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Mining the Biomedical Literature

Craven offer a concise and accessible introduction to key ideas in biomedical text mining. The chapters cover such topics as the relevant sources;

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Biomedical Data Mining Using Machine Learning

Biomedical Data Mining is an ever growing area of Natural Laguage Processing. This book provides an introduction to this field and its;

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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics

of unstructured information. This big data challenge is most evident in biomedical informatics: the trend towards precision medicine has resulted in an;

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Advanced Data Mining and Applications

This book constitutes the proceedings of the 12th International Conference on Advanced Data Mining and Applications, ADMA 2016, held;

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Artificial Intelligence in Data Mining

Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI;

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Data Mining in Biomedical Imaging, Signaling, and Systems

, Signaling, and Systems provides an in-depth examination of the biomedical and clinical applications of data mining. It supplies examples;

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Data Mining in Biomedical Imaging, Signaling, and Systems

, Signaling, and Systems provides an in-depth examination of the biomedical and clinical applications of data mining. It supplies examples;

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Semantic Relation Extraction for Systems Biology

have been developed and improved. This work aimed at the development of a broad scale text mining system covering a multitude of relation as;

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Data Mining for Biomarker Discovery

. Discovering, managing, and interpreting knowledge of new biomarkers are challenging and attractive problems in the emerging field of biomedical;

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Computational Bioengineering and Bioinformatics

on biomechanics, biomedical decision support systems, data mining, personalized diagnostics, bio-signal processing, protein structure;

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Computational Bioengineering and Bioinformatics

on biomechanics, biomedical decision support systems, data mining, personalized diagnostics, bio-signal processing, protein structure;

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Internet of Things in Biomedical Engineering

Internet of Things in Biomedical Engineering presents the most current research in Internet of Things (IoT) applications for clinical;

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Signal Processing in Medicine and Biology

This book covers emerging trends in signal processing research and biomedical engineering, exploring the ways in which signal processing;

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Bioinformatics Research and Applications

This book constitutes the proceedings of the 13th International Symposium on Bioinformatics Research and Applications, ISBRA 2017, held;

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Medical Image Databases

Medical Image Databases covers the new technologies of biomedical imaging databases and their applications in clinical services;

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Trends and Applications in Knowledge Discovery and Data Mining

Knowledge Discovery and Data Mining (PAKDD) held in Tainan, Taiwan, in May 2014. The 73 revised papers presented were carefully reviewed and;

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Computational Modeling in Bioengineering and Bioinformatics

cover biomechanics and bioimaging, biomedical decision support system, data mining, personalized diagnoses, bio-signal processing, protein;

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What are the roles, actions and positions of non-formal biomedical prescribers and providers in developing countries? A systematic literature review

What Are the Roles, Actions and Positions of Non-Formal Biomedical Prescribers and Providers in Developing Countries? a Systematic;

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Proceedings Fourth International Conference on Information Processing

Recognition Computer Communication Networks Hardware and Optimization Data Mining Software Engineering Distributed Systems Biomedical;

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Biological Data Mining

biomedical applications. This volume examines the concepts, problems, progress, and trends in developing and applying new data mining techniques;

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Biological Data Mining

biomedical applications. This volume examines the concepts, problems, progress, and trends in developing and applying new data mining techniques;

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Data Mining

knowledge from these data falls far behind our pace of collecting the data. Data Mining: Theories, Algorithms, and Examples introduces and explains;

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Data Mining

knowledge from these data falls far behind our pace of collecting the data. Data Mining: Theories, Algorithms, and Examples introduces and explains;

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Robust Data Mining

can be found in data acquired with biomedical instruments or other experimental techniques. Integration of robust optimization in the existing;

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Temporal Data Mining

prediction. The book also explores the use of temporal data mining in medicine and biomedical informatics, business and industrial applications, web;

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Temporal Data Mining

prediction. The book also explores the use of temporal data mining in medicine and biomedical informatics, business and industrial applications, web;

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Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These;

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