Latest AI and machine learning research in back pain for healthcare professionals.
INTRODUCTION: Nonmedical use of prescription medications/drugs (NMUPD) is a serious public health threat, particularly in relation to the prescription opioid analgesics abuse epidemic. While attention to this problem has been growing, there remains an urgent need to develop novel strategies in the field of "digital epidemiology" to better identify, analyze and understand trends in NMUPD behavior.
OBJECTIVES: A once-daily, extended-release hydrocodone bitartrate tablet with abuse-deterrent properties (Hysingla ER® [HYD]) is available for the treatment of chronic pain in appropriate patients. This study evaluated the intranasal abuse potential and pharmacokinetics of HYD coarse and fine particles vs hydrocodone powder or placebo.
BACKGROUND: Opioids are used for the treatment of pain. However, 30-50% of patients have insufficient effect to the opioid initially selected by the p...
Feature selection is a critical step in electronic health record (EHR)-based predictive modeling, where input variables are often high-dimensional, sp...
Validated measures of pain catastrophizing primarily assess catastrophizing as a stable trait. However, emerging evidence suggests catastrophizing flu...
Generative artificial intelligence (AI) has emerged as a powerful framework for drug discovery, yet most current approaches follow one-drug-one-gene t...
Exogenous opioids that activate mu-opioid receptors (MORs) in nociceptive circuits mediate transient pain relief lasting minutes to hours but have mor...
Background Machine learning (ML) models are increasingly used to predict adverse outcomes after surgery. However, most rely on static patient characte...
Objective: Stigmatizing language in the electronic health record (EHR) has been associated with adverse patient experience in substance use disorder c...
Background: Large language models (LLMs) are increasingly used in medical education and clinical decision-making, but their reliability in high-risk m...
Opioid addiction is characterized by escalating drug use, driven in part by negative reinforcement from withdrawal, but the neural processes linking w...
High inpatient opioid exposure is associated with increased risk of persistent opioid use. Early identification of high-risk patients may improve opio...
The identification of suitable lead molecules in the vast chemical space is a critical and challenging task in drug discovery campaigns. Recently, it ...
The opioid crisis has severely impacted Ohio, with overdose death rates surpassing national averages and disproportionately affecting rural and Appala...
Background Personalized medicine promises to tailor treatments to the individual, but it carries a hidden risk: mistaking statistical noise for action...
Background: Australian health practitioners are regulated under the Health Practitioner Regulation National Law, with serious conduct matters referred...
Large language models (LLMs) are increasingly used for qualitative analysis in substance use research, yet their performance relative to human coders ...
The opioid epidemic continues to ravage communities worldwide, straining healthcare systems, disrupting families, and demanding urgent computational s...
Genome-wide association studies of physical activity traits have mapped numerous loci, yet the molecular mechanisms through which exercise influences ...
Nutritional interventions are important for managing chronic health conditions, but current computational methods provide limited support for personal...