Latest AI and machine learning research in pain management for healthcare professionals.
In the fast-fashion industry, overproduction and unsold inventory create significant environmental problems. Precise sales forecasts for unreleased items could drastically improve the efficiency and profits of industries. However, predicting the success of entirely new styles is difficult due to the absence of past data and ever-changing trends. Specifically, currently used deterministic models ...
Glaucoma is a progressive optic neuropathy characterized by structural damage to the optic nerve head and functional changes in the visual field. Detecting glaucoma early is crucial to preventing loss of eyesight. However, medical datasets often suffer from class imbalances, making detection more difficult for deep-learning algorithms. We use a generative-based framework to enhance glaucoma diag...
Multimodal emotion recognition in conversation (MERC) refers to identifying and classifying human emotional states by combining data from multiple d...
Big data visualization - the visual-spatial display of quantitative information culled from huge data sets - is now firmly embedded within the every...
With the intensification of global aging, health management of the elderly has become a focus of social attention. This study designs and implements...
BACKGROUND: The present study aimed to determine whether machine-learning (ML)-based models can predict 3-, 6, and 12-month responses to the monoclona...
BACKGROUND: Trigeminal neuralgia (TN) is defined as spontaneous pain in the region of the trigeminal nerve that seriously affects a patient's quality ...
Convolutional neural networks (CNNs) are well established in handling local features in visual tasks; yet, they falter in managing complex spatial rel...
Intervertebral disc degeneration (IDD) is a primary cause of low back pain and disability. Cellular senescence and apoptosis due to endoplasmic reticu...
Early diagnosis and discovery of therapeutic drug targets are crucial objectives for the effective management of Alzheimer's Disease (AD). Current a...
Medical image segmentation is essential for applications like robotic surgeries, disease diagnosis, and treatment planning. Recently, various deep-l...
Neuropathologic changes of Alzheimer disease (AD) including Aβ accumulation and neuroinflammation are frequently observed in the cerebral cortex of pa...
IMPORTANCE: Prompt and accurate diagnosis of arteritic anterior ischemic optic neuropathy (AAION) from giant cell arteritis and other systemic vasculi...
Brain neural signal at different frequency bands relates to different functions. However, the frequency-specific properties of spontaneous brain activ...
In recent years, machine learning, particularly Natural Language Processing, has emerged as a valuable tool for analyzing unstructured health data, su...
Understanding the neurobiology of opioid use disorder (OUD) using resting-state functional magnetic resonance imaging (rs-fMRI) may help inform trea...
The Workflows Community Summit gathered 111 participants from 18 countries to discuss emerging trends and challenges in scientific workflows, focusi...
In this paper, we approach an overlooked yet critical task Graph2Image: generating images from multimodal attributed graphs (MMAGs). This task poses...
Background: One of the key FDA-approved medications for Opioid Use Disorder (OUD) is buprenorphine. Despite its popularity, individuals often report...
Although modern imaging technologies allow us to study connectivity between two distinct brain regions in-vivo, an in-depth understanding of how ana...