Pain Management

Enhanced phenotypes for identifying opioid overdose in emergency department visit electronic health record data.

BACKGROUND: Accurate identification of opioid overdose (OOD) cases in electronic healthcare record (EHR) data is an important element in surveillance, empirical research, and clinical intervention. We sought to improve existing OOD electronic phenotypes by incorporating new data types beyond diagnostic codes and by applying several statistical and machine learning methods.

CIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning.

The endocannabinoid system, which includes cannabinoid receptor 1 and 2 subtypes (CBR and CBR, respectively), is responsible for the onset of various pathologies including neurodegeneration, cancer, neuropathic and inflammatory pain, obesity, and inflammatory bowel disease. Given the high similarity of CBR and CBR, generating subtype-selective ligands is still an open challenge. In this work, the ...

Deep learning for video-based automated pain recognition in rabbits.

Despite the wide range of uses of rabbits (Oryctolagus cuniculus) as experimental models for pain, as well as their increasing popularity as pets, pai...

Design and Evaluation of Deep Learning Models for Continuous Acute Pain Detection Based on Phasic Electrodermal Activity.

The current method for assessing pain in clinical practice is subjective and relies on self-reported scales. An objective and accurate method of pain ...

H2Former: An Efficient Hierarchical Hybrid Transformer for Medical Image Segmentation.

Accurate medical image segmentation is of great significance for computer aided diagnosis. Although methods based on convolutional neural networks (CN...

Mouth-Opener Technique for Ultrasound-Guided Inferior Alveolar Nerve Block: A Case Series of Extraction of Impacted Mandibular Third Molars.

Extraction of the impacted mandibular third molar (IMTM) is common in oral surgery, but its postoperative pain is severe. Ultrasound-guided inferior a...

Multiobjective Molecular Optimization for Opioid Use Disorder Treatment Using Generative Network Complex.

Opioid use disorder (OUD) has emerged as a significant global public health issue, necessitating the discovery of new medications. In this study, we p...

A longitudinal observational study on the epidemiology of painful procedures and sucrose administration in hospitalized preterm neonates.

Although sucrose is widely administered to hospitalized infants for single painful procedures, total sucrose volume during the entire neonatal intensi...

Analgesia quality index improves the quality of postoperative pain management: a retrospective observational study of 14,747 patients between 2014 and 2021.

BACKGROUND: The application of artificial intelligence patient-controlled analgesia (AI-PCA) facilitates the remote monitoring of analgesia management...

De Novo Design of κ-Opioid Receptor Antagonists Using a Generative Deep-Learning Framework.

Likely effective pharmacological interventions for the treatment of opioid addiction include attempts to attenuate brain reward deficits during period...

Evaluating the performance of large language models: ChatGPT and Google Bard in generating differential diagnoses in clinicopathological conferences of neurodegenerative disorders.

This study explores the utility of the large language models (LLMs), specifically ChatGPT and Google Bard, in predicting neuropathologic diagnoses fro...

Developing and deploying deep learning models in brain magnetic resonance imaging: A review.

Magnetic resonance imaging (MRI) of the brain has benefited from deep learning (DL) to alleviate the burden on radiologists and MR technologists, and ...

Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies.

The objective of this study is to evaluate the efficacy of deep learning (DL) techniques in improving the quality of diffusion MRI (dMRI) data in clin...

Probing the molecular mechanisms of α-synuclein inhibitors unveils promising natural candidates through machine-learning QSAR, pharmacophore modeling, and molecular dynamics simulations.

Parkinson's disease is characterized by a multifactorial nature that is linked to different pathways. Among them, the abnormal deposition and accumula...

Clinical relevance of deep learning models in predicting the onset timing of cancer pain exacerbation.

Cancer pain is a challenging clinical problem that is encountered in the management of cancer pain. We aimed to investigate the clinical relevance of ...

Stratification of diabetes in the context of comorbidities, using representation learning and topological data analysis.

Diabetes is a heterogenous, multimorbid disorder with a large variation in manifestations, trajectories, and outcomes. The aim of this study is to val...

External validation of machine learning algorithm predicting prolonged opioid prescriptions in opioid-naïve lumbar spine surgery patients using a Taiwanese cohort.

BACKGROUND/PURPOSE: Identifying patients at risk of prolonged opioid use after surgery prompts appropriate prescription and personalized treatment pla...

Lumbar Spinal Canal Segmentation in Cases with Lumbar Stenosis Using Deep-U-Net Ensembles.

BACKGROUND: Narrowing of the lumbar spinal canal, or lumbar stenosis (LS), may cause debilitating radicular pain or muscle weakness. It is the most fr...

[Application possibilities of digital tools in postoperative pain therapy].

BACKGROUND: Recently, digital tools, such as smartphone-based applications and the use of artificial intelligence have increasingly found their way in...

Brain imaging signatures of neuropathic facial pain derived by artificial intelligence.

Advances in neuroimaging have permitted the non-invasive examination of the human brain in pain. However, a persisting challenge is in the objective d...