Data mining, systems analysis, and optimization in biomedicine
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Data mining, systems analysis, and optimization in biomedicine Gainesville, Florida, U.S.A., 28-30 March 2007 by

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Published by American Institute of Physics in Melville, N.Y .
Written in English

Subjects:

  • Medical informatics -- Congresses,
  • Medicine -- Data processing -- Congresses,
  • Biology -- Data processing -- Congresses

Book details:

Edition Notes

Includes bibliographical references and index.

Statementeditors, Onur Seref, O. Erhun Kundakcioglu, Panos M. Pardalos.
GenreCongresses.
SeriesAIP conference proceedings -- 953, AIP conference proceedings -- no. 953.
ContributionsSeref, Onur., Kundakcioglu, O. Erhun., Pardalos, Panos M.
Classifications
LC ClassificationsR858.A2 D38 2007
The Physical Object
Paginationix, 318 p.:
Number of Pages318
ID Numbers
Open LibraryOL16474333M
ISBN 100735404674
ISBN 109780735404670
LC Control Number2007938607

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"This book is an in-depth look at ‘the development of appropriate methods for extracting useful information’ from data in biomedicine. is aimed at scientists and practitioners in the fields of biomedicine, engineering, mathematics, and computer science as well as graduate students and is appropriate for a variety of readers. . Request PDF | On Nov 1, , Onur Seref and others published Data Mining, Systems Analysis and Optimization in Biomedicine | Find, read and cite all the research you need on ResearchGate. Data Mining, Systems Analysis and Optimization in Biomedicine; Onur Seref, University of Florida, Department of Industrial and Systems Engineering, Gainesville, FL, USA ; O. Erhun Kundakcioglu, University of Florida, Department of Industrial and Systems Engineering, Gainesville, FL, USA ; Panos Pardalos, University of Florida, Industrial and. Data Mining in Biomedical Imaging, Signaling, and Systems provides an in-depth examination of the biomedical and clinical applications of data mining. It supplies examples of frequently encountered heterogeneous data modalities and details the applicability of data mining approaches used to address the computational challenges in analyzing.

Data Mining, Systems Analysis and Optimization in Biomedicine By Onur Seref, O Erhun Kundakcioglu and Panos Pardalos Topics: XX. Comments on: Optimization and data mining in biomedicine Article (PDF Available) in Top 17(2) December with 23 Reads How we measure 'reads'Author: Sergiy Butenko. The application of data mining in the domain of bioinformatics is explained. It also highlights some of the current challenges and opportunities of data mining in bioinformatics. Keywords: Data Mining, Bioinformatics, Protein Sequences Analysis, Bioinformatics Tools. 1. Introduction. Data Mining, System Products and Research Prototypes Although data mining is a young field with many issues that still need to be researched in depth, there are already great many off-the-shelf data mining system products and domain-specific data mining application software Size: 62KB.

  Medicine and biomedical sciences have become data-intensive fields, which, at the same time, enable the application of data-driven approaches and require sophisticated data analysis and data mining methods. Biomedical informatics provides a proper interdisciplinary context to integrate data and knowledge when processing available information Cited by:   Applying data-driven techniques to big health data can be of great benefit in the biomedical and healthcare domain, allowing identification and extraction of relevant information and reducing the time spent by biomedical and healthcare professionals and researchers who are trying to find meaningful patterns and new threads of by: 2. Medical Informatics: Knowledge Management and Data Mining in Biomedicine (Integrated Series in Information Systems (8)) th Edition by Hsinchun Chen (Editor), Sherrilynne S. Fuller (Editor), Carol Friedman (Editor), William Hersh (Editor) & 1 more/5(2). Information technology, as a rapidly evolving discipline in medical data science, with significant potential in future healthcare, and multimodal acquisition systems, mobile devices, sensors, and AI-powered applications has redefined the optimization of clinical processes. This book features an interdisciplinary collection of papers that have.