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Titlebook: Computational Bioengineering and Bioinformatics; Computer Modelling i Nenad Filipovic Conference proceedings 2020 The Editor(s) (if applica

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書(shū)目名稱(chēng)Computational Bioengineering and Bioinformatics
副標(biāo)題Computer Modelling i
編輯Nenad Filipovic
視頻videohttp://file.papertrans.cn/233/232128/232128.mp4
概述Presents the proceedings of the VIII International Conference on Computational Bioengineering (ICCB2019), held in Belgrade, Serbia, on September 4–6, 2019.Discusses advances in the field of computatio
叢書(shū)名稱(chēng)Learning and Analytics in Intelligent Systems
圖書(shū)封面Titlebook: Computational Bioengineering and Bioinformatics; Computer Modelling i Nenad Filipovic Conference proceedings 2020 The Editor(s) (if applica
描述.This book explores the latest and most relevant topics in the field of computational bioengineering and bioinformatics, with a particular focus on patient-specific, disease-progression modeling. It covers computational methods for cardiovascular disease prediction, with an emphasis on biomechanics, biomedical decision support systems, data mining, personalized diagnostics, bio-signal processing, protein structure prediction, biomedical image processing, analysis and visualization, and high-performance computing. It also discusses state-of-the-art tools for disease characterization, and recent advances in areas such as biomechanics, cardiovascular engineering, patient-specific modeling, population-based modeling, multiscale modeling, image processing, data mining, biomedical decision-support systems, signal processing, biomaterials and dental biomechanics, tissue and cell engineering, computational chemistry and high-performance computing. As such, it is a valuable resource for researchers, medical and bioengineering students, and medical device and software experts.
出版日期Conference proceedings 2020
關(guān)鍵詞Biomechanics; Cardiovascular Engineering; Patient Specific Modelling; Population Based Modelling; Multis
版次1
doihttps://doi.org/10.1007/978-3-030-43658-2
isbn_softcover978-3-030-43660-5
isbn_ebook978-3-030-43658-2Series ISSN 2662-3447 Series E-ISSN 2662-3455
issn_series 2662-3447
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

書(shū)目名稱(chēng)Computational Bioengineering and Bioinformatics影響因子(影響力)




書(shū)目名稱(chēng)Computational Bioengineering and Bioinformatics影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Computational Bioengineering and Bioinformatics網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Computational Bioengineering and Bioinformatics網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Computational Bioengineering and Bioinformatics被引頻次




書(shū)目名稱(chēng)Computational Bioengineering and Bioinformatics被引頻次學(xué)科排名




書(shū)目名稱(chēng)Computational Bioengineering and Bioinformatics年度引用




書(shū)目名稱(chēng)Computational Bioengineering and Bioinformatics年度引用學(xué)科排名




書(shū)目名稱(chēng)Computational Bioengineering and Bioinformatics讀者反饋




書(shū)目名稱(chēng)Computational Bioengineering and Bioinformatics讀者反饋學(xué)科排名




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Heart Mechanical Model Based on Holzapfel Experiments,[.]. The Cauchy stress/stretch and shear stress/amount of shear relation curves are used, which are established experimentally under different loading conditions: biaxial extension and triaxial shear. The averaged curves obtained from all considered specimens in [.] are reconstructed and used in our
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,Finite Element Models with Smeared Fields Within Tissue – A Review of the Current Developments,onducted by the first author over several years. The basis of this methodology represents the formulation of a composite smeared finite element (CSFE). The CSFE consists of domains which can be at different length scale, where we have separate physical fields for each of the domains and with the cor
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Application of Composite Smeared Finite Element Model in Drug Delivery Inside Organs,tions. This methodology enables modeling physical fields in biological systems in a simple way, which otherwise, by detailed representation of each biological constituents (capillaries, cell membranes, cell interior, etc.), would not be practical to use. Here we summarize the basic concept of the sm
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Pre-term Birth Prediction at Home: Signal Filtering Influence on the Good Prediction Rate,.]. Despite continuous clinical routine improvements, the preterm rate remains steady. With the aim of avoiding long hospitalization for pregnant women we propose an embedded system which acquires and processes EHG signals. We have already proposed a detection and recognition system for intrauterine
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