Indonesian protected health information removal using named entity recognition

Herley Shaori Al-Ash, Ivan Fanany, Alhadi Bustamam

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The Electronic Health Record (EHR) is the implementation of a computer system to keep a history of patient health records. All information related to patients is stored as patients who have medical history, immunization status, sugar level, and blood pressure records. EHR also contains the patient protected health information such as patient name and patient id. However, before processing further any text processing method, the protected health information needs to be removed from the data. This research employs a combination of long short term memory neural networks and conditional random fields in order to remove protected health information within the data. We employ several evaluations criteria to discover the best model. Our final evaluation result yields 0.76 the proposed model best result.

Original languageEnglish
Title of host publicationProceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages258-263
Number of pages6
ISBN (Electronic)9781728121338
DOIs
Publication statusPublished - 1 Jul 2019
Event12th International Conference on Information and Communication Technology and Systems, ICTS 2019 - Surabaya, Indonesia
Duration: 18 Jul 2019 → …

Publication series

NameProceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019

Conference

Conference12th International Conference on Information and Communication Technology and Systems, ICTS 2019
CountryIndonesia
CitySurabaya
Period18/07/19 → …

Keywords

  • Conditional random fields
  • Electronic health record
  • Long short term memory neural networks
  • Protected health information

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