Next-generation phenotyping of electronic health records

Columbia University

PubMed
Indexed incrossrefpubmed

Abstract

The national adoption of electronic health records (EHR) promises to make an unprecedented amount of data available for clinical research, but the data are complex, inaccurate, and frequently missing, and the record reflects complex processes aside from the patient's physiological state. We believe that the path forward requires studying the EHR as an object of interest in itself, and that new models, learning from data, and collaboration will lead to efficient use of the valuable information currently locked in health records.

Citation impact

812
total citations
FWCI
54.37
Percentile
100%
References
51
Citations per year

Authors

2

Topics & keywords

Keywords
  • Health records
  • Computer science
  • Data science
  • Electronic health record
  • Object (grammar)
  • Aside
  • Health care
  • Artificial intelligence
No related works found for this paper.