首页|Auburn University Reports Findings in Machine Learning (Discrimination of Common E. coli Strains in Urine by Liquid Chromatography-Ion Mobility-Tandem Mass Spec trometry and Machine Learning)
Auburn University Reports Findings in Machine Learning (Discrimination of Common E. coli Strains in Urine by Liquid Chromatography-Ion Mobility-Tandem Mass Spec trometry and Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsreporting from Auburn, Alabama, by News Rx journalists, research stated, “Accurate identification ofbacterial strains i n clinical samples is essential to provide an appropriate antibiotherapy to the patient andreduce the prescription of broad-spectrum antimicrobials, leading to antibiotic resistance. In this study, weutilized the combination of a multidim ensional analytical technique, liquid chromatography-ion mobilitytandemmass sp ectrometry (LC-IM-MS/MS), and machine learning to accurately identify and distin guish11 () strains in artificially contaminated urine samples.”
AuburnAlabamaUnited StatesNorth an d Central AmericaCyborgsEmerging TechnologiesMachine Learning
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