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检索条件"任意字段=Proceedings of the 2023 10th International Conference on Biomedical and Bioinformatics Engineering"

共 916 条记录，以下是61-70 订阅

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Comprehensive Analysis on Feature Selection, Machine Learning and Deep Learning Algorithms to Detect Driver Drowsiness - An EEG Study 10

Comprehensive Analysis on Feature Selection, Machine Learnin...

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10th international conference on biomedical and bioinformatics engineering (ICBBE)

作者： Ferdous, Talukdar Raian Tushar, Md Abdul Kader Rafi, Rifath Hasan Asif, Nazmus Salehin Palash, Torikul Islam Arman, Md Adil Saha, Debasish Kumar Islam, Muhammad Muinul Univ Houston Houston TX 77204 USA New Jersey Inst Technol Newark NJ USA Texas Southern Univ Houston TX USA Florida Int Univ Miami FL USA Khulna Univ Engn & Technol Khulna Bangladesh

ISBN: (纸本)9798400708343

Drowsiness among drivers is one of the key reasons for traffic accidents which has been recognized as a global problem and this hazardous event causes physical injury, economic suffering, and even death to people. With the advancement of artificial intelligence, drowsiness can be detected from the brain signals and a prior alert can be generated to avoid such losses. For an optimal classification study, extensive analysis of major aspects such as optimal feature selection and choosing compatible classification algorithms should be done properly. this study focused on the classification of the drowsiness stage and active stage from continuous EEG signal (9 channels) starting with the implementation of feature selection algorithms to find the best temporal EEG features for feeding the classifiers and then undergoing different machine learning and deep learning algorithms. Recursive feature elimination and chi-square test, two popular feature selection algorithms, were utilized to find the most possible contributing features which were then fed to 17 machine learning models and 3 deep learning networks. After primary performance analysis selected machine learning models: K-Nearest Neighbor (KNN), Logistic Regression, Random Forest and Support Vector Machine (SVM) were chosen for hyperparametric tuning to achieve the highest performance. Among three deep learning algorithms such as long-short-term memory (LSTM), artificial neural network (ANN), and 1-dimensional convolutional network (1D-CNN), LSTM outperformed the rests with a classi- accuracy with lower resource consumption than the deep learning models. the goal of this study is to help in the improvement of a drowsiness classification system that is effective in preventing accidents and reducing the risk of harm to people and property.

关键词： Drowsiness detection Machine Learning Deep Learning Feature engineering

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Generalized Net Model of the First Phase of the General Claim Process 10

Generalized Net Model of the First Phase of the General Clai...

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10th IEEE international conference on Intelligent Systems, IS 2020

作者： Blidov, Hristo Doukovska, Lyubka Atanassov, Krassimir Institute of Information and Communication Technologies Bulgarian Academy of Sciences Department of Intelligent Systems Acad. G. Bonchev Str. Bl. 2 Sofia1113 Bulgaria Dept. of Bioinformatics and Mathematical Modelling Institute of Biophysics and Biomedical Engineering Bulgarian Academy of Sciences Bl. 105 Acad. G. Bonchev Str. Sofia1113 Bulgaria Intelligent Systems Laboratory Prof. Asen Zlatarov University Burgas8010 Bulgaria

ISBN: (纸本)9781728154565

In the present paper an application to the apparatus of generalized nets is proposed for modeling the first phase of the general claim process. the advantages of using such model are very different, some of them are expressed in helping to detect and eliminate unnecessary complications in the process itself, leading to its simplification and optimization, presenting a complex process simpler and more understandable, for scientific and teaching needs etc. © 2020 IEEE.

关键词： General claim process Generalizexd net Model

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Survey: Big Data Application in biomedical Research 2018

Survey: Big Data Application in Biomedical Research

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10th international conference on Computer and Automation engineering (ICCAE)

作者： Bachiller, Yvonne Busch, Peter Kavakli, Manolya Hamey, Len Dept Comp 33 Wilding St Sydney NSW Australia Macquarie Univ Dept Comp Sydney NSW 2109 Australia

ISBN: (纸本)9781450364102

In recent years, the emergence of diverse applications created a plethora of data and immense sources that can be applied in varying areas of the industry worldwide escalating its capabilities including biomedicine. Subsequently, analytical tools loomed to leverage the availability of massive data to analyze and elicit meaningful information to improve biomedical research and enhance healthcare systems. Algorithms applied in these analytical tools supplements the prognosis of diseases and personalized treatment of fatal diseases. this survey will evaluate algorithms used in bio medical research for personalized precision medicine, dissect the characteristics that made breakthrough in improving the efficiency of the analytical tool and identify the possible applicability in other diseases. It will focus on the machine learning and deep learning algorithms, both supervised and unsupervised that is applied in terminal diseases.

关键词： Big data machine learning deep learning algorithms disease diagnosis biomedicine

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Data Integration in the Life Sciences - 10th international conference, DILS 2014, proceedings

Data Integration in the Life Sciences - 10th International C...

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10th international conference on Data Integration in the Life Sciences, DILS 2014

ISBN: (纸本)9783319085890

the proceedings contain 14 papers. the topics discussed include: an asset management approach to continuous integration of heterogeneous biomedical data;mining linked open data: a case study with genes responsible for intellectual disability;data integration between Swedish national clinical health registries and biobanks using an availability system;data management experiences and best practices from the perspective of a plant research institute;a semantic web faceted search system for facilitating building of biodiversity and ecosystems services;handling multiple foci in graph databases;completing the is-a structure of biomedical ontologies;annotation-based feature extraction from sets of SBML models;REX - a tool for discovering evolution trends in ontology regions;discovering relations between indirectly connected biomedical concepts;and exploiting semantics from ontologies and shared annotations to partition linked data.

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Blockchain infrastructure and services for biomedical applications 10

Blockchain infrastructure and services for biomedical applic...

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10th international conference on Electrical, Electronic and Computing engineering, IcETRAN 2023

作者： Bogdanović, Zorica Labus, Aleksandra Despotović-Zrakić, Marijana Bjelica, Danijel Bjelica, Artur University of Belgrade Faculty of Organizational Sciences Belgrade Serbia University of Novi Sad Faculty of Medicine Novi Sad Serbia

ISBN: (纸本)9798350307115

Characteristics of blockchain technologies, such as decentralization, anonymity, auditability, transparency, reliability and immutability, have inspired numerous potential applications in the field of biomedicine. the goal of this research is to point out the possibilities of using blockchain technologies in biomedical applications, with a focus on extended medical supply chain management and transparent end-to-end data provisioning. As a possible approach, we propose a blockchain-based platform for storing data from the medical supply chain, data about and measured using various medical devices, patient medical records, personal health records, sensor data, and others, in order to provide all stakeholders with access to relevant and accurate data and raise the level of trust. We present the components needed for the implementation of the proposed system. Finally, we discuss the benefits and challenges related to the implementation of the proposed system.) © 2023 IEEE.

关键词： Smart contract

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Effects of triadimefon on the metabolism of cultured hepatocytes

Effects of triadimefon on the metabolism of cultured hepatoc...

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10th IEEE international conference on bioinformatics and Bioengineering, BIBE-2010

作者： Iyer, Vidya V. Androulakis, Ioannis P. Roth, Charles M. Ierapetritou, Marianthi G. Department of Chemical and Biochemical Engineering Rutgers University Piscataway NJ United States Department of Biomedical Engineering Rutgers University Piscataway NJ United States

ISBN: (纸本)9780769540832

the liver, being the major site of metabolism, plays a critical role in xenobiotic biotransformation and clearance. Quantifying the links between central hepatic and xenobiotic metabolism is critical to understanding toxicant-induced hepatic injury. Conazoles are a class of azole fungicides used to prevent fungal growth in fruits, vegetables and seeds, and for the treatment of fungal infections. Certain conazoles (such as triadimefon) are found to be tumorigenic in rats and mice. In this study, cultured primary rat hepatocytes were treated to varying doses (

关键词： Cells

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On constructing thermodynamically consistent parametrizations of kinetic models

On constructing thermodynamically consistent parametrization...

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10th IEEE international conference on bioinformatics and Bioengineering, BIBE-2010

作者： Jenkinson, W. Garrett Goutsias, John Whitaker Biomedical Engineering Institute Johns Hopkins University Baltimore MD 21218 United States

ISBN: (纸本)9780769540832

Experimental construction of biochemical reaction systems that model cellular behavior often leads to kinetic parameter values that do not satisfy important thermodynamic constraints, thus resulting in models that are not physically realizable. In this paper, we propose a method that takes thermodynamically infeasible published kinetic parameter values and recomputes a new set of thermodynamically consistent values. the method is based on formulating and implementing an appropriate constrained optimization problem by assuming that the molecular dynamics produced by the published values are "noisy" versions of the corresponding dynamics produced by the thermodynami-cally consistent "true" values. © 2010 IEEE.

关键词： Kinetic parameters

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Dynamic Cluster-based Retrieval and Discovery for biomedical Literature 19

Dynamic Cluster-based Retrieval and Discovery for Biomedical...

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10th ACM international conference on bioinformatics, Computational Biology and Health Informatics (ACM-BCB)

作者： Ortiz, Michael Segundo Kim, Heejun Wang, Mengqian Seki, Kazuhiro Mostafa, Javed Univ N Carolina Carolina Hlth Informat Program Chapel Hill NC 27515 USA Univ N Carolina Sch Informat & Lib Sci Chapel Hill NC 27515 USA Konan Univ Dept Intelligence & Informat Kobe Hyogo Japan Univ N Carolina Sch Informat & Lib Sci Carolina Hlth Informat Program Chapel Hill NC 27515 USA

ISBN: (纸本)9781450366663

Due to increased specialization and experimentation, the volume of biomedical literature is rapidly increasing, where the current modalities of search and retrieval system can no longer support effective and efficient knowledge discovery. Standard information retrieval systems such as PubMed make assumptions as to users' prior knowledge and expect them to formulate a proper query term for the information they are looking for. there exist user feedback mechanisms to help users reformulate their queries, which still assumes that users know how the search results could be effectively narrowed down by way of additional keywords and/or filters. As an alternative, we revisit the Scatter/Gather information retrieval paradigm. Specifically, we explore a real-time dynamic cluster-based document browsing approach in the biomedical domain, discuss the system architecture involving keyword discovery and dynamic clustering, and present a working prototype with a relevant use case in comparison with a standard ranking-based information retrieval system.

关键词： exploratory search unsupervised learning information retrieval biomedicine

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Extracting Co-mention features from biomedical literature for automated protein phenotype prediction using PHENOstruct 10

Extracting Co-mention features from biomedical literature fo...

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10th international conference on bioinformatics and Computational Biology, BICOB 2018

作者： Shahri, Morteza Pourreza Kahanda, Indika Gianforte School of Computing Montana State University BozemanMT59717 United States

ISBN: (纸本)9781943436118

Human Phenotype Ontology (HPO) is a recently introduced standard vocabulary for describing disease-related phenotypic abnormalities in human. Since experimental determination of HPO categories for human proteins is a highly resource-consuming task, developing automated tools that can accurately predict HPO categories has gained interest recently. In our previous work, we developed PHENOstruct, an automated phenotype prediction tool that uses input features generated from heterogeneous data sources including standard bag-of-words features extracted from biomedical literature. In this work, we introduce novel co-mention features which are based on co-occurrences of protein names and HPO terms within a specified span of text. Our experimental results indicate that utilizing co-mentions significantly improves the overall performance and that the most effective span is the paragraph-level. this is the first study that uses a knowledge-based approach for generating literature features for the task of automated protein phenotype prediction. these findings have implications for practitioners interested in developing automated biocuration pipelines for phenotypes. © 2018 ISCA, BICOB.

关键词： Proteins

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Issues in architectural modeling and evolution in the know-it-all case study 10

Issues in architectural modeling and evolution in the know-i...

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10th IEEE international conference and Workshop on the engineering of Computer-Based Systems

作者： Butler, G Shen, X Xu, LA Concordia Univ Dept Comp Sci Montreal PQ H3G 1M8 Canada

ISBN: (纸本)0769519172

the Know-It-All Project is investigating methodologies for the development, application, and evolution of frameworks. A concrete framework for database management systems is being developed as a case study for the methodology research. the methodology revolves around a set of models for the domain, the functionality, the architecture, the design, and the code. these models reflect the common and variable features of the domain. there are several issues with respect to architecture that we have encountered and are exploring. these include (1) the choice of models for the architecture;(2) the design of the architecture and its evaluation;(3) the evolution of the architecture by extending the concept of refactoring from source code to architecture;and (4) the modeling of variation in architectures across the product line. the point of the paper is to report on the status of architectural modeling in our case study and to highlight issues still to be resolved.

关键词： Application software bioinformatics Computer aided software engineering Computer architecture Concrete Data models Database systems Object oriented databases Object oriented modeling Software architecture

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