity in the spinal cord and brain.

Peripheral nerves can acquire damage through trauma, demyelinating diseases, inflammatory or immune-mediated insults, cancer, metabolic disorders, med...

A narrative review of the role of AI and machine learning in enhancing cauda equina syndrome diagnosis.

INTRODUCTION: Cauda Equina Syndrome (CES) is a neurological emergency requiring rapid diagnosis. Traditional diagnostic methods face challenges due to...

Cost-effectiveness of artificial intelligence interventions for musculoskeletal disorders of the spine: a systematic review.

Musculoskeletal disorders (MSDs) represent a substantial global health burden, and artificial intelligence (AI)-based technologies are emerging as pot...

Diagnostic value of machine-learning using conventional magnetic resonance imaging markers for pediatric idiopathic intracranial hypertension: a retrospective study.

BACKGROUND: Pediatric idiopathic intracranial hypertension can be challenging to diagnose; magnetic resonance imaging (MRI) signs are considered suppo...

Cerebrospinal fluid volume outperforms traditional measures for predicting treatment failure in infant hydrocephalus.

BACKGROUND: Endoscopic third ventriculostomy with choroid plexus cauterization (ETV/CPC) offers an alternative to shunt placement for infant hydroceph...

Enhancing crop yield prediction accuracy with a novel interpretable deep learning model: MHCNN-LSTM-MHA.

Accurate and reliable crop yield prediction before harvest is essential for informed decision-making, food security, resource optimization, climate ch...

Neural network modelling of proton RBE values at predominant survival fractions of in vitro data.

While a constant relative biological effectiveness (RBE) of 1.1 is applied in clinical proton therapy, longstanding clinical concern and in vitro evid...