Automated Extraction of Causal Relations from Text for Teaching Surgical Concepts

Myat Su Yin, Mihai Pomarlan, Peter Haddawy, Muhammad Rauf Tabassam, Chitpol Chaimanakarn, Natchalee Srimaneekarn, Saeed Ul Hassan

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

5 Citations (Scopus)

Abstract

Effective teaching of surgical decision making requires providing students with a deep understanding of the domain so that they have the ability to make decisions in novel situations. This means providing them with a thorough understanding of causal relations between actions and their possible effects in the context of various states of the patient as well as previous actions. Intelligent tutoring systems to teach surgical decision making thus require such domain knowledge, but there are currently no medical ontologies that encompass it. While it is possible to engineer the needed ontologies by hand, this requires a large effort for every new domain to be covered. In this paper we explore the possibility of automatically extracting causal relations from textbooks on surgery. Specifically, we adapt the spaCy NLP tool for this task and apply it to a collection of fifteen textbooks on endodontic root canal treatment, which is one of the most challenging areas of dental surgery. Since the main purpose is to extract knowledge for teaching, we focus on actions that can lead to surgical mishaps. We evaluate the precision and recall of the extracted relations using a gold standard prepared by a pair of dental surgeons.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Healthcare Informatics, ICHI 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728153827
DOIs
Publication statusPublished - Nov 2020
Event8th IEEE International Conference on Healthcare Informatics, ICHI 2020 - Virtual, Oldenburg, Germany
Duration: 30 Nov 20203 Dec 2020

Publication series

Name2020 IEEE International Conference on Healthcare Informatics, ICHI 2020

Conference

Conference8th IEEE International Conference on Healthcare Informatics, ICHI 2020
Country/TerritoryGermany
CityVirtual, Oldenburg
Period30/11/203/12/20

Keywords

  • causal relation
  • ontology
  • surgery
  • text mining

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