Identifying homogeneous subgroups of patients and important features: a topological machine learning approach.

Journal: BMC bioinformatics
Published Date: Sep 20, 2021

Abstract

BACKGROUND: This paper exploits recent developments in topological data analysis to present a pipeline for clustering based on Mapper, an algorithm that reduces complex data into a one-dimensional graph.

Authors

  • Ewan Carr
    Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
  • Mathieu Carrière
    Inria Sophia-Antipolis, DataShape Team, Biot, France.
  • Bertrand Michel
    Ecole Centrale de Nantes, LMJL - UMR CNRS 6629, Nantes, France.
  • Frédéric Chazal
    Inria Saclay, Ile-de-France, Alan Turing Building, Palaiseau, France.
  • Raquel Iniesta
    Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. raquel.iniesta@kcl.ac.uk.

Keywords

External Resources

Popular Topics
Recent Journals