Pain Management

Latest AI and machine learning research in pain management for healthcare professionals.

10,891 articles
Stay Ahead - Weekly Pain Management research updates
Subscribe
Browse Categories
Showing 2601-2620 of 10,891 articles

Advancing the prediction and understanding of placebo responses in chronic back pain using large language models

Placebo analgesia in chronic pain is a widely studied clinical phenomenon, where expectations about the effectiveness of a treatment can result in substantial pain relief when using an inert treatment agent. While placebos offer an opportunity for non-pharmacological treatment in chronic pain, not everyone demonstrates an analgesic response. Prior research has identified biopsychosocial factors th...

Data-Driven Insights on Opioid Use and Health Behavior Trends Following Decriminalization: Zero-Shot Sentiment and Behavior Analysis

Opioid decriminalization has taken on renewed urgency in regions grappling with high mortality and health-care costs. Traditional assessments often focus on legal or epidemiological data, leaving gaps in understanding how the public actually perceives and reacts to such policies. This paper introduces an AI-driven approach that applies Mistral, a Large Language Model (LLM), to a corpus of over 22,...

LLM-Guided Pain Management: Examining Socio-Demographic Gaps in Cancer vs non-Cancer cases

Large language models (LLMs) offer potential benefits in clinical care. However, concerns remain regarding socio-demographic biases embedded in their ...

Unmet Needs in Acute Hepatic Porphyria Diagnosis: A Comparative Big Data Analysis of an AI-based Human-in-the-Loop Screening Versus Standard of Care

Acute Hepatic Porphyria (AHP) is a rare genetic disease characterized by unpredictable life-threatening attacks. There is no reliable biochemical scre...

Machine learning-based calculation of neurovascular compression surface area correlates with post-microvascular decompression pain outcomes for trigeminal neuralgia

Machine learning-generated segmentations of the trigeminal nerve and nearby blood vessels have the potential to quantify the magnitude of neurovascula...

Suitability of just-in-time adaptive intervention in post-COVID-19-related symptoms: A systematic scoping review

Patients with post-COVID-19-related symptoms require active and timely support in self-management. Just-in-time adaptive interventions (JITAI) seem pr...

A CNN Autoencoder for Learning Latent Disc Geometry from Segmented Lumbar Spine MRI

Low back pain is the world’s leading cause of disability and pathology of the lumbar intervertebral discs is frequently considered a driver of pain. T...

Robust radiomic signatures of intervertebral disc degeneration from MRI

Low back pain (LBP) is the most common musculoskeletal symptom worldwide and intervertebral disc (IVD) degeneration is an important contributing facto...

Epigenetic signatures of regional tau pathology and cognition in the aging and pathological brain

Primary age-related tauopathy (PART) and Alzheimer’s disease (AD) share hippocampal phospho-tau (p-tau) pathology but differ in ß-amyloid burden and d...

AI-MI: A Deep Learning Model to Predict Actionable Acute Coronary Syndrome Using 12-Lead ECGs

Chest pain is among the most common chief complaints in Emergency Departments (EDs), and differentiating acute coronary syndrome from low-risk chest p...

A comparative analysis of dengue, chikungunya, and Zika in a pediatric cohort over 18 years

Dengue, chikungunya, and Zika are diseases of major human concern. Differential diagnosis is complicated in children and adolescents by their overlapp...

AI Implementation in U.S. Healthcare and Its Association With Elder Mortality and Quality of Care

Hospitals are increasingly adopting artificial intelligence (AI) tools in clinical care. However, their overall impact on the health of older adults r...

Segmentation of clinical imagery for improved epidural stimulation to address spinal cord injury

Spinal cord injury (SCI) can severely impair motor and autonomic function, with long-term consequences for quality of life. Epidural stimulation has e...

Machine Learning-Based Identification of Sickle Cell Disease Subphenotypes in Clinical Trial Data

Sickle Cell Disease (SCD) is a rare autosomal recessive disorder caused by a point mutation producing abnormal hemoglobin S, leading to deformed red b...

Development of Machine Learning Algorithms Using EEG Data to Detect the Presence of Chronic Pain

Chronic pain impacts more than one in five adults in the United States (US) and the costs associated with the condition amount to hundreds of billions...

Completeness and Quality of Neurology Referral Letters Generated by a Large Language Model for Standardized Scenarios

Large Language Models (LLMs) offer promising applications in healthcare, including drafting referral letters. However, access to LLMs specifically des...

Justifying model complexity: evaluating transfer learning against classical models for intraoperative nociception monitoring under anesthesia

Accurate intraoperative detection of nociceptive events is essential for optimizing analgesic administration and improving postoperative outcomes. Whi...

Artificial Intelligence for Predicting Treatment Adherence in Opioid Use Disorder: A Scoping Review

Opioid use disorder (OUD) is a chronic condition in which an individual engages in the persistent use of opioids that causes significant distress and ...

Neuroinflammation distinguishes HLA haplotypes in progressive supranuclear palsy

Progressive supranuclear palsy (PSP) is a neurodegenerative 4R tauopathy clinically presenting with atypical parkinsonism or cognitive behavioral chan...

Machine learning models to detect opioid misuse in Emergency Department patients at triage

Emergency department (ED) encounters represent valuable opportunities to initiate evidence-based treatments for patients with opioid misuse, but few r...

Browse Categories