Pain Management

Haves and have-nots: socioeconomic position improves accuracy of machine learning algorithms for predicting high-impact chronic pain.

Lower socioeconomic position (SEP) is associated with increased risk of developing chronic pain, experiencing more severe pain, and suffering greater pain-related disability. However, SEP is a multidimensional construct; there is a dearth of research on which SEP features are most strongly associated with high-impact chronic pain, the relative importance of SEP predictive features compared to esta...

Role of Artificial intelligence model in prediction of low back pain using T2 weighted MRI of Lumbar spine.

BACKGROUND: Low back pain (LBP), the primary cause of disability, is the most common musculoskeletal disorder globally and the primary cause of disability. Magnetic resonance imaging (MRI) studies are inconclusive and less sensitive for identifying and classifying patients with LBP. Hence, this study aimed to investigate the role of artificial intelligence (AI) models in the prediction of LBP usin...

Lumbar Radicular Pain in the Eyes of Artificial Intelligence: Can You 'Imagine' What I 'Feel'?

OBJECTIVE: Pain is a complex sensory and emotional experience that significantly impacts individuals' well-being. Lumbar radicular pain (LRP) is a pre...

Effects of end-effector robotic arm reach training with functional electrical stimulation for chronic stroke survivors.

BACKGROUND: Upper-extremity dysfunction significantly affects dependence in the daily lives of stroke survivors, limiting their participation in the s...

Developing and Validating a Multimodal Dataset for Neonatal Pain Assessment to Improve AI Algorithms With Clinical Data.

BACKGROUND: Using Artificial Intelligence (AI) for neonatal pain assessment has great potential, but its effectiveness depends on accurate data labeli...

Machine learning and biological validation identify sphingolipids as potential mediators of paclitaxel-induced neuropathy in cancer patients.

BACKGROUND: Chemotherapy-induced peripheral neuropathy (CIPN) is a serious therapy-limiting side effect of commonly used anticancer drugs. Previous st...

Transforming personalized chronic pain management with artificial intelligence: A commentary on the current landscape and future directions.

Artificial intelligence (AI) has the potential to revolutionize chronic pain management by guiding the development of effective treatment strategies t...

Pain Assessment for Patients with Dementia and Communication Impairment: Feasibility Study of the Usage of Artificial Intelligence-Enabled Wearables.

BACKGROUND: Recent studies on machine learning have shown the potential to provide new methods with which to assess pain through the measurement of si...

HiMul-LGG: A hierarchical decision fusion-based local-global graph neural network for multimodal emotion recognition in conversation.

Emotion recognition in conversation (ERC) is a vital task that requires deciphering human emotions through analysis of contextual and multimodal infor...

PAINe: An Artificial Intelligence-based Virtual Assistant to Aid in the Differentiation of Pain of Odontogenic versus Temporomandibular Origin.

INTRODUCTION: Pain associated with temporomandibular dysfunction (TMD) is often confused with odontogenic pain, which is a challenge in endodontic dia...

A deep learning framework combining molecular image and protein structural representations identifies candidate drugs for pain.

Artificial intelligence (AI) and deep learning technologies hold promise for identifying effective drugs for human diseases, including pain. Here, we ...

An Experimental and Clinical Physiological Signal Dataset for Automated Pain Recognition.

Access to large amounts of data is essential for successful machine learning research. However, there is insufficient data for many applications, as d...

Factors predicting access to medications for opioid use disorder for housed and unhoused patients: A machine learning approach.

BACKGROUND: Opioid use disorder (OUD) is a growing public health crisis, with opioids involved in an overwhelming majority of drug overdose deaths in ...

An improved algorithm for salient object detection of microscope based on U-Net.

With the rapid advancement of modern medical technology, microscopy imaging systems have become one of the key technologies in medical image analysis....

Operant Conditioning Neuromorphic Circuit With Addictiveness and Time Memory for Automatic Learning.

Most operant conditioning circuits predominantly focus on simple feedback process, few studies consider the intricacies of feedback outcomes and the u...

Automatic Segmentation of Ultrasound-Guided Quadratus Lumborum Blocks Based on Artificial Intelligence.

Ultrasound-guided quadratus lumborum block (QLB) technology has become a widely used perioperative analgesia method during abdominal and pelvic surger...

Machine learning in the diagnosis, management, and care of patients with low back pain: a scoping review of the literature and future directions.

BACKGROUND CONTEXT: Low back pain (LBP) remains the leading cause of disability globally. In recent years, machine learning (ML) has emerged as a pote...

Continuous Short-Term Pain Assessment in Temporomandibular Joint Therapy Using LSTM Models Supported by Heat-Induced Pain Data Patterns.

This study aims to design a time-continuous pain level assessment system for temporomandibular joint therapy. Our objectives cover verifying literatur...

AI-based lumbar central canal stenosis classification on sagittal MR images is comparable to experienced radiologists using axial images.

OBJECTIVES: The assessment of lumbar central canal stenosis (LCCS) is crucial for diagnosing and planning treatment for patients with low back pain an...

Application Value of a Machine Learning Model in Predicting Mild Depression Associated with Migraine without Aura.

To investigate the application value of a machine learning model in predicting mild depression associated with migraine without aura (MwoA). 178 pat...