Literature DB >> 29295100

MedEx/J: A One-Scan Simple and Fast NLP Tool for Japanese Clinical Texts.

Eiji Aramaki1, Ken Yano1, Shoko Wakamiya1.   

Abstract

Because of recent replacement of physical documents with electronic medical records (EMR), the importance of information processing in the medical field has increased. In light of this trend, we have been developing MedEx/J, which retrieves important Japanese language information from medical reports. MedEx/J executes two tasks simultaneously: (1) term extraction, and (2) positive and negative event classification. We designate this approach as a one-scan approach, providing simplicity of systems and reasonable accuracy. MedEx/J performance on the two tasks is described herein: (1) term extraction (F<inf>β = 1</inf> = 0.87) and (2) positive-negative classification (F<inf>β = 1</inf> = 0.63). This paper also presents discussion and explains remaining issues in the medical natural language processing field.

Keywords:  Medical Informatics; Natural Language Processing

Mesh:

Year:  2017        PMID: 29295100

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  2 in total

1.  Extraction and Standardization of Patient Complaints from Electronic Medication Histories for Pharmacovigilance: Natural Language Processing Analysis in Japanese.

Authors:  Misa Usui; Eiji Aramaki; Tomohide Iwao; Shoko Wakamiya; Tohru Sakamoto; Mayumi Mochizuki
Journal:  JMIR Med Inform       Date:  2018-09-27

2.  Identification of Adverse Drug Event-Related Japanese Articles: Natural Language Processing Analysis.

Authors:  Shogo Ujiie; Shuntaro Yada; Shoko Wakamiya; Eiji Aramaki
Journal:  JMIR Med Inform       Date:  2020-11-27
  2 in total

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