A new study published in the International Journal of General Medicine showed that physicians may reliably estimate the ...

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

A Hebrew University study suggests AI tools could help growers better manage water use by predicting healthy plant behavior and flagging early signs of stress.

A new Israeli study suggests that machine-learning models may soon give growers a far more precise way to predict how much water their crops use each day, while also laying the groundwork for earlier ...

Researchers have developed a novel AI-driven framework using the XGBoost algorithm to accurately evaluate the skid resistance of asphalt pavements under various conditions. Published in Smart ...

1 U.S. Geological Survey, Geology, Energy and Minerals Science Center, Reston, VA, United States 2 Department of Systems Engineering, Colorado State University, Fort Collins, CO, United States In this ...

Abstract: Additive manufacturing (AM), particularly with Laser Powder Bed Fusion (LPBF), excels in fabricating intricate geometries and custom components through layer-by-layer deposition. However, ...

Benefits of Combining Circulating Tumor DNA With Tissue and Longitudinal Circulating Tumor DNA Genotyping in Advanced Solid Tumors: SCRUM-Japan MONSTAR-SCREEN-1 Study Osteosarcoma (OS) is the most ...

Abstract: Fraud in supply chain operations poses significant risks to businesses, including financial losses, operational inefficiencies, and erosion of stakeholder trust. With the increasing ...

Abstract: Decision tree boosting algorithms, such as XGBoost, have demonstrated superior predictive performance on tabular data for supervised learning compared to neural networks. However, recent ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The experimental exploration of the chemical space of crystalline materials, ...