Pain Management

Automated Smart Home Assessment to Support Pain Management: Multiple Methods Analysis.

BACKGROUND: Poorly managed pain can lead to substance use disorders, depression, suicide, worsening health, and increased use of health services. Most pain assessments occur in clinical settings away from patients' natural environments. Advances in smart home technology may allow observation of pain in the home setting. Smart homes recognizing human behaviors may be useful for quantifying function...

Plasma Concentrations of Pro-inflammatory Cytokine IL-6 and Antiinflammatory Cytokine IL-10 in Short- and Long-term Opioid Users with Noncancer Pain.

INTRODUCTION: Little is known whether the duration of opioid use influences the concentrations of pro- and anti-inflammatory cytokines.

Prediction of cancer dependencies from expression data using deep learning.

Detecting cancer dependencies is key to disease treatment. Recent efforts have mapped gene dependencies and drug sensitivities in hundreds of cancer c...

Analysis of 17 fentanyls in plasma and blood by UPLC-MS/MS with interpretation of findings in surgical and postmortem casework.

The opioid crisis is linked to an increased misuse of fentanyl as well as fentanyl analogs that originate from the illicit drug market. Much of our cu...

Designing individual-specific and trial-specific models to accurately predict the intensity of nociceptive pain from single-trial fMRI responses.

Using machine learning to predict the intensity of pain from fMRI has attracted rapidly increasing interests. However, due to remarkable inter- and in...

Predicting Diabetic Neuropathy Risk Level Using Artificial Neural Network and Clinical Parameters of Subjects With Diabetes.

BACKGROUND: A risk assessment tool has been developed for automated estimation of level of neuropathy based on the clinical characteristics of patient...

Efficacy of bilateral erector spinae block for post-operative analgesia in liver hydatid surgery.

BACKGROUND: Erector spinae plane (ESP) block is a recently described interfacial block, and since 2016, studies have shown that it is a safe technique...

CS-Net: Deep learning segmentation of curvilinear structures in medical imaging.

Automated detection of curvilinear structures, e.g., blood vessels or nerve fibres, from medical and biomedical images is a crucial early step in auto...

Predicting alcohol dependence from multi-site brain structural measures.

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification ...

Prediction of 7-year's conversion from subjective cognitive decline to mild cognitive impairment.

Subjective cognitive decline (SCD) is a high-risk yet less understood status before developing Alzheimer's disease (AD). This work included 76 SCD ind...

Effects of nerve-sparing procedures on bowel function after robot-assisted radical prostatectomy: A longitudinal study.

BACKGROUND: This study aimed to evaluate rectal pain and bowel function of the patients following robot-assisted radical prostatectomy (RARP).

Clinical predictive modelling of post-surgical recovery in individuals with cervical radiculopathy: a machine learning approach.

Prognostic models play an important role in the clinical management of cervical radiculopathy (CR). No study has compared the performance of modern ma...

Comparative study between deep learning and QSAR classifications for TNBC inhibitors and novel GPCR agonist discovery.

Machine learning is a well-known approach for virtual screening. Recently, deep learning, a machine learning algorithm in artificial neural networks, ...

Facial erythema detects diabetic neuropathy using the fusion of machine learning, random matrix theory and self organized criticality.

Rubeosis faciei diabeticorum, caused by microangiopathy and characterized by a chronic facial erythema, is associated with diabetic neuropathy. In cli...

Investigating Pain-Related Avoidance Behavior using a Robotic Arm-Reaching Paradigm.

Avoidance behavior is a key contributor to the transition from acute pain to chronic pain disability. Yet, there has been a lack of ecologically valid...

Artificial intelligence interventions focused on opioid use disorders: A review of the gray literature.

BACKGROUND: With the artificial intelligence (AI) paradigm shift comes momentum toward the development and scale-up of novel AI interventions to aid i...

Effectiveness of Radiofrequency Ablation in the Treatment of Painful Osseous Metastases: A Correlation Meta-Analysis with Machine Learning Cluster Identification.

A systematic review and meta-analysis of pain response after radiofrequency (RF) ablation over time for osseous metastases was conducted in 2019. Anal...

Development and Validation of Machine Learning-Based Prediction for Dependence in the Activities of Daily Living after Stroke Inpatient Rehabilitation: A Decision-Tree Analysis.

BACKGROUND AND PURPOSE: Accurate prediction using simple and changeable variables is clinically meaningful because some known-predictors, such as stro...

The effect of a social robot intervention on sleep and motor activity of people living with dementia and chronic pain: A pilot randomized controlled trial.

OBJECTIVE: To investigate the effect of a social robot intervention on sleep and motor activity in nursing home residents living with dementia and chr...

Deep learning for automated glaucomatous optic neuropathy detection from ultra-widefield fundus images.

BACKGROUND/AIMS: To develop a deep learning system for automated glaucomatous optic neuropathy (GON) detection using ultra-widefield fundus (UWF) imag...