Algorithms and a tool for automatic decryption of clinical notes

Simon G. Abbott, Abejide Ade-Ibijola

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

2 Citations (Scopus)

Abstract

Natural Language Processing (NLP) presents a set of techniques that are finding applications in modern healthcare, for the extraction and generation text. Clinical notes are classically originated and derived from various sources of narratives such as reports, referral letters, discharge notes and clinical summaries. In this paper, we present algorithms and a tool for enabling each member of a medical team to read and understand each others medical notes, using NLP techniques. We refer to this process as the decryption, or the deciphering, of complex clinical notes into simple readable language. We have presented a tool called the Clinical Note Translator (CNT). Based on the replacement of technical terms in clinical notes, CNT translates these notes to plain text. This solution is expected to assist multidisciplinary medical teams in understanding peer-to-peer expert notes.

Original languageEnglish
Title of host publication2019 6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages137-143
Number of pages7
ISBN (Electronic)9781728145778
DOIs
Publication statusPublished - Nov 2019
Event6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019 - Johannesburg, South Africa
Duration: 19 Nov 201920 Nov 2019

Publication series

Name2019 6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019

Conference

Conference6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019
Country/TerritorySouth Africa
CityJohannesburg
Period19/11/1920/11/19

Keywords

  • Clinical notes
  • Information extraction
  • Natural language processing
  • Parsers

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Computational Mathematics
  • Modeling and Simulation

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