Data Mining and Medical Knowledge Management: Cases and Applications. Este artículo no está disponible.
Idioma: inglés
Editorial: Igi Global Scientific Publishing, 2009
- Tapa dura
- Nuevo

Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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Vendedor de IberLibro desde 25 de marzo de 2015
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EUR 256,61
Descripción del artículo del vendedor
In English.
N° de ref. del artículo ria9781605662183_new
- Título
- Data Mining and Medical Knowledge Management: Cases and Applications
- Editorial
- Igi Global Scientific Publishing
- Año de publicación
- 2009
- Estado
- New
- Encuadernación
- Encuadernación de tapa dura
- Idioma
- inglés
- ISBN 10
- 1605662186
- ISBN 13
- 9781605662183
- Peso del artículo
- 1480 gramos
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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Reseña del editor
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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