Machine learning powers new approach to detecting soil contaminants

Machine learning powers new approach to detecting soil contaminants

A team of researchers at Rice University and Baylor College of Medicine has developed a new strategy for identifying hazardous pollutants in soil, even ones that have never been isolated or studied in a lab.

Machine Learning Powers New Approach to Detecting Soil Contaminants

HOUSTON, Texas — A team of researchers at Rice University and Baylor College of Medicine has developed a new strategy for identifying hazardous pollutants in soil, even ones that have never been isolated or studied in a lab. The new approach, described in a study published in Proceedings of the National Academy of Sciences, uses light-based imaging, theoretical predictions of compounds’ light signatures and machine learning (ML) algorithms to de…

A team of researchers from Rice University and Baylor College of Medicine has developed a new strategy to identify hazardous pollutants in the soil, even those that have never been isolated or studied in a laboratory. The new approach, described in a study published in Acts of the National Academy of Sciences, uses imaging in [...]