Using machine learning to predict antimicrobial minimum inhibitory concentrations and associated genomic features for nontyphoidal Salmonella
Marcus Nguyen, Scott Wesley Long, Patrick F. McDermott, Randall J. Olsen, Robert Olson, Rick L. Stevens, Gregory H. Tyson, Shaohua Zhao, James J. Davis
This study uses XGBoost to predict antimicrobial MICs for nontyphoidal Salmonella with high accuracy using genomic data.
Journal of Clinical Microbiology · Oct 12, 2018Peer-reviewedBioinformatics