Diagnosis Classification in the Emergency Room Using Natural Language Processing

Marieke M. van Buchem; H. 't Hart; Pablo Mosteiro Romero; Ilse M.J. Kant; Martijn P. Bauer

doi:10.3233/SHTI230273

Diagnosis Classification in the Emergency Room Using Natural Language Processing

Marieke M. van Buchem^*
, H. 't Hart
, Pablo Mosteiro Romero
, Ilse M.J. Kant
, Martijn P. Bauer

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Diagnosis classification in the emergency room (ER) is a complex task. We developed several natural language processing classification models, looking both at the full classification task of 132 diagnostic categories and at several clinically applicable samples consisting of two diagnoses that are hard to distinguish.

Original language	English
Title of host publication	Caring is Sharing – Exploiting the Value in Data for Health and Innovation
Place of Publication	Netherlands
Publisher	IOS Press
Pages	815 - 816
Number of pages	2
ISBN (Electronic)	978-1-64368-389-8
ISBN (Print)	978-1-64368-388-1
DOIs	https://doi.org/10.3233/SHTI230273
Publication status	Published - 18 May 2023

Publication series

Name	Studies in Health Technology and Informatics
Publisher	IOS Press
Volume	302
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Bibliographical note

Publisher Copyright:
© 2023 European Federation for Medical Informatics (EFMI) and IOS Press.

Keywords

Natural language processing
diagnosis classification
emergency medicine

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10.3233/SHTI230273Licence: CC BY-NC

SHTI-302-SHTI230273Final published version, 119 KBLicence: CC BY-NC

Cite this

van Buchem, M. M., 't Hart, H., Mosteiro Romero, P., Kant, I. M. J., & Bauer, M. P. (2023). Diagnosis Classification in the Emergency Room Using Natural Language Processing. In Caring is Sharing – Exploiting the Value in Data for Health and Innovation (pp. 815 - 816). (Studies in Health Technology and Informatics; Vol. 302). IOS Press. https://doi.org/10.3233/SHTI230273

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title = "Diagnosis Classification in the Emergency Room Using Natural Language Processing",

abstract = "Diagnosis classification in the emergency room (ER) is a complex task. We developed several natural language processing classification models, looking both at the full classification task of 132 diagnostic categories and at several clinically applicable samples consisting of two diagnoses that are hard to distinguish.",

keywords = "Natural language processing, diagnosis classification, emergency medicine",

author = "\{van Buchem\}, \{Marieke M.\} and \{'t Hart\}, H. and \{Mosteiro Romero\}, Pablo and Kant, \{Ilse M.J.\} and Bauer, \{Martijn P.\}",

note = "Publisher Copyright: {\textcopyright} 2023 European Federation for Medical Informatics (EFMI) and IOS Press.",

year = "2023",

month = may,

day = "18",

doi = "10.3233/SHTI230273",

language = "English",

isbn = "978-1-64368-388-1",

series = "Studies in Health Technology and Informatics",

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address = "Netherlands",

}

Diagnosis Classification in the Emergency Room Using Natural Language Processing. / van Buchem, Marieke M.; 't Hart, H.; Mosteiro Romero, Pablo et al.
Caring is Sharing – Exploiting the Value in Data for Health and Innovation. Netherlands: IOS Press, 2023. p. 815 - 816 (Studies in Health Technology and Informatics; Vol. 302).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Diagnosis Classification in the Emergency Room Using Natural Language Processing

AU - van Buchem, Marieke M.

AU - 't Hart, H.

AU - Mosteiro Romero, Pablo

AU - Kant, Ilse M.J.

AU - Bauer, Martijn P.

PY - 2023/5/18

Y1 - 2023/5/18

N2 - Diagnosis classification in the emergency room (ER) is a complex task. We developed several natural language processing classification models, looking both at the full classification task of 132 diagnostic categories and at several clinically applicable samples consisting of two diagnoses that are hard to distinguish.

AB - Diagnosis classification in the emergency room (ER) is a complex task. We developed several natural language processing classification models, looking both at the full classification task of 132 diagnostic categories and at several clinically applicable samples consisting of two diagnoses that are hard to distinguish.

KW - Natural language processing

KW - diagnosis classification

KW - emergency medicine

UR - https://www.scopus.com/pages/publications/85159769760

U2 - 10.3233/SHTI230273

DO - 10.3233/SHTI230273

M3 - Conference contribution

SN - 978-1-64368-388-1

T3 - Studies in Health Technology and Informatics

SP - 815

EP - 816

BT - Caring is Sharing – Exploiting the Value in Data for Health and Innovation

PB - IOS Press

CY - Netherlands

ER -

Diagnosis Classification in the Emergency Room Using Natural Language Processing

Abstract

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Keywords

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