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Titlebook: Artificial Intelligence in Medicine; 13th Conference on A Mor Peleg,Nada Lavra?,Carlo Combi Conference proceedings 2011 Springer-Verlag Gmb

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發(fā)表于 2025-3-21 16:40:29 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Artificial Intelligence in Medicine
期刊簡稱13th Conference on A
影響因子2023Mor Peleg,Nada Lavra?,Carlo Combi
視頻videohttp://file.papertrans.cn/163/162499/162499.mp4
發(fā)行地址Fast track proceedings
學科分類Lecture Notes in Computer Science
圖書封面Titlebook: Artificial Intelligence in Medicine; 13th Conference on A Mor Peleg,Nada Lavra?,Carlo Combi Conference proceedings 2011 Springer-Verlag Gmb
影響因子.This book constitutes the refereed proceedings of the 13th Conference on Artificial Intelligence in Medicine, AIME 2011, held in Bled, Slovenia, in July 2011...The 42 revised full and short papers presented together with 2 invited talks were carefully reviewed and selected from 113 submissions. The papers are organized in topical sections on knowledge-based systems; data mining; special session on AI applications; probabilistic modeling and reasoning; terminologies and ontologies; temporal reasoning and temporal data mining; therapy planning, scheduling and guideline-based care; and natural language processing..
Pindex Conference proceedings 2011
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Architectures for Frequency Synthesizers,t against these maladies. (Genetic overlap of complex phenotypes has gained increasing experimental support and is no longer just an ungrounded scientific hypothesis.) Furthermore, as yet largely unknown shared environmental factors likely tend to trigger the manifestation of more than one phenotype
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Silver Soled State Energy Storage Devices, in turn, requires advanced IT support for healthcare processes covering both organizational procedures and knowledge-intensive, dynamic treatment processes. Nowadays, required agility is often hindered by a lack of flexibility in hospital information systems. To overcome this inflexibility a new g
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J. Lee,A. Lamperski,J. Schmitt,N. Cowanss of EIRA is the lack of mechanisms to describe to the clinicians, rationales behind the anomalous detections. In this paper, we extend EIRA by providing it with an argumentation-based justification system that formalizes and communicates to the clinicians the reasons why a patient response is anom
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