Sepsis remains a major global health challenge due to its high mortality rate and the difficulty of predicting its onset from nonspecific early symptoms. To address this, we explored the feasibility of using fine-tuned small-scale large language mode... read more
The widespread adoption of computed tomography has increased the detection of lung nodules. However, deep learning methods for classification of benign and malignant nodules often fail to comprehensively integrate global and local features, and most ... read more
Head computed tomography (CT) imaging is a widely used imaging modality with multitudes of medical indications, particularly in assessing pathology of the brain, skull and cerebrovascular system. It is commonly used as the first-line imaging in neuro... read more
Tobacco quality inspection plays a vital role in ensuring standardized processing, reducing economic losses, and improving industrial automation. However, traditional inspection methods often suffer from inefficiency, high labor costs, and limited re... read more
OBJECTIVE: Accurate morphometric measurements are crucial for musculoskeletal radiography, but they remain labor-intensive and prone to inter-reader variability. Current artificial intelligence-based solutions often require large annotated training d... read more
Image super-resolution (SR) is a computer vision task that reconstructs high-resolution (HR) images from low-resolution (LR) images using algorithms. Current Transformer architectures typically employ modules in a sequential arrangement, which often ... read more
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.