Data Mining in Clinical Medicine

  • Carlos Fernández-Llatas
  • Juan Miguel García-Gómez

Part of the Methods in Molecular Biology book series (MIMB, volume 1246)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Innovative Data Mining Techniques for Clinical Medicine

    1. Front Matter
      Pages 1-1
    2. Elies Fuster-Garcia, Adrián Bresó, Juan Martínez Miranda, Juan Miguel García-Gómez
      Pages 3-17
    3. Salvador Tortajada, Montserrat Robles, Juan Miguel García-Gómez
      Pages 57-78
    4. Carlos Fernandez-Llatas, Bernardo Valdivieso, Vicente Traver, Jose Miguel Benedi
      Pages 79-88
    5. Lucia Sacchi, Arianna Dagliati, Riccardo Bellazzi
      Pages 89-105
  3. Mining Medical Data Over Internet

    1. Front Matter
      Pages 107-107
    2. Johan Gustav Bellika, Torje Starbo Henriksen, Kassaye Yitbarek Yigzaw
      Pages 109-122
    3. Jose Enrique Borras-Morell
      Pages 123-130
    4. C. L. Sanchez-Bocanegra, F. Sanchez-Laguna, J. L. Sevillano
      Pages 131-146
    5. Carlos Fernandez-Llatas, Salvatore F. Pileggi, Gema Ibañez, Zoe Valero, Pilar Sala
      Pages 147-155
  4. New Applications of Data Mining in Clinical Medicine Problems

    1. Front Matter
      Pages 157-157
    2. Der-Ming Liou, Wei-Pin Chang
      Pages 175-189
    3. Miguel Rodrigo, Jorge Pedrón-Torecilla, Ismael Hernández, Alejandro Liberos, Andreu M. Climent, María S. Guillem
      Pages 217-235
    4. Adrián Bresó, Carlos Sáez, Javier Vicente, Félix Larrinaga, Montserrat Robles, Juan Miguel García-Gómez
      Pages 237-257
    5. Lenin-G. Lemus-Zúñiga, Esperanza Navarro-Pardo, Carmen Moret-Tatay, Ricardo Pocinho
      Pages 259-267
  5. Back Matter
    Pages 269-270

About this book


This volume complies a set of Data Mining techniques and new applications in real biomedical scenarios. Chapters focus on innovative data mining techniques, biomedical datasets and streams analysis, and real applications. Written in the highly successful Methods in Molecular Biology series format, chapters are thought to show to Medical Doctors and Engineers the new trends and techniques that are being applied to Clinical Medicine with the arrival of new Information and Communication technologies

Authoritative and practical, Data Mining in Clinical Medicine seeks to aid scientists with  new approaches and trends in the field.


Bayesian perspective Cloud Computing technologies Health Recommender systems LBER Sentiment Analysis automatic actigraphy pattern analysis biomedical data problems cancer metobolic models speech recognintion techniques

Editors and affiliations

  • Carlos Fernández-Llatas
    • 1
  • Juan Miguel García-Gómez
    • 2
  1. 1.Instituto Itaca, Universitat Politècnica de ValènciaValenciaSpain
  2. 2.Instituto Itaca, Universitat Politècnica de ValènciaValenciaSpain

Bibliographic information

  • DOI
  • Copyright Information Springer Science+Business Media New York 2015
  • Publisher Name Humana Press, New York, NY
  • eBook Packages Springer Protocols
  • Print ISBN 978-1-4939-1984-0
  • Online ISBN 978-1-4939-1985-7
  • Series Print ISSN 1064-3745
  • Series Online ISSN 1940-6029
  • Buy this book on publisher's site