The infrastructure behind AI agents isn't static—it’s a living, evolving system. Designing effective data pipelines means ...

Objective: To assess the performance of a novel deep learning (DL)-based artificial intelligence (AI) system in classifying computed tomography (CT) scans of pneumonia patients into different groups, ...

Deep learning using routine lab data showed promise in distinguishing candidemia from bacteremia but fell short of outperforming established biomarkers.

Cardiovascular disease is the leading cause of death not only in the United States but globally, per the World Health ...

We’re learning about the phrase 'to go with the flow' which means to follow other people in their thoughts, ideas or actions because it’s the easiest thing to do.

For example, Wu et al. (13), using data from 4,738 patients extracted from the eICU database, constructed a machine model that predicted patients with severe ARDS with an accuracy and AUC of 0.9110, 0 ...

To mitigate domain differences, we adapt the model using a diverse chest X-ray dataset. We evaluate DAViT on a real-world dataset of 5,856 chest X-rays. The results demonstrate that DAViT achieves ...

This paper proposes a new convolutional neuronal network architecture for pneumonia detection in pediatric healthcare. The model was constructed from the scratch and was trained, validated, and tested ...