A machine learning model can use patient-reported data and remote therapeutic monitoring to accurately assess low disease ...

A machine learning model using basic clinical data can predict PH risk, identifying key predictors like low hemoglobin and elevated NT-proBNP. Researchers have developed a machine learning model that ...

When experiments are impractical, density functional theory (DFT) calculations can give researchers accurate approximations of chemical properties. The mathematical equations that underpin the ...

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

Logistic regression is the most cost-effective model for medial vascular calcification classification, with a mean ICER of $278 using five low-cost features. Despite similar diagnostic accuracy, ...

With heatwaves among Europe's deadliest climate hazards, a team of scientists led by CMCC has developed a prediction system capable of providing helpful information 4 to 7 weeks before summer, which ...

Artificial intelligence (AI) is increasingly prevalent, integrated into phone apps, search engines and social media platforms ...

Built on App Orchid's semantic knowledge graph, the Agent continuously learns from context to improve accuracy, transparency, and enterprise trust.

The researchers argue that the integration of explainable AI into clinical decision-making pipelines could reshape cancer ...

MIT researchers have built a new AI system that allows robots to create detailed 3D maps of complex environments within seconds. The technology could transform how search-and-rescue robots navigate ...