By Carol Friedman (auth.), Carlo Combi, Yuval Shahar, Ameen Abu-Hanna (eds.)
This e-book constitutes the refereed complaints of the twelfth convention on man made Intelligence in drugs in Europe, AIME 2009, held in Verona, Italy in July 2009.
The 24 revised lengthy papers and 36 revised brief papers offered including 2 invited talks have been rigorously reviewed and chosen from one hundred forty submissions. The papers are equipped in topical sections on agent-based structures, temporal information mining, laptop studying and information discovery, textual content mining, traditional language processing and iteration, ontologies, selection aid structures, functions of AI-based photo processing strategies, protocols and instructions, in addition to workflow systems.
Read Online or Download Artificial Intelligence in Medicine: 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Verona, Italy, July 18-22, 2009. Proceedings PDF
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Extra resources for Artificial Intelligence in Medicine: 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Verona, Italy, July 18-22, 2009. Proceedings
3 Formulation of the Problem In order to formulate the problem of interest in this work here we introduce some useful concepts and then describe the problem in formal terms. , am } be the ﬁnite set of real-valued parameters which describe the physiology of the patient. Physiological data consists of a collection M p of time-ordered measurements of the set P . An event e is deﬁned by the signature tF , tL , Ea, IEa, SEa , where [tF , tL ] (tF < tL ) indicates the time-period of the event (tF , tL ∈ τ 1 ).
Fuzzy Systems in Medicine. In: Proc. of the International Conference in Fuzzy Logic and Technology, pp. 2–5 (2001) 2. : Activity Monitoring: Noticing Interesting Changes in Behavior. In: KDD 1999, pp. 53–62 (1999) 3. : PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation 101(23), e215–e220 (2000) 4. : A method for automated temporal knowledge acquisition applied to sleep-related breathing disorders. Artiﬁcial Intelligence in Medicine 23(2), 211–237 (2001) 5.
E. events characterized by heterogeneous temporal nature. Second, it allows to exploit the integration of different healthcare information sources, such as administrative and clinical data, through a uniform representation. In this work we developed some features able to support the application of the algorithm and the management of the output results. A first feature consists in a postprocessing pruning strategy, aimed at filtering the rules according to a statistical objective measure, the minimum improvement.