abracadabra 发表于 2025-3-28 16:40:48
Emerging Trends in Knowledge Discovery and Data Mining978-3-642-36778-6Series ISSN 0302-9743 Series E-ISSN 1611-3349filicide 发表于 2025-3-28 21:27:32
Takashi Washio,Jun LuoHigh quality selected papers.Unique visibility.State of the art research品尝你的人 发表于 2025-3-29 02:36:53
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/e/image/308516.jpg委派 发表于 2025-3-29 03:36:42
https://doi.org/10.1007/978-3-642-36778-6classification; health informatics; information retrieval; machine learning; process mining使苦恼 发表于 2025-3-29 08:12:46
Modality Classification for Medical Images Using Sparse Coded Affine-Invariant Descriptors,tos. While assessing image modality is trivial for humans, reliable automatic methods are required to deal with large un-annotated image bases, such as figures taken from the millions of scientific publications. We present a multi-disciplinary approach to tackle the classification problem by combiniinconceivable 发表于 2025-3-29 11:36:08
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Getting a Grasp on Clinical Pathway Data: An Approach Based on Process Mining,enges in terms of design, implementation and diagnosis. Nonetheless, streamlining clinical pathways with the purpose of delivering high quality care while at the same time reducing costs is a promising goal. In this paper, we propose a methodology founded on process mining for intelligent analysis ononplus 发表于 2025-3-29 23:20:42
ALIVE: A Multi-relational Link Prediction Environment for the Healthcare Domain,his purpose, we propose ALIVE, a multi-relational link prediction and visualization environment for the healthcare domain. ALIVE combines novel link prediction methods with a simple user interface and intuitive visualization of data to enhance the decision-making process for healthcare professionalsincite 发表于 2025-3-30 01:48:49
http://reply.papertrans.cn/31/3086/308516/308516_49.pngamputation 发表于 2025-3-30 04:08:15
Applying NLP Techniques for Query Reformulation to Information Retrieval with Geographical Referencphical criteria of relevance. However, since a GIR system can be treated as a traditional Information Retrieval (IR) system, it is important to pay attention to finding effective methods for query reformulation. In this way, the search results will improve their quality and recall. In this paper, we