Standard vocabularies to improve machine learning model transferability with electronic health record data: retrospective cohort study using health care-associated infection

HIGHLIGHTS

• who: Unknown from the Department of Biomedical, School of Medicine, University of Utah, Salt Lake City, UT, United have published the research work: Standard Vocabularies to Improve Machine Learning Model Transferability With Electronic Health Record Data: Retrospective Cohort Study Using Health Care-Associated Infection, in the Journal: (JOURNAL)
• what: The study demonstrated that grouping features can overcome challenges created by data heterogeneity. This study has substantial implications for the application of ML models to clinical practice.
• how: The authors hypothesized that ML models for HAI detection using grouped features from EHR data would . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or E-mail:

  If you don't have an account, you can create one here.