Latest AI and machine learning research in pain management for healthcare professionals.
OBJECTIVE: To develop a natural language processing (NLP) algorithm that can accurately extract head...
BACKGROUND: Vestibular migraine (VM) and Menière's disease (MD) are two common causes of recurrent s...
Aneurysmal subarachnoid haemorrhage (aSAH) can lead to complications such as acute hydrocephalic con...
OBJECTIVE: The aim of this review is to identify gaps and provide a direction for future research in...
Drug-induced diseases are the most important component of iatrogenic disease. It is the duty of doct...
Our study aims to evaluate the potential of a deep learning (DL) algorithm for differentiating the s...
Pain assessment in trigeminal neuralgia (TN) mouse models is essential for exploring its pathophysio...
English text has a clear and compact subject structure, which makes it easy to find dependency relat...
Understanding, measuring, and mitigating pain-related suffering is a key challenge for both clinical...
PURPOSE: The objective of this study was to perform a retrospective cohort analysis, in which we mea...
Migraine headache, a prevalent and intricate neurovascular disease, presents significant challenges ...
Facial expressions have increasingly been used to assess emotional states in mammals. The recognitio...
The differential diagnosis for optic atrophy can be challenging and requires expensive, time-consumi...
In clinical practice, functional limitations in patients with low back pain are subjectively assesse...
BACKGROUND: Paravertebral block has similar effect as epidural anesthesia, and has good somatic and ...
Early diagnosis of dementia diseases, such as Alzheimer's disease, is difficult because of the time ...
BACKGROUND: Health-related patient-reported outcomes (HR-PROs) are crucial for assessing the quality...
Pain perception nociceptors (PPN), an important type of sensory neuron, are capable of sending out a...
INTRODUCTION: Low back pain is a global health issue causing disability and missed work days. Common...
Convolutional Neural Networks have been widely applied in medical image segmentation. However, the e...
This study aimed to enhance performance, identify additional predictors, and improve the interpretab...