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Data Mining in Medical and Biological Research

By Giannopoulou Eugenia, G.

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Book Id: WPLBN0003842490
Format Type: PDF eBook :
File Size:
Reproduction Date: 2015

Title: Data Mining in Medical and Biological Research  
Author: Giannopoulou Eugenia, G.
Volume:
Language: English
Subject: Biological Research, Ai and Robotics, Programming
Collections: Online Programming Books
Historic
Publication Date:
2008
Publisher: Intech

Citation

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Eugenia, G. (2008). Data Mining in Medical and Biological Research. Retrieved from http://kindle.worldlibrary.net/


Description
Description: It consists of seventeen chapters, twelve related to medical research and five focused on the biological domain, which describe interesting applications, motivating progress and worthwhile results. We hope that the readers will benefit from this book and consider it as an excellent way to keep pace with the vast and diverse advances of new research efforts.

Table of Contents
TOC : Discovery of the Latent Supportive Relevance in Medical Data Mining - Intelligent Decision Support System for Classification of Eeg Signals Using Wavelet Coefficients - Data Mining for DNA Viruses with Breast Cancer and its Limitation - Building Ontology from Knowledge Base Systems - Building Clinical Trust in Automated Knowledge Acquisition - Radiology Data Mining Applications Using Imaging Informatics - Application of Data Mining and Text Mining to the Analysis of Medical near Miss Cases - Interactive Knowledge Discovery for Temporal Lobe Epilepsy - Monitoring Human Resources of a Public Health-Care System through Intelligent Data Analysis and Visualization - Data and Mined-Knowledge Interoperability in eHealth Systems - A Scalable Healthcare Integrated Platform (SHIP) and Key Technologies for Daily Application - A Mobile Device Based ECG Analysis System - A New Definition and Look at DNA Motif - Data Mining Applications in the Post-Genomic Era - Topological Analysis of Cellular Networks - Biomedical Literature Mining for Biological Databases Annotation - Social Data Mining to Improve Bioinspired Intelligent Systems.


 

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