Pain Management

Childhood Maltreatment and Risk for Illicit Substance Use: Evidence for Mid-Adolescence as a Sensitive Exposure Period

Childhood maltreatment is a well-established risk factor for substance misuse. However, it remains unclear whether risk for specific illicit substances is driven primarily by the cumulative burden of adverse experiences or by exposures during specific sensitive developmental periods. We administered the Maltreatment and Abuse Chronology of Exposure (MACE) scale to 2,013 medically healthy young adu...

Machine learning to phenotype pain and predict response to pain interventions among young adults with irritable bowel syndrome

Irritable bowel syndrome (IBS) is a prevalent disorder whose most debilitating symptom is pain. The complex, multifactorial nature of IBS pain leads to highly variable and often inadequate responses to self-management, underscoring the urgent need for personalized prediction models. This ancillary analysis of a randomized controlled trial (NCT03332537) utilized data from 80 young adults with IBS. ...

Neuromechanical Predictors of Clinical Scores of Balance and Functional Mobility in Chronic Stroke Survivors – A Machine Learning Approach

Clinical tests such as the Berg Balance Scale (BBS) and Timed Up and Go (TUG) are used to assess balance and functional mobility following stroke. The...

Lower pre-treatment TMS-evoked cortical reactivity and alpha-band oscillatory dynamics predict efficacy of primary motor cortex neuromodulation for chronic pain

Repetitive transcranial magnetic stimulation (rTMS) targeting the primary motor cortex (M1) provides significant pain relief in approximately 45% of p...

Agentic Generative Artificial Intelligence System for Classification of Pathology-Confirmed Primary Progressive Aphasia Variants

Accurate clinical and pathological diagnoses are essential in neurodegenerative diseases, especially given the emergence of pathology-specific disease...

Clinical Implementation of an AI Algorithm for Substance Misuse Screening in Hospitalized Adults

Manual inpatient screening for substance misuse is labor-intensive and inconsistently applied. Evaluation of artificial intelligence (AI)–assisted scr...

Enhancing Anterior Quadratus Lumborum Block Accuracy with Artificial Intelligence: A Segmentation Approach Evaluated by Dice Score Metrics

Anterior quadratus lumborum (QL) block is a regional anesthesia technique shown to provide both somatic and visceral pain relief by targeting lower th...

Arachnoiditis: Leveraging crowdsourcing and AI in a cross-sectional study of 1,105 cases to improve identification, understanding, and treatment

Arachnoiditis, a painful and potentially disabling neurological condition, results from persistent inflammation of the spinal cord pia-arachnoid membr...

Prevalence and Predictors of Silent Vertebral Compression Fractures: A Cross-Sectional Population-Based Study Using UK Biobank Imaging Data

To estimate the prevalence of silent vertebral compression fractures (VCF) in an asymptomatic population and to assess the demographic and clinical pr...

Characterize Disease Progression Subphenotypes in Real World Populations with Overweight and Obesity using a Graph-based Neural Network Framework

Obesity is a chronic, heterogeneous condition, with risks, trajectories, and treatment responses that vary widely among individuals. However, research...

Detecting Scoliosis at Scale Using Automated Cobb Angle Analysis in the UK Biobank

Adult degenerative scoliosis arises after skeletal maturity in an initially normal spine, primarily driven by age-related degeneration. The Cobb angle...

Comparing computable structured phenotype- versus large language model-identification of opioid use disorder using electronic health record data

Opioid use disorder (OUD) is common in emergency departments (EDs); identification via structured computable phenotypes may miss important clinical co...

Machine learning-driven prediction of opioid and stimulant-related drug overdose fatalities: Analysis of the potential fourth wave

Between 2010 and 2021, fentanyl and stimulants co-involved deaths increased from 0.6% to 32.3% of all overdose deaths in the U.S. The Centers for Dise...

Predicting Motor Trajectories and Mapping Progression Subtypes in Parkinson’s Disease via Structure–Function Neural Field Encoding and Multi-View Representation

Parkinson’s disease (PD) is characterized by substantial heterogeneity in progression patterns, posing major challenges for individualized prognosis a...

Heterogeneous epigenetic variation converges on splicing dysregulation in opioid addiction

Disease heterogeneity presents a major challenge for genetic and epigenetic dissection of complex traits. Neuropsychiatric traits, such as opioid use ...

Implementation of an Opioid Use Disorder (OUD) Machine-Learning Phenotype in Real-Time for the ADAPT Project

Develop and deploy a real-time, EHR-integrated machine learning phenotype to identify emergency department (ED) patients with opioid use disorder (OUD...

Machine learning augmented genome-wide meta-analysis of prescription opioid use in 860,000 individuals

Opioid analgesics are widely prescribed for pain, yet individuals vary markedly in their patterns of medical opioid use, influencing the risk of prolo...

Mapping research on ICT addiction: a comprehensive review of Internet, smartphone, social media, and gaming addictions.

INTRODUCTION: The use of information and communication technologies such as the Internet, smartphones, social media, and gaming has gained significant...

Effectiveness of digital self-care device for at risk drinking problems: focus on individuals at risk for alcohol-related issues.

AIMS: This study was conducted to verify the effectiveness of using digital self-care devices in reducing alcohol-related problems among high-risk alc...

Machine learning identifies genes linked to neurological disorders induced by equine encephalitis viruses, traumatic brain injuries, and organophosphorus nerve agents.

Venezuelan, eastern, and western equine encephalitis viruses (collectively referred to as equine encephalitis viruses---EEV) cause serious neurologica...