A functional supervised learning approach to the study of blood pressure data.

Journal: Statistics in medicine
Published Date:

Abstract

In this work, a functional supervised learning scheme is proposed for the classification of subjects into normotensive and hypertensive groups, using solely the 24-hour blood pressure data, relying on the concepts of Fréchet mean and Fréchet variance for appropriate deformable functional models for the blood pressure data. The schemes are trained on real clinical data, and their performance was assessed and found to be very satisfactory.

Authors

  • Georgios I Papayiannis
    Department of Statistics, Athens University of Economics & Business, Athens, Greece.
  • Emmanuel A Giakoumakis
    Department of Informatics, Athens University of Economics & Business, Athens, Greece.
  • Efstathios D Manios
    Faculty of Medicine, National & Kapodistrian University of Athens, Athens, Greece.
  • Spyros D Moulopoulos
    Faculty of Medicine, National & Kapodistrian University of Athens, Athens, Greece.
  • Kimon S Stamatelopoulos
    Faculty of Medicine, National & Kapodistrian University of Athens, Athens, Greece.
  • Savvas T Toumanidis
    Faculty of Medicine, National & Kapodistrian University of Athens, Athens, Greece.
  • Nikolaos A Zakopoulos
    Faculty of Medicine, National & Kapodistrian University of Athens, Athens, Greece.
  • Athanasios N Yannacopoulos
    Department of Statistics, Athens University of Economics & Business, Athens, Greece.