Review re-maps multi-view learning into four supervised scenarios and three granular sub-tiers, delivering the first unified ...

Kernel methods represent a cornerstone in modern machine learning, enabling algorithms to efficiently derive non-linear patterns by implicitly mapping data into high‐dimensional feature spaces. At 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 ...

Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

A scientist in Sweden has developed a new hybrid local features-based method using thermographs to identify faulty solar panels. A researcher from Sweden’s Jönköping University has proposed a machine ...

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, and if it is accurately predicted ...

No audio available for this content. High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, ...

Modern agriculture is a data-rich but decision-constrained domain, where traditional methods struggle to keep pace with ...

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