The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...

Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...

The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...

Background and Goal: This study examined whether machine learning could predict the risk and contributing factors of no-shows and late cancellations in primary care practices. Study Approach: ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

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 ...