Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

The process of testing new solar cell technologies has traditionally been slow and costly, requiring multiple steps. Led by a fifth-year PhD student, a Johns Hopkins team has developed a machine ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

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 ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...

High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, traditional methods like the R-ratio ...

Hundreds of thousands of children in China have been separated from their parents. A Yale SOM study finds that a ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...