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Construction of an PFT database with various clinical information using optical character recognition and regular expression technique

  • Park, Man Young (Mibyeong Research Center, Korea Institute of Oriental Medicine) ;
  • Park, Rae Woong (Department of Biomedical Informatics, Ajou University School of Medicine)
  • Received : 2017.06.02
  • Accepted : 2017.08.23
  • Published : 2017.10.31

Abstract

The pulmonary function test (PFT) is an essential data source for evaluating the effect of drugs on the lungs or the status of lung function. However, the numeric values of PFT cannot be easily used for clinical studies without labor-intensive manual efforts, because PFTs are usually recorded as image files. This study was aimed at constructing a de-identified, open-access PFT database with various clinical information. For constructing the PFT database, optical character recognition (OCR), regular expression, and the parsing technique were used to extract alphanumeric data from the PFT images in a Korean tertiary teaching hospital. This longitudinal observational database contains 413,000 measurements of PFT from 183,000 patients.

Keywords

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Cited by

  1. CIMI: Classify and Itemize Medical Image System for PFT Big Data Based on Deep Learning vol.10, pp.23, 2017, https://doi.org/10.3390/app10238575