Abstract: This research aims to explore the use of modern complex defensive machine learning algorithms in the provision of predictive analytics for health improvement. Incorporating electronic health ...

Programming efficient asynchronous systems is challenging because it can often be hard to express the design declaratively, or to defend against interleaving-dependent bugs such as data races and ...

The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...

Abstract: This study presents deep learning models' design, implementation, and evaluation to generate personalized learning paths in educational environments. Data was collected from diverse sources, ...