Pain Management

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

8,765 articles
Stay Ahead - Weekly Pain Management research updates
Subscribe
Browse Specialties
Showing 778-798 of 8,765 articles
Differentiating Glaucomatous Optic Neuropathy From Non-glaucomatous Optic Neuropathies Using Deep Learning Algorithms.

PURPOSE: A deep learning framework to differentiate glaucomatous optic disc changes due to glaucomat...

Evaluation of a deep learning-based reconstruction method for denoising and image enhancement of shoulder MRI in patients with shoulder pain.

OBJECTIVES: To evaluate the diagnostic performance of an automated reconstruction algorithm combinin...

The Clinical Suitability of an Artificial Intelligence-Enabled Pain Assessment Tool for Use in Infants: Feasibility and Usability Evaluation Study.

BACKGROUND: Infants are unable to self-report their pain, which, therefore, often goes underrecogniz...

Explainable Artificial Intelligence (XAI) in Pain Research: Understanding the Role of Electrodermal Activity for Automated Pain Recognition.

Artificial intelligence and especially deep learning methods have achieved outstanding results for v...

Automatic assessment of pain based on deep learning methods: A systematic review.

BACKGROUND AND OBJECTIVE: The automatic assessment of pain is vital in designing optimal pain manage...

Spatiotemporal analysis of speckle dynamics to track invisible needle in ultrasound sequences using convolutional neural networks: a phantom study.

PURPOSE: Accurate needle placement into the target point is critical for ultrasound interventions li...

Expectile Neural Networks for Genetic Data Analysis of Complex Diseases.

The genetic etiologies of common diseases are highly complex and heterogeneous. Classic methods, suc...

Knowledge Guided Attention and Graph Convolutional Networks for Chemical-Disease Relation Extraction.

The automatic extraction of the chemical-disease relation (CDR) from the text becomes critical becau...

MRI brain tumor segmentation using residual Spatial Pyramid Pooling-powered 3D U-Net.

Brain tumor diagnosis has been a lengthy process, and automation of a process such as brain tumor se...

Deep Learning System Outperforms Clinicians in Identifying Optic Disc Abnormalities.

BACKGROUND: The examination of the optic nerve head (optic disc) is mandatory in patients with heada...

Explainable deep learning for insights in El Niño and river flows.

The El Niño Southern Oscillation (ENSO) is a semi-periodic fluctuation in sea surface temperature (S...

State-of-the-art Applications of Patient-Reported Outcome Measures in Spinal Care.

Patient-reported outcome measures (PROMs) assign objective measures to patient's subjective experien...

Deep Learning Analysis of Chest Radiographs to Triage Patients with Acute Chest Pain Syndrome.

Background Patients presenting to the emergency department (ED) with acute chest pain (ACP) syndrome...

A hybrid deep learning model for regional O and NO concentrations prediction based on spatiotemporal dependencies in air quality monitoring network.

Short-term prediction of urban air quality is critical to pollution management and public health. Ho...

Automated multi-modal Transformer network (AMTNet) for 3D medical images segmentation.

Over the past years, convolutional neural networks based methods have dominated the field of medical...

Predicting decompression surgery by applying multimodal deep learning to patients' structured and unstructured health data.

BACKGROUND: Low back pain (LBP) is a common condition made up of a variety of anatomic and clinical ...

Robotic Simulators for Tissue Examination Training With Multimodal Sensory Feedback.

Tissue examination by hand remains an essential technique in clinical practice. The effective applic...

Research progress on the structure and biological diversities of 2-phenylindole derivatives in recent 20 years.

The privileged structure binds to multiple receptors with high affinity, which is helpful to the dev...

A deep learning method to detect opioid prescription and opioid use disorder from electronic health records.

OBJECTIVE: As the opioid epidemic continues across the United States, methods are needed to accurate...

Browse Specialties