Pain Management

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

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Physicochemical stability of binary admixtures of paracetamol and dexketoprofen-trometamol for patient-controlled analgesia use.

BACKGROUND: Intravenous admixtures of dexketoprofen-trometamol and paracetamol are frequently used i...

Detecting Opioid-Related Aberrant Behavior using Natural Language Processing.

The United States is in the midst of a prescription opioid epidemic, with the number of yearly opioi...

The Dependence of Machine Learning on Electronic Medical Record Quality.

There is growing interest in applying machine learning methods to Electronic Medical Records (EMR). ...

Deep Learning Solutions for Classifying Patients on Opioid Use.

Opioid analgesics, as commonly prescribed medications used for relieving pain in patients, are espec...

Complex analyses on clinical information systems using restricted natural language querying to resolve time-event dependencies.

PURPOSE: This paper reports on a generic framework to provide clinicians with the ability to conduct...

Comparison of Natural Language Processing Rules-based and Machine-learning Systems to Identify Lumbar Spine Imaging Findings Related to Low Back Pain.

RATIONALE AND OBJECTIVES: To evaluate a natural language processing (NLP) system built with open-sou...

Bioactive polymeric formulations for wound healing.

Ricinoleic acid (RA) has potential to promote wound healing because of its analgesic and anti-inflam...

A hybrid model based on neural networks for biomedical relation extraction.

Biomedical relation extraction can automatically extract high-quality biomedical relations from biom...

High-Order Convolutional Neural Network Architecture for Predicting DNA-Protein Binding Sites.

Although Deep learning algorithms have outperformed conventional methods in predicting the sequence ...

Successful bystander-administered intranasal naloxone reversal of opioid overdose between two veterans: A case report.

Opioid overdose-related morbidity and mortality remain one of the most pressing public health crises...

Ongoing brain rhythms shape I-wave properties in a computational model.

BACKGROUND: Responses to transcranial magnetic stimulation (TMS) are notoriously variable. Previous ...

Thalamocortical dysrhythmia detected by machine learning.

Thalamocortical dysrhythmia (TCD) is a model proposed to explain divergent neurological disorders. I...

Electroencephalographic derived network differences in Lewy body dementia compared to Alzheimer's disease patients.

Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) require differential management despite...

A convolutional neural network to filter artifacts in spectroscopic MRI.

PURPOSE: Proton MRSI is a noninvasive modality capable of generating volumetric maps of in vivo tiss...

Dependency-based Siamese long short-term memory network for learning sentence representations.

Textual representations play an important role in the field of natural language processing (NLP). Th...

A novel triterpenoid 16-hydroxy betulinic acid isolated from attributes multi-faced pharmacological activities.

The aerial parts of extensively used ethnomedicinal plant (Burm. f.) Robinson growing wild in Bangl...

Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

PURPOSE: To assess the performance of a deep learning algorithm for detecting referable glaucomatous...

Personalized prediction of drug efficacy for diabetes treatment via patient-level sequential modeling with neural networks.

Patients with type 2 diabetes mellitus are generally under continuous long-term medical treatment ba...

A cooperation of catheters and guidewires-based novel remote-controlled vascular interventional robot.

Remote-controlled vascular interventional robots (RVIRs) are being developed to increase the overall...

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