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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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51#
發(fā)表于 2025-3-30 09:26:00 | 只看該作者
,Mixed–Integer Real–Time Iterations, Classification errors tended to be concentrated around transients, what constrains their practical impact. Hence, we consider our proposal to be suitable for 24?h-based monitoring of physical activity in ambulatory scenarios and a first step towards intensity-specific energy expenditure estimators.
52#
發(fā)表于 2025-3-30 13:45:31 | 只看該作者
Conference proceedings 2011 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..
53#
發(fā)表于 2025-3-30 17:18:56 | 只看該作者
54#
發(fā)表于 2025-3-30 23:57:28 | 只看該作者
55#
發(fā)表于 2025-3-31 03:34:30 | 只看該作者
https://doi.org/10.1007/978-3-642-78774-4alised dynamic context-aware feedback. The system uses an ontology of messages to find appropriate feedback using context information to prune irrelevant paths. The system adapts using derived probabilities about user preferences for certain message types. We aim to improve patient compliance and user experience.
56#
發(fā)表于 2025-3-31 08:21:38 | 只看該作者
57#
發(fā)表于 2025-3-31 13:00:17 | 只看該作者
58#
發(fā)表于 2025-3-31 16:35:01 | 只看該作者
Ratan Kumar Roy,Ahana Choudhurykeratoconus diagnosis from ORA examinations. As a first use of machine learning approach with ORA parameters, this research work presents a performance comparison of the main machine learning algorithms. This approach improves ORA parameters’ analysis helping ophthalmologist’s efficiency in clinical diagnosis.
59#
發(fā)表于 2025-3-31 18:25:52 | 只看該作者
Understanding Etiology of Complex Neurodevelopmental Disorders: Two Approaches. Although it may seem overly ambitious to target multiple phenotypes jointly, we believe we can obtain much more information from existing data and gain new insights into individual phenotypes by modeling phenotypes jointly. My talk sketches two distinct computational approaches to this problem.
60#
發(fā)表于 2025-3-31 23:56:00 | 只看該作者
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