Pain Management

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

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DyGraphformer: Transformer combining dynamic spatio-temporal graph network for multivariate time series forecasting.

Transformer-based models demonstrate tremendous potential for Multivariate Time Series (MTS) forecas...

Amaurosis after Inferior Alveolar Nerve Block Injection in a Seven-Year-Old Girl: A Case Report and Review of the Literature.

A seven-year-old girl was referred for the treatment of her primary teeth. An inferior alveolar nerv...

Developing a Wearable Sensor-Based Digital Biomarker of Opioid Dependence.

BACKGROUND: Repeated opioid exposure leads to a variety of physiologic adaptations that develop at d...

Spatial patterns of rural opioid-related hospital emergency department visits: A machine learning analysis.

As opioid-related overdose emergency department visits continue to rise in the United States, there ...

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, exp...

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...

TransC-ac4C: Identification of N4-Acetylcytidine (ac4C) Sites in mRNA Using Deep Learning.

N4-acetylcytidine (ac4C) is a post-transcriptional modification in mRNA that is critical in mRNA tra...

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...

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 strok...

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...

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 eff...

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 t...

Muscle Fat and Volume Differences in People With Hip-Related Pain Compared With Controls: A Machine Learning Approach.

BACKGROUND: Hip-related pain (HRP) affects young to middle-aged active adults and impacts physical a...

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 ...

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 t...

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 odonto...

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 d...

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, ther...

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...

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 ...

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

Most operant conditioning circuits predominantly focus on simple feedback process, few studies consi...

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