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Data Mining Applications in Engineering and Medicine

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Book Series: 2012-08-29 ISBN: 9789535107200 9789535142867 Year: Pages: 338 DOI: 10.5772/2616 Language: English
Publisher: IntechOpen
Subject: Computer Science
Added to DOAB on : 2019-10-03 07:51:49

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Data Mining Applications in Engineering and Medicine targets to help data miners who wish to apply different data mining techniques. Data mining generally covers areas of statistics, machine learning, data management and databases, pattern recognition, artificial intelligence, etc. In this book, most of the areas are covered by describing different applications. This is why you will find here why and how Data Mining can also be applied to the improvement of project management. Since Data Mining has been widely used in a medical field, this book contains different chapters reffering to some aspects and importance of its use in the mentioned field: Incorporating Domain Knowledge into Medical Image Mining, Data Mining Techniques in Pharmacovigilance, Electronic Documentation of Clinical Pharmacy Interventions in Hospitals etc. We hope that this book will inspire readers to pursue education and research in this emerging field.

Big Data on Real-World Applications

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ISBN: 9789535124894 9789535124900 9789535141945 Year: Pages: 124 DOI: 10.5772/61396 Language: English
Publisher: IntechOpen
Subject: Computer Science
Added to DOAB on : 2019-10-03 07:51:49

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As technology advances, high volumes of valuable data are generated day by day in modern organizations. The management of such huge volumes of data has become a priority in these organizations, requiring new techniques for data management and data analysis in Big Data environments. These environments encompass many different fields including medicine, education data, and recommender systems. The aim of this book is to provide the reader with a variety of fields and systems where the analysis and management of Big Data are essential. This book describes the importance of the Big Data era and how existing information systems are required to be adapted to face up the problems derived from the management of massive datasets.

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