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Titlebook: Knowledge-Based Systems in Biomedicine and Computational Life Science; Tuan D. Pham,Lakhmi C. Jain Book 2013 Springer-Verlag Berlin Heidel

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书目名称Knowledge-Based Systems in Biomedicine and Computational Life Science
编辑Tuan D. Pham,Lakhmi C. Jain
视频videohttp://file.papertrans.cn/545/544228/544228.mp4
概述Latest research in Knowledge-based Systems in Biomedicine.Bridges the gap between hypothesis-driven and data-driven problem solving in medicine and biology.Written by leading experts in the field
丛书名称Studies in Computational Intelligence
图书封面Titlebook: Knowledge-Based Systems in Biomedicine and Computational Life Science;  Tuan D. Pham,Lakhmi C. Jain Book 2013 Springer-Verlag Berlin Heidel
描述.This book presents a sample of research on knowledge-based systems in biomedicine and computational life science. The contributions include: personalized stress diagnosis system, image analysis system for breast cancer diagnosis, analysis of neuronal cell images, structure prediction of protein, relationship between two mental disorders, detection of cardiac abnormalities, holistic medicine based treatment and analysis of life-science data.. .
出版日期Book 2013
关键词Biomedicine; Computational Intelligence; Knowledge-based Systems; Systems Biology
版次1
doihttps://doi.org/10.1007/978-3-642-33015-5
isbn_softcover978-3-642-44530-9
isbn_ebook978-3-642-33015-5Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightSpringer-Verlag Berlin Heidelberg 2013
The information of publication is updating

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Breast Cancer Histological Image Classification with Multiple Features and Random Subspace Classifion histological images. The image features are extracted using the Curvelet Transform, statistics of Gray Level Co-occurrence Matrix (GLCM) and the Completed Local Binary Patterns (CLBP), respectively. The three different features are combined together and used for classification. A classifier ensem
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Protein Structure Prediction: Are We There Yet?,tein conformations is the key to it. But still, there is a huge sequence-structure gap between the available number of protein sequences and the known count of experimentally solved structures. Because of several technical and resource limitations, experimentally determined structures do not exist f
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Robust Algorithmic Detection of Cardiac Pathologies from Short Periods of RR Data,lities. Recently we have illustrated that building meta-indicators on the base of existing indicators from nonlinear dynamics (NLD) using boosting-like ensemble learning techniques could help to overcome one of the main restrictions of all NLD and linear indicators – requirement of long time series
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