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Titlebook: Medical Content-Based Retrieval for Clinical Decision Support; First MICCAI Interna Barbara Caputo,Henning Müller,Jayashree Kalpathy-C Conf

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發(fā)表于 2025-3-21 18:14:24 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Medical Content-Based Retrieval for Clinical Decision Support
副標(biāo)題First MICCAI Interna
編輯Barbara Caputo,Henning Müller,Jayashree Kalpathy-C
視頻videohttp://file.papertrans.cn/630/629133/629133.mp4
叢書(shū)名稱(chēng)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Medical Content-Based Retrieval for Clinical Decision Support; First MICCAI Interna Barbara Caputo,Henning Müller,Jayashree Kalpathy-C Conf
出版日期Conference proceedings 2010
關(guān)鍵詞alzheimers; clinical decision making; content-based retrieval; data retrieval; gaid data; lung deseases; m
版次1
doihttps://doi.org/10.1007/978-3-642-11769-5
isbn_softcover978-3-642-11768-8
isbn_ebook978-3-642-11769-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2010
The information of publication is updating

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發(fā)表于 2025-3-21 21:35:01 | 只看該作者
Medical Content-Based Retrieval for Clinical Decision Support978-3-642-11769-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
板凳
發(fā)表于 2025-3-22 03:03:17 | 只看該作者
0302-9743 Overview: 978-3-642-11768-8978-3-642-11769-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
地板
發(fā)表于 2025-3-22 04:33:49 | 只看該作者
https://doi.org/10.1007/978-3-642-11769-5alzheimers; clinical decision making; content-based retrieval; data retrieval; gaid data; lung deseases; m
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發(fā)表于 2025-3-22 11:31:55 | 只看該作者
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發(fā)表于 2025-3-22 15:02:39 | 只看該作者
3D Case–Based Retrieval for Interstitial Lung Diseases5.1% of correct matching among five classes of lung tissues as well as a mean average retrieval precision at rank 1 of 71% show that automated lung tissue categorization in HRCT data is complementary to case–based retrieval both from the user’s viewpoint and also on the algorithmic side.
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發(fā)表于 2025-3-22 18:56:09 | 只看該作者
Automatic Annotation of X-Ray Images: A Study on Attribute Selectiont of attribute selection on the classification performance. Our experiments show that principal component analysis based attribute selection manifests prediction values that are comparable to the baseline (all-features case) with considerably smaller subsets of original features, inducing lower processing times and reduced storage space.
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發(fā)表于 2025-3-22 23:11:55 | 只看該作者
Overview of the First Workshop on Medical Content–Based Retrieval for Clinical Decision Support at Mworkshop, provide details about the organization and participation, discuss the current state–of–the–art in clinical image retrieval and the use of images for clinical decision support. We conclude with open issues and challenges that lie ahead for the domain of medical content–based retrieval.
9#
發(fā)表于 2025-3-23 04:51:30 | 只看該作者
Image Retrieval for Alzheimer’s Disease Detectionor Machines. Finally, ranking of most accurate matches are generated by applying an Euclidean distance score. The overall system architecture follows a multi-level model, permitting performance analysis of components independently. Experimental results demonstrate that the system can produce effective results.
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發(fā)表于 2025-3-23 09:13:15 | 只看該作者
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