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Titlebook: Knowledge Representation for Health-Care; ECAI 2010 Workshop K David Riaño,Annette Teije,Mor Peleg Conference proceedings 2011 Springer Ber

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发表于 2025-3-21 18:07:20 | 显示全部楼层 |阅读模式
书目名称Knowledge Representation for Health-Care
副标题ECAI 2010 Workshop K
编辑David Riaño,Annette Teije,Mor Peleg
视频video
概述deals with the interaction between patient data and guidelines
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Knowledge Representation for Health-Care; ECAI 2010 Workshop K David Riaño,Annette Teije,Mor Peleg Conference proceedings 2011 Springer Ber
描述This book constitutes the proceedings of the KR4HC 2010 workshop held at ECAI in Lisbon, Portugal, in August 2010. The 11 extended papers presented were carefully reviewed and selected from 19 submissions. The papers cover topics like ontologies, patient data, records, and guidelines, and clinical practice guidelines.
出版日期Conference proceedings 2011
关键词cluster analysis; data mining; digital libraries; health care; health records; information systems; intero
版次1
doihttps://doi.org/10.1007/978-3-642-18050-7
isbn_softcover978-3-642-18049-1
isbn_ebook978-3-642-18050-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Berlin Heidelberg 2011
The information of publication is updating

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/k/image/544033.jpg
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Knowledge Representation for Health-Care978-3-642-18050-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
发表于 2025-3-22 10:49:15 | 显示全部楼层
0302-9743 in Lisbon, Portugal, in August 2010. The 11 extended papers presented were carefully reviewed and selected from 19 submissions. The papers cover topics like ontologies, patient data, records, and guidelines, and clinical practice guidelines.978-3-642-18049-1978-3-642-18050-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
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https://doi.org/10.1007/978-3-642-18050-7cluster analysis; data mining; digital libraries; health care; health records; information systems; intero
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Critiquing Knowledge Representation in Medical Image Interpretation Using Structure Learninge experiments we have gained much insight into the problem of knowledge representation and concluded that structure learning results can be conceptually clear and of help in designing a Bayesian network for medical image interpretation.
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Cristina Romero-Tris,David Riaño,Francis Realed in the previous century to contain democratic unrest. This time, the idea was to undercut any possible appeal of the model taking shape in East Germany. The disadvantage of the system, however, was that it ran the risk of muting signals from the market and encouraging complacency.
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