Pain Management

Automatic Segmentation of Ultrasound-Guided Quadratus Lumborum Blocks Based on Artificial Intelligence.

Ultrasound-guided quadratus lumborum block (QLB) technology has become a widely used perioperative a...

Machine learning in the diagnosis, management, and care of patients with low back pain: a scoping review of the literature and future directions.

BACKGROUND CONTEXT: Low back pain (LBP) remains the leading cause of disability globally. In recent ...

Continuous Short-Term Pain Assessment in Temporomandibular Joint Therapy Using LSTM Models Supported by Heat-Induced Pain Data Patterns.

This study aims to design a time-continuous pain level assessment system for temporomandibular joint...

AI-based lumbar central canal stenosis classification on sagittal MR images is comparable to experienced radiologists using axial images.

OBJECTIVES: The assessment of lumbar central canal stenosis (LCCS) is crucial for diagnosing and pla...

Application Value of a Machine Learning Model in Predicting Mild Depression Associated with Migraine without Aura.

To investigate the application value of a machine learning model in predicting mild depression asso...

Text mining of verbal autopsy narratives to extract mortality causes and most prevalent diseases using natural language processing.

Verbal autopsy (VA) narratives play a crucial role in understanding and documenting the causes of mo...

Temperature dependence of mosquitoes: Comparing mechanistic and machine learning approaches.

Mosquito vectors of pathogens (e.g., Aedes, Anopheles, and Culex spp. which transmit dengue, Zika, c...

Influence of next-generation artificial intelligence on headache research, diagnosis and treatment: the junior editorial board members' vision - part 1.

Artificial intelligence (AI) is revolutionizing the field of biomedical research and treatment, leve...

The Use of Natural Language Processing Methods in Reddit to Investigate Opioid Use: Scoping Review.

BACKGROUND: The growing availability of big data spontaneously generated by social media platforms a...

Automatic segmentation of echocardiographic images using a shifted windows vision transformer architecture.

Echocardiography is one the most commonly used imaging modalities for the diagnosis of congenital he...

Artificial intelligence and pain management: cautiously optimistic.

MyofAPPcial: Construct validity of a novel technological aid for improving clinical reasoning in the management of myofascial pain syndrome.

BACKGROUND: Physiotherapists encounter challenges in diagnosing myofascial trigger points (MTrPs), w...

A coordinated adaptive multiscale enhanced spatio-temporal fusion network for multi-lead electrocardiogram arrhythmia detection.

The multi-lead electrocardiogram (ECG) is widely utilized in clinical diagnosis and monitoring of ca...

Classifying High-Risk Patients for Persistent Opioid Use After Major Spine Surgery: A Machine-Learning Approach.

BACKGROUND: Persistent opioid use is a common occurrence after surgery and prolonged exposure to opi...

Comparative analysis of artificial intelligence and expert assessments in detecting neonatal procedural pain.

Assessing pain in newborns in the NICU is crucial due to their frequent exposure to painful stimuli,...

GlobalSR: Global context network for single image super-resolution via deformable convolution attention and fast Fourier convolution.

Vision Transformer have achieved impressive performance in image super-resolution. However, they suf...

AI and Big Data approaches to addressing the opioid crisis: a scoping review protocol.

INTRODUCTION: This paper outlines the steps necessary to assess the latest developments in artificia...

Cross-view discrepancy-dependency network for volumetric medical image segmentation.

The limited data poses a crucial challenge for deep learning-based volumetric medical image segmenta...

Image harmonization with Simple Hybrid CNN-Transformer Network.

Image harmonization seeks to transfer the illumination distribution of the background to that of the...

Prediction of mortality events of patients with acute heart failure in intensive care unit based on deep neural network.

BACKGROUND: Acute heart failure (AHF) in the intensive care unit (ICU) is characterized by its criti...

Federated Learning in Glaucoma: A Comprehensive Review and Future Perspectives.

CLINICAL RELEVANCE: Glaucoma is a complex eye condition with varied morphological and clinical prese...