• Corpus ID: 243832906

Predicting Antimicrobial Resistance in the Intensive Care Unit

@inproceedings{Wang2021PredictingAR,
  title={Predicting Antimicrobial Resistance in the Intensive Care Unit},
  author={Taiyao Wang and Kyle R. Hansen and Joshua Loving and Ioannis Ch. Paschalidis and Helen van Aggelen and Eran Simhon},
  year={2021}
}
Correspondence: wty@bu.edu Philips Research North America, Cambridge, MA, USA Full list of author information is available at the end of the article Abstract Antimicrobial resistance (AMR) is a risk for patients and a burden for the healthcare system. However, AMR assays typically take several days. This study develops predictive models for AMR based on easily available clinical and microbiological predictors, including patient demographics, hospital stay data, diagnoses, clinical features, and… 

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