Information discovery on electronic health records /

Exploiting the rich information found in electronic health records (EHRs) can faciliate better medical research and improve the quality of medical practice. Until now, a trivial amount of research has been published on the challenges of leveraging this information. Addressing these challenges, Infor...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Hristidis, Vagelis
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Boca Raton : Taylor & Francis, ©2010.
Colección:Chapman & Hall/CRC data mining and knowledge discovery series.
Temas:
Medical records > Data processing.
Data mining.
Confidential communications.
Electronic Health Records
Confidentiality
Data Mining
Dossiers médicaux > Informatique.
Exploration de données (Informatique)
Secret professionnel.
TECHNOLOGY & ENGINEERING > Biomedical.
MEDICAL > Family & General Practice.
MEDICAL > Allied Health Services > Medical Technology.
MEDICAL > Biotechnology.
MEDICAL > Lasers in Medicine.
Confidential communications
Data mining
Medical records > Data processing
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Overview of XML / Fernando Farfán and Vagelis Hristidis
  • Electronic Health Records / Fernando Farfán, Ramakrishna Varadarajan, and Vagelis Hristidis
  • Overview of Information Discovery Techniques on EHRs / Vagelis Hristidis
  • Data Quality and Integration Issues in Electronic Health Records / Ricardo João Cruz-Correia, Pedro Pereira Rodrigues, Alberto Freitas, Filipa Canario Almeida, Rong Chen, and Altamiro Costa-Pereira
  • Ethical, Legal, and Social Issues for EHR Data Protection / Reid Cushman
  • Searching Electronic Health Records / Ramakrishna Varadarajan, Vagelis Hristidis, Fernando Farfán, and Redmond Burke
  • Data Mining and Knowledge Discovery on EHRs / Donald J. Berndt, Monica Chiarini Tremblay, and Stephen L. Luther
  • Privacy-Preserving Information Discovery on EHRs / Li Xiong, James Gardner, Pawel Jurczyk, and James J. Lu
  • Real-Time and Mobile Physiological Data Analysis / Daniele Apiletti, Elena Baralis, Giulia Bruno, Tania Cerquitelli, and Alessandro Fiori
  • Medical Image Segmentation / Xiaolei Huang and Gavriil Tsechpenakis.

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