Machine Learning in Medicine Part Two /

Machine learning is concerned with the analysis of large data and multiple variables. However, it is also often more sensitive than traditional statistical methods to analyze small data. The first volume reviewed subjects like optimal scaling, neural networks, factor analysis, partial least squares,...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Cleophas, Ton J. (Autor), Zwinderman, Aeilko H. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Dordrecht : Springer Netherlands : Imprint: Springer, 2013.
Edición:1st ed. 2013.
Temas:
Medicine-Research.
Biology-Research.
Invertebrates.
Medical sciences.
Statistics .
Image processing-Digital techniques.
Computer vision.
Literacy.
Biomedical Research.
Invertebrate Zoology.
Health Sciences.
Statistics.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Introduction to Machine Learning Part Two
  • Two-stage Least Squares
  • Multiple Imputations
  • Bhattacharya Analysis
  • Quality-of-life (QOL) Assessments with Odds Ratios
  • Logistic Regression for Assessing Novel Diagnostic Tests against Control
  • Validating Surrogate Endpoints
  • Two-dimensional Clustering
  • Multidimensional Clustering
  • Anomaly Detection
  • Association Rule Analysis
  • Multidimensional Scaling
  • Correspondence Analysis
  • Multivariate Analysis of Time Series
  • Support Vector Machines
  • Bayesian Networks
  • Protein and DNA Sequence Mining
  • Continuous Sequential Techniques
  • Discrete Wavelet Analysis
  • Machine Learning and Common Sense
  • Statistical Tables
  • Index.

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