Latest AI and machine learning research in head trauma for healthcare professionals.
OBJECTIVE: Traumatic brain injury (TBI) remains a leading cause of disability and death globally, an...
The purpose of this study was to investigate the utility of deep learning image reconstruction at me...
BACKGROUND: Hair transplantation is a minimally invasive procedure for treating hair loss in men and...
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, heterogeneous, and systemi...
The incidence of TB in Taiwan declined by 62% from 2005 to 2023 (i.e., from 73/100,000 to 28/100,000...
Accurate retrieval of the maintained information is crucial for working memory. This process primari...
INTRODUCTION: Post-stroke depression is one of the important complications of stroke and affects pat...
Stroke continues to be a major adverse event in advanced congestive heart failure (CHF) patients aft...
Objectives: While Large Language Models (LLMs) have been widely used to assist clinicians and supp...
The growing adoption of synthetic data in healthcare is driven by privacy concerns, limited access...
Since the early days of the Explainable AI movement, post-hoc explanations have been praised for t...
Mild Traumatic Brain Injury (TBI) detection presents significant challenges due to the subtle and ...
The advancement of AI systems for mental health support is hindered by limited access to therapeut...
Pelvic fractures, often caused by high-impact trauma, frequently require surgical intervention. Im...
Post-hoc explanation methods provide interpretation by attributing predictions to input features. ...
Post-Traumatic Stress Disorder (PTSD) remains underdiagnosed in clinical settings, presenting oppo...
Early and accurate diagnosis of pulmonary hypertension (PH) is essential for optimal patient manag...
Text-to-image generation models, especially Multimodal Diffusion Transformers (MMDiT), have shown ...
Code translation migrates codebases across programming languages. Recently, large language models ...
The size of a model has been a strong predictor of its quality, as well as its cost. As such, the ...
Ontologies are widely used in databases to standardize data, improving data quality, integration, an...