Traffic accidents threaten human lives and impose substantial financial burdens annually.
Accurate estimation of accident fatal crash risk is crucial for enhancing road safety and …

Background Enteral nutrition through feeding tubes serves as the primary method of
nutritional supplementation for patients unable to feed themselves. Plain radiographs are …

The proliferation of text generation applications in social networks has raised concerns
about the authenticity of online content. Large language models like GPTs can now produce …

Deep neural networks have shown remarkable performance on a wide range of
classification tasks and applications. However, the large model size and the enormous size …

SQL injection (SQLi) attacks continue to severely threaten application security, allowing
malicious actors to exploit web input and manipulate an application's database with …

Modern neural network models have demonstrated exceptional classification capabilities
comparable to human performance in various medical diagnosis tasks. However, their …

Neural network model calibration is crucial in medical imaging, where accurate probabilistic
predictions are essential for informed decision-making. Existing calibration techniques often …

Most galaxies in the nearby Universe are gravitationally bound to a cluster or group of
galaxies. Their optical contents, such as optical richness, are crucial for understanding the …

Medical images and reports offer invaluable insights into patient health. The heterogeneity
and complexity of these data hinder effective analysis. To bridge this gap, we investigate …