EHR phenotyping via jointly embedding medical concepts and words into a unified vector space.

Journal: BMC medical informatics and decision making
Published Date:

Abstract

BACKGROUND: There has been an increasing interest in learning low-dimensional vector representations of medical concepts from Electronic Health Records (EHRs). Vector representations of medical concepts facilitate exploratory analysis and predictive modeling of EHR data to gain insights about the patterns of care and health outcomes. EHRs contain structured data such as diagnostic codes and laboratory tests, as well as unstructured free text data in form of clinical notes, which provide more detail about condition and treatment of patients.

Authors

  • Tian Bai
    Key Laboratory of Bio-based Material Science & Technology (Northeast Forestry University), Ministry of Education, Harbin, China.
  • Ashis Kumar Chanda
    Department of Computer & Information Sciences, Temple University, Philadelphia, PA, USA.
  • Brian L Egleston
    Fox Chase Cancer Center, Temple University, Philadelphia, PA, USA.
  • Slobodan Vucetic