Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 27,871 to 27,880 of 219,064 articles

Lightweight large language models for early sepsis prediction via a semantic abstraction rule engine.

Scientific reports
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 

DeepFAN, a transformer-based model for human-artificial intelligence collaborative assessment of incidental pulmonary nodules in CT scans: a multireader, multicase trial.

Nature cancer
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 

3D foundation model for generalizable disease detection in head computed tomography.

Nature biomedical engineering
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 

Edge-enabled IoT framework for real-time tobacco quality monitoring.

Scientific reports
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 

An artificial intelligence framework for universal landmark matching and morphometry in musculoskeletal radiography.

European radiology
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 

WHANet: Weighted Hierarchical Attention for Lightweight SR.

Scientific reports
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