Pain Management

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

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Artificial intelligence (AI) impacting diagnosis of glaucoma and understanding the regulatory aspects of AI-based software as medical device.

Glaucoma, the group of eye diseases is characterized by increased intraocular pressure, optic neurop...

Distant Supervision Relation Extraction via adaptive dependency-path and additional knowledge graph supervision.

Relation Extraction systems train an extractor by aligning relation instances in Knowledge Base with...

Machine-Learning and Chemicogenomics Approach Defines and Predicts Cross-Talk of Hippo and MAPK Pathways.

Hippo pathway dysregulation occurs in multiple cancers through genetic and nongenetic alterations, r...

Comparison of analgesia and akinesia between sub-Tenon's capsule anesthesia and trans-Tenon's capsule retrobulbar anesthesia in vitrectomy.

OBJECTIVES: We compared the effects of sub-Tenon's capsule anesthesia (STA) and trans-Tenon's capsul...

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

BACKGROUND: Poorly managed pain can lead to substance use disorders, depression, suicide, worsening ...

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 pr...

Interpretation of cluster structures in pain-related phenotype data using explainable artificial intelligence (XAI).

BACKGROUND: In pain research and clinics, it is common practice to subgroup subjects according to sh...

Prediction of cancer dependencies from expression data using deep learning.

Detecting cancer dependencies is key to disease treatment. Recent efforts have mapped gene dependenc...

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 orig...

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 i...

Discrimination of alcohol dependence based on the convolutional neural network.

In this paper, a total of 20 sites of single nucleotide polymorphisms (SNPs) on the serotonin 3 rece...

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 neuropath...

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 20...

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...

Predicting alcohol dependence from multi-site brain structural measures.

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance im...

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 Alzhe...

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 ro...

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 erythe...

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 ...

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