A framenet for cancer information in clinical narratives: Schema and annotation

Kirk Roberts, Yuqi Si, Anshul Gandhi, Elmer V Bernstam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a pilot project named Cancer FrameNet. The project's goal is a general-purpose natural language processing (NLP) resource for cancer-related information in clinical notes (i.e., patient records in an electronic health record system). While previous cancer NLP annotation projects have largely been ad hoc resources to address a specific and immediate information need, the frame semantic method employed here emphasizes the information presented in the notes themselves and its linguistic structure. To this end, three semantic frames (targeting the high-level tasks of cancer diagnoses, cancer therapeutic procedures, and tumor descriptions) are created and annotated on a clinical text corpus. Prior to annotation, candidate sentences are extracted from a clinical data warehouse and de-identified to remove any private information. The frames are then annotated with the three frames totaling over thirty frame elements. This paper describes these steps in the pilot project and discusses issues encountered to evaluate the feasibility of general-purpose linguistic resources for extracting cancer-related information.

LanguageEnglish
Title of host publicationLREC 2018 - 11th International Conference on Language Resources and Evaluation
EditorsHitoshi Isahara, Bente Maegaard, Stelios Piperidis, Christopher Cieri, Thierry Declerck, Koiti Hasida, Helene Mazo, Khalid Choukri, Sara Goggi, Joseph Mariani, Asuncion Moreno, Nicoletta Calzolari, Jan Odijk, Takenobu Tokunaga
PublisherEuropean Language Resources Association (ELRA)
Pages272-279
Number of pages8
ISBN (Electronic)9791095546009
StatePublished - Jan 1 2019
Event11th International Conference on Language Resources and Evaluation, LREC 2018 - Miyazaki, Japan
Duration: May 7 2018May 12 2018

Other

Other11th International Conference on Language Resources and Evaluation, LREC 2018
CountryJapan
CityMiyazaki
Period5/7/185/12/18

Fingerprint

cancer
narrative
pilot project
semantics
resources
linguistics
language
Annotation
Cancer
candidacy
electronics
health
Frame Semantics
Resources
Natural Language Processing

Keywords

  • Cancer
  • Clinical information extraction
  • Frame semantics

ASJC Scopus subject areas

  • Linguistics and Language
  • Education
  • Library and Information Sciences
  • Language and Linguistics

Cite this

Roberts, K., Si, Y., Gandhi, A., & Bernstam, E. V. (2019). A framenet for cancer information in clinical narratives: Schema and annotation. In H. Isahara, B. Maegaard, S. Piperidis, C. Cieri, T. Declerck, K. Hasida, H. Mazo, K. Choukri, S. Goggi, J. Mariani, A. Moreno, N. Calzolari, J. Odijk, ... T. Tokunaga (Eds.), LREC 2018 - 11th International Conference on Language Resources and Evaluation (pp. 272-279). European Language Resources Association (ELRA).

A framenet for cancer information in clinical narratives : Schema and annotation. / Roberts, Kirk; Si, Yuqi; Gandhi, Anshul; Bernstam, Elmer V.

LREC 2018 - 11th International Conference on Language Resources and Evaluation. ed. / Hitoshi Isahara; Bente Maegaard; Stelios Piperidis; Christopher Cieri; Thierry Declerck; Koiti Hasida; Helene Mazo; Khalid Choukri; Sara Goggi; Joseph Mariani; Asuncion Moreno; Nicoletta Calzolari; Jan Odijk; Takenobu Tokunaga. European Language Resources Association (ELRA), 2019. p. 272-279.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Roberts, K, Si, Y, Gandhi, A & Bernstam, EV 2019, A framenet for cancer information in clinical narratives: Schema and annotation. in H Isahara, B Maegaard, S Piperidis, C Cieri, T Declerck, K Hasida, H Mazo, K Choukri, S Goggi, J Mariani, A Moreno, N Calzolari, J Odijk & T Tokunaga (eds), LREC 2018 - 11th International Conference on Language Resources and Evaluation. European Language Resources Association (ELRA), pp. 272-279, 11th International Conference on Language Resources and Evaluation, LREC 2018, Miyazaki, Japan, 5/7/18.
Roberts K, Si Y, Gandhi A, Bernstam EV. A framenet for cancer information in clinical narratives: Schema and annotation. In Isahara H, Maegaard B, Piperidis S, Cieri C, Declerck T, Hasida K, Mazo H, Choukri K, Goggi S, Mariani J, Moreno A, Calzolari N, Odijk J, Tokunaga T, editors, LREC 2018 - 11th International Conference on Language Resources and Evaluation. European Language Resources Association (ELRA). 2019. p. 272-279
Roberts, Kirk ; Si, Yuqi ; Gandhi, Anshul ; Bernstam, Elmer V. / A framenet for cancer information in clinical narratives : Schema and annotation. LREC 2018 - 11th International Conference on Language Resources and Evaluation. editor / Hitoshi Isahara ; Bente Maegaard ; Stelios Piperidis ; Christopher Cieri ; Thierry Declerck ; Koiti Hasida ; Helene Mazo ; Khalid Choukri ; Sara Goggi ; Joseph Mariani ; Asuncion Moreno ; Nicoletta Calzolari ; Jan Odijk ; Takenobu Tokunaga. European Language Resources Association (ELRA), 2019. pp. 272-279
@inproceedings{dbc0c8f0b75b4ed29a72c05ca6e864f6,
title = "A framenet for cancer information in clinical narratives: Schema and annotation",
abstract = "This paper presents a pilot project named Cancer FrameNet. The project's goal is a general-purpose natural language processing (NLP) resource for cancer-related information in clinical notes (i.e., patient records in an electronic health record system). While previous cancer NLP annotation projects have largely been ad hoc resources to address a specific and immediate information need, the frame semantic method employed here emphasizes the information presented in the notes themselves and its linguistic structure. To this end, three semantic frames (targeting the high-level tasks of cancer diagnoses, cancer therapeutic procedures, and tumor descriptions) are created and annotated on a clinical text corpus. Prior to annotation, candidate sentences are extracted from a clinical data warehouse and de-identified to remove any private information. The frames are then annotated with the three frames totaling over thirty frame elements. This paper describes these steps in the pilot project and discusses issues encountered to evaluate the feasibility of general-purpose linguistic resources for extracting cancer-related information.",
keywords = "Cancer, Clinical information extraction, Frame semantics",
author = "Kirk Roberts and Yuqi Si and Anshul Gandhi and Bernstam, {Elmer V}",
year = "2019",
month = "1",
day = "1",
language = "English",
pages = "272--279",
editor = "Hitoshi Isahara and Bente Maegaard and Stelios Piperidis and Christopher Cieri and Thierry Declerck and Koiti Hasida and Helene Mazo and Khalid Choukri and Sara Goggi and Joseph Mariani and Asuncion Moreno and Nicoletta Calzolari and Jan Odijk and Takenobu Tokunaga",
booktitle = "LREC 2018 - 11th International Conference on Language Resources and Evaluation",
publisher = "European Language Resources Association (ELRA)",

}

TY - GEN

T1 - A framenet for cancer information in clinical narratives

T2 - Schema and annotation

AU - Roberts, Kirk

AU - Si, Yuqi

AU - Gandhi, Anshul

AU - Bernstam, Elmer V

PY - 2019/1/1

Y1 - 2019/1/1

N2 - This paper presents a pilot project named Cancer FrameNet. The project's goal is a general-purpose natural language processing (NLP) resource for cancer-related information in clinical notes (i.e., patient records in an electronic health record system). While previous cancer NLP annotation projects have largely been ad hoc resources to address a specific and immediate information need, the frame semantic method employed here emphasizes the information presented in the notes themselves and its linguistic structure. To this end, three semantic frames (targeting the high-level tasks of cancer diagnoses, cancer therapeutic procedures, and tumor descriptions) are created and annotated on a clinical text corpus. Prior to annotation, candidate sentences are extracted from a clinical data warehouse and de-identified to remove any private information. The frames are then annotated with the three frames totaling over thirty frame elements. This paper describes these steps in the pilot project and discusses issues encountered to evaluate the feasibility of general-purpose linguistic resources for extracting cancer-related information.

AB - This paper presents a pilot project named Cancer FrameNet. The project's goal is a general-purpose natural language processing (NLP) resource for cancer-related information in clinical notes (i.e., patient records in an electronic health record system). While previous cancer NLP annotation projects have largely been ad hoc resources to address a specific and immediate information need, the frame semantic method employed here emphasizes the information presented in the notes themselves and its linguistic structure. To this end, three semantic frames (targeting the high-level tasks of cancer diagnoses, cancer therapeutic procedures, and tumor descriptions) are created and annotated on a clinical text corpus. Prior to annotation, candidate sentences are extracted from a clinical data warehouse and de-identified to remove any private information. The frames are then annotated with the three frames totaling over thirty frame elements. This paper describes these steps in the pilot project and discusses issues encountered to evaluate the feasibility of general-purpose linguistic resources for extracting cancer-related information.

KW - Cancer

KW - Clinical information extraction

KW - Frame semantics

UR - http://www.scopus.com/inward/record.url?scp=85059889928&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85059889928&partnerID=8YFLogxK

M3 - Conference contribution

SP - 272

EP - 279

BT - LREC 2018 - 11th International Conference on Language Resources and Evaluation

A2 - Isahara, Hitoshi

A2 - Maegaard, Bente

A2 - Piperidis, Stelios

A2 - Cieri, Christopher

A2 - Declerck, Thierry

A2 - Hasida, Koiti

A2 - Mazo, Helene

A2 - Choukri, Khalid

A2 - Goggi, Sara

A2 - Mariani, Joseph

A2 - Moreno, Asuncion

A2 - Calzolari, Nicoletta

A2 - Odijk, Jan

A2 - Tokunaga, Takenobu

PB - European Language Resources Association (ELRA)

ER -