An empirical evaluation of deep learning for ICD-9 code assignment using MIMIC-III clinical notes.

Journal: Computer methods and programs in biomedicine
Published Date:

Abstract

BACKGROUND AND OBJECTIVE: Code assignment is of paramount importance in many levels in modern hospitals, from ensuring accurate billing process to creating a valid record of patient care history. However, the coding process is tedious and subjective, and it requires medical coders with extensive training. This study aims to evaluate the performance of deep-learning-based systems to automatically map clinical notes to ICD-9 medical codes.

Authors

  • Jinmiao Huang
    Georgia Institute of Technology, North Ave NW, Atlanta, Georgia, 30332, USA. Electronic address: vichuang@gatech.edu.
  • Cesar Osorio
    Georgia Institute of Technology, North Ave NW, Atlanta, Georgia, 30332, USA. Electronic address: cesar.osorio@gatech.edu.
  • Luke Wicent Sy
    Georgia Institute of Technology, North Ave NW, Atlanta, Georgia, 30332, USA. Electronic address: sylukewicent@gmail.com.