A new machine learning method from Rice University helps scientists better understand the unique light signatures of ...

The algorithm will then use the MOMA data as input and output predictions of the chemical composition of the studied sample, based on its training. "The more we do to optimize the data analysis ...

Researchers have developed a new machine learning algorithm that excels at interpreting optical spectra, potentially enabling faster and more precise medical diagnoses and sample analysis.

The Rice University solution is termed Peak-Sensitive Elastic-net Logistic Regression, or PSE-LR, a method tailored for spectral analysis. PSE-LR includes computational steps intended to more ...

Researchers at Rice University have developed a new machine learning (ML) algorithm that excels at interpreting the "light ...

A collaborative research effort between UNIST and the Korea Institute of Science and Technology (KIST) has led to the ...