Pain Management

Investigating the temporal dynamics of electroencephalogram (EEG) microstates using recurrent neural networks.

Electroencephalogram (EEG) microstates that represent quasi-stable, global neuronal activity are considered as the building blocks of brain dynamics. Therefore, the analysis of microstate sequences is a promising approach to understand fast brain dynamics that underlie various mental processes. Recent studies suggest that EEG microstate sequences are non-Markovian and nonstationary, highlighting t...

Initial classification of low back and leg pain based on objective functional testing: a pilot study of machine learning applied to diagnostics.

OBJECTIVE: The five-repetition sit-to-stand (5R-STS) test was designed to capture objective functional impairment and thus provided an adjunctive dimension in patient assessment. The clinical interpretability and confounders of the 5R-STS remain poorly understood. In clinical use, it became apparent that 5R-STS performance may differ between patients with lumbar disk herniation (LDH), lumbar spina...

Intravenous Lignocaine-Fentanyl Versus Epidural Ropivacaine-Fentanyl for Postoperative Analgesia After Major Abdominal Oncosurgery: A Pilot Prospective Randomised Study.

OBJECTIVE: Epidural injection of local anaesthetics and intravenous opioid injection are two common analgesic strategies following major abdominal onc...

Assessment of knee pain from MR imaging using a convolutional Siamese network.

OBJECTIVES: It remains difficult to characterize the source of pain in knee joints either using radiographs or magnetic resonance imaging (MRI). We so...

On the localness modeling for the self-attention based end-to-end speech synthesis.

Attention based end-to-end speech synthesis achieves better performance in both prosody and quality compared to the conventional "front-end"-"back-end...

The Prediction of Human Abdominal Adiposity Based on the Combination of a Particle Swarm Algorithm and Support Vector Machine.

: Abdominal adiposity is an important risk factor of chronic cardiovascular diseases, thus the prediction of abdominal adiposity and obesity can reduc...

Machine-learned identification of psychological subgroups with relation to pain interference in patients after breast cancer treatments.

BACKGROUND: Persistent pain in breast cancer survivors is common. Psychological and sleep-related factors modulate perception, interpretation and copi...

Continuous Pain Assessment Using Ensemble Feature Selection from Wearable Sensor Data.

Sickle cell disease (SCD) is a red blood cell disorder complicated by lifelong issues with pain. Management of SCD related pain is particularly challe...

Estimation of absolute states of human skeletal muscle via standard B-mode ultrasound imaging and deep convolutional neural networks.

The objective is to test automated estimation of active and passive skeletal muscle states using ultrasonic imaging. Current technology (electromyogr...

Automatic detection of rare pathologies in fundus photographs using few-shot learning.

In the last decades, large datasets of fundus photographs have been collected in diabetic retinopathy (DR) screening networks. Through deep learning, ...

Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs.

PURPOSE: To develop a deep learning approach based on deep residual neural network (ResNet101) for the automated detection of glaucomatous optic neuro...

Understanding Opioid Use Disorder (OUD) using tree-based classifiers.

BACKGROUND: Opioid Use Disorder (OUD), defined as a physical or psychological reliance on opioids, is a public health epidemic. Identifying adults lik...

Letter to the Editor regarding the article "Comparison of intra- and postoperative analgesia and pain perception in robot-assisted vs. open radical prostatectomy".

Rapid Assessment of Opioid Exposure and Treatment in Cities Through Robotic Collection and Chemical Analysis of Wastewater.

INTRODUCTION: Accurate data regarding opioid use, overdose, and treatment is important in guiding community efforts at combating the opioid epidemic. ...

Prevalence and Diagnosis of Neurological Disorders Using Different Deep Learning Techniques: A Meta-Analysis.

This paper dispenses an exhaustive review on deep learning techniques used in the prognosis of eight different neuropsychiatric and neurological disor...

The Detection of Opioid Misuse and Heroin Use From Paramedic Response Documentation: Machine Learning for Improved Surveillance.

BACKGROUND: Timely, precise, and localized surveillance of nonfatal events is needed to improve response and prevention of opioid-related problems in ...

Gait Biomarkers Classification by Combining Assembled Algorithms and Deep Learning: Results of a Local Study.

Machine learning, one of the core disciplines of artificial intelligence, is an approach whose main emphasis is analytical model building. In other wo...

Structured sequence processing and combinatorial binding: neurobiologically and computationally informed hypotheses.

Understanding how the brain forms representations of structured information distributed in time is a challenging endeavour for the neuroscientific com...

Ultrasound-Guided Subclavian Perivascular Brachial Plexus Block Using 0.5% Bupivacaine with Dexmedetomidine as an Adjuvant: A Prospective Randomized Controlled Trial.

BACKGROUND: Ultrasound guidance has dramatically improved the accuracy of nerve localization, and various adjuvants prolong the block and extend analg...

Comparison of Continuous Wound Infusion versus Continuous Epidural Infusion in Upper Abdominal Surgery: Noninferiority Randomized Controlled Trial.

CONTEXT: Wound catheter offers a less invasive alternative for postoperative analgesia in the abdominal surgery.