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What is Knowledge Acquisition Bottleneck

Handbook of Research on Trends in the Diagnosis and Treatment of Chronic Conditions
A serious problem that results from the fact that ontologies are curated by Domain Experts in any given science field and those that simultaneously master the ontological engineering knowledge that is traditionally in need are very few worldwide. The sources of information are currently humongous, namely the Internet, but to classify and structure it there exists a serious shortage of human power to render the availability of ontological foundations that are supposedly the stepping stone for the realization of wide spread computer reasoning and the Semantic Web.
Published in Chapter:
Clinical Practice Ontology Automatic Learning from SOAP Reports
David Mendes (Universidade de Évora, Portugal), Irene Pimenta Rodrigues (Universidade de Évora, Portugal), and Carlos Fernandes Baeta (Unidade Local de Saúde do Norte Alentejano, Portugal)
DOI: 10.4018/978-1-4666-8828-5.ch016
Abstract
We show how we implemented an end-to-end process to automatically develop a clinical practice knowledge base acquiring from SOAP notes. With our contribution we intend to overcome the “Knowledge Acquisition Bottleneck” problem by jump-starting the knowledge gathering from the most widely available source of clinical information that are natural language reports. We present the different phases of our process to populate automatically a proposed ontology with clinical assertions extracted from daily routine SOAP notes. The enriched ontology becomes a reasoning able knowledge base that depicts accurately and realistically the clinical practice represented by the source reports. With this knowledge structure in place and novel state-of-the-art reasoning capabilities, based in consequence driven reasoners, a clinical QA system based in controlled natural language is introduced that reveals breakthrough possibilities regarding the applicability of Artificial Intelligence techniques to the medical field.
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