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Medical Informatics: Knowledge Management and Data Mining in Biomedicine

Hsinchun Chen ; Sherrilynne S. Fuller ; Carol Friedman ; William Hersh (eds.)

Resumen/Descripción – provisto por la editorial

No disponible.

Palabras clave – provistas por la editorial

Health Informatics; IT in Business; Bioinformatics; Information Systems and Communication Service; Biomedical Engineering; e-Commerce/e-business

Disponibilidad
Institución detectada Año de publicación Navegá Descargá Solicitá
No detectada 2005 SpringerLink

Información

Tipo de recurso:

libros

ISBN impreso

978-0-387-24381-8

ISBN electrónico

978-0-387-25739-6

Editor responsable

Springer Nature

País de edición

Reino Unido

Fecha de publicación

Información sobre derechos de publicación

© Springer Science+Business Media, Inc. 2005

Tabla de contenidos

Joint Learning Using Multiple Types of Data and Knowledge

Zan Huang; Hua Su; Hsinchun Chen

This chapter discusses joint learning research in biomedical domains. A brief review of the field of joint learning research is given, with emphases on the large-scale data and knowledge resources used for learning and the central biological questions involved. Two representative joint learning case studies are presented with algorithmic details. The two case studies involved two representative joint learning tasks, protein function classification and regulatory network learning, and two important algorithmic frameworks for joint learning, the kernel-based framework and probabilistic graphical models. A wide range of biological data and existing knowledge was also involved in these two studies.

Unit III - Text Mining and Data Mining | Pp. 593-624