A Methodology for Ontology Reuse: The Case of the Abdominal Ultrasound Ontology

A Methodology for Ontology Reuse: The Case of the Abdominal Ultrasound Ontology

Nur Zareen Zulkarnain, Farid Meziane
Copyright: © 2019 |Pages: 21
DOI: 10.4018/IJIIT.2019100101
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There is an abundance of existing biomedical ontologies such as the National Cancer Institute Thesaurus and the Systematized Nomenclature of Medicine-Clinical Terms. Implementing these ontologies in a particular system however, may cause unnecessary high usage of memory and slows down the systems' performance. On the other hand, building a new ontology from scratch will require additional time and efforts. Therefore, this research explores the ontology reuse approach in order to develop an Abdominal Ultrasound Ontology by extracting concepts from existing biomedical ontologies. This article presents the reader with a step by step method in reusing ontologies together with suggestions of the off-the-shelf tools that can be used to ease the process. The results show that ontology reuse is beneficial especially in the biomedical field as it allows for developers from the non-technical background to build and use domain specific ontology with ease. It also allows for developers with technical background to develop ontologies with minimal involvements from domain experts.
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In previous work, Zulkarnain et al. (2015a) proposed the development of an architecture to support ultrasound report generation and standardisation. The proposed architecture and report were validated by radiologists and specialists at the 2015 UK Radiological Congress held in the City of Liverpool (Zulkarnain et al., 2015b) and the 2016 British Medical Ultrasound Annual Scientific Meeting and Exhibition held in the City of York (Zulkarnain et al., 2016a). In the medical and radiography fields, ultrasound reports are the main media used to communicate the results of an ultrasound examination from a sonographer or radiologist to a referring clinician. It was reported that images alone are of limited value since the outcomes of any ultrasound investigation are based on the findings during the scan (Boland, 2007). Indeed, many features and quantitative data are collected during the ultrasound examination such as tissue characterisation and various measurements and it is this information that is communicated via the reports.

The use of information technology (IT) in the medical field such as electronic patients’ records and some decision support systems has allowed for a better understanding of some pathologies, health management and patient care. However, the integration of IT in the radiology field is limited particularly in the reporting phase. During the development of the standard report and its validation, it was highlighted by the radiologists and clinicians that the main issue is the variations in the reporting styles. These variations were noticed in the structure of the reports as well as in the terminologies used. These variations may impact on the way a report is interpreted and in turn affect the decision-making process and the way a patient is managed (Zulkarnain et al., 2015a). Radiologists and clinicians believe that the solution to this problem resides in using structured reporting with the support of an ontology as its knowledge base (Kahn, et al., 2009). The use of an ontology will allow the standardisation of the terminology used during reporting, allowing a better exploitation of these reports by computerised tools for knowledge discovery, classification and predictions.

The work reported in this paper, is the development of an ontology that will complement and support the computerised standard report developed by Zulkarnain et al., (2015a). Furthermore, this paper is an extension and consolidation of the works reported by Zulkarnain et al. (2015a, 2015b, 2016a, 2016b).

There are different approaches to develop ontologies. We can use existing ontologies, develop one from scratch or adapt and reuse existing ontologies. Each approach has its advantages and disadvantages. For example, in one hand reusing an existing ontology will require no resources for its development but may be too large for a specific application and its integration to the rest of the system could be problematic. On the other hand, developing a new one will require a lot of efforts during its development but may fit better to the requirements of the new application. In this research, we are specifically interested in abdominal ultrasound reporting, and the existing ontologies evaluated were found to be large. For example, using the National Cancer Institute Thesaurus (NCIT) would require a large storage, as it contains as many as 118,941 classes, and more time to process. In this research we adopted the ontology reuse approach for developing the Abdominal Ultrasound Ontology (AUO) to be used in the ultrasound reporting system.

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