Knowledge Management for Health Care Procedures: From by David Riano
By David Riano
This ebook constitutes the completely refereed post-workshop court cases of the 1st AIME 2007 workshop From wisdom to worldwide Care, K4CARE 2007, held in Amsterdam, The Netherlands, in July 2007, along with the eleventh overseas convention on man made Intelligence in drugs, AIME 2007.
The 10 revised complete papers provided including 2 invited papers have been conscientiously chosen in the course of a moment around of reviewing and development from 14 lectures given on the workshop and are awarded in prolonged model within the publication. The papers are equipped in topical sections on health and wellbeing care wisdom administration, healthiness care wisdom elicitation, healthiness care wisdom transformation, and overall healthiness care clever systems.
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Extra info for Knowledge Management for Health Care Procedures: From Knowledge to Global Care, AIME 2007 Workshop K4CARE 2007, Amsterdam, The Netherlands, July 7, 2007, ...
However, clinicians do not use them as much as expected since health care organisations started to develop them. There are, among others, two barriers making their use difficult. First, the unfamiliarity with clinical guidelines prevents clinicians applying them . In order to solve this problem, an easy access to guideline documents must be available at the point of care. For example, as a direct link accessible from the D. ): K4CARE 2007, LNAI 4924, pp. 21–31, 2008. c Springer-Verlag Berlin Heidelberg 2008 22 M.
To the special casuistry of the Web. We also cover all the main steps of the ontology learning process, configuring an integrated and intelligent learning approach. Our approach is fully unsupervised. This is especially important due to the amount of available web resources, avoiding the need of a domain expert. The incremental learning method allows a dynamic adaptation of the evaluated corpus as new knowledge is acquired (bootstrap). Moreover, it has continuous feedback about the productivity of the learning task performed at each moment, guiding the learning to the most productive entities.
Thus, each step can be bootstrapped with the knowledge acquired up to that moment. In this manner, new concepts and relationships can be used as seeds for further analysis. Through several iterations, the system incrementally constructs the semantic network of concepts composing the domain ontology. As shown in Fig. 2, the learning process is divided in several phases. Fig. 2. g. cancer) that indicates the domain for which the ontology should be constructed. The system starts by querying a web search engine to obtain a corpus of web documents to analyse.