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 ...

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 ...

AI and machine learning are revolutionizing drug discovery, development, and lifecycle management, addressing industry ...

Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...

This study presents a transfer learning–based method for predicting train-induced environmental vibration. The method applies ...

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft Your email has been sent A new “periodic table for machine learning” is reshaping how researchers explore AI, ...

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, ...

A new research paper shows the approach performs significantly better than the random-walk forecasting method.

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 ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

Machine learning reduces friction at every stage of a business, whether you’re coming up with new product ideas or getting the goods delivered to the client. It increases business efficiency, improves ...