The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment. Data Mining and Medical Knowledge Management: Cases and Applications presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies.
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Petr Berka is a full professor at the Department of Information and Knowledge Engineering, University of Economics and also works in the Centre of Biomedical Informatics, Institute of Computer Science, Academy of Sciences of the Czech Republic. His main research interests are machine learning, data mining and knowledge-based systems.
Jan Rauch is an associate professor at the Deptartment of Information and Knowledge Engineering, University of Economics and also works in the Centre of Biomedical Informatics, Institute of Computer Science, Academy of Sciences of the Czech Republic. His main research interest is data mining.
Djamel Abdelkader Zighed received his Master in Computer and Automatic Science in 1982 and his PhD in computer science in 1985 both from University Lyon I. He was as assistant professor at University Lyon 1 in 1984-1987. In 1987, he joined the University Lyon II where he worked as lecturer (1987-1991), professor (1991-2000) and 1st class professor (2000 - present). He is interested in data mining (including mining complex data), machine learning and knowledge engineering. He is the founder and was director (1995-2002) of the ERIC laboratory (laboratory for development of methods and software for knowledge engineering, and more specifically automatic Knowledge Discovery in Databases).
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment. Data Mining and Medical Knowledge Management: Cases and Applications presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies. Seller Inventory # 9781605662183
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