The abundance of biomedical ontologies is beneficial to the development of biomedical related systems. However, existing biomedical ontologies such as the National Cancer Institute Thesaurus (NCIT), Foundational Model of Anatomy (FMA) and Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) are often too large to be implemented in a particular system and cause unnecessary high usage of memory and slow down the system's processing time. Developing a new ontology from scratch just for the use of a particular system is deemed as inefficient since it requires additional time and causes redundancy. Thus, a potentially better method is by reusing existing ontologies. However, currently there are no specific methods or tools for reusing ontologies. This paper aims to provide readers with a step by step method in reusing ontologies together with the tools that can be used to ease the process.
Abstract:Ultrasound reports are developed in different ways by clinicians and radiologists. These variations in reporting style, content and format could impact on the value of the report and the way it is interpreted, which in turn have implications on patient management and decision making. There are many reasons for the poor success rate of some reporting systems which is usually down to poor adaptability and the main one being the human factor. In this paper, we present a system architecture model for a proposed medical ultrasound reporting system that attempt to address some of these problems. In this system, we propose a solution where humans will not need to adapt to the system, instead the system acknowledge the various styles, contents and format being produced by the humans and uses an ontology to standardise the terminology and Natural Language Processing techniques to transform free text reports to the preferred proposed model of a structured and standardised report.
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