Machine learning in medicine: a practical introduction.

Journal: BMC medical research methodology
Published Date:

Abstract

BACKGROUND: Following visible successes on a wide range of predictive tasks, machine learning techniques are attracting substantial interest from medical researchers and clinicians. We address the need for capacity development in this area by providing a conceptual introduction to machine learning alongside a practical guide to developing and evaluating predictive algorithms using freely-available open source software and public domain data.

Authors

  • Jenni A M Sidey-Gibbons
    Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ, UK.
  • Chris J Sidey-Gibbons
    Department of Surgery, Harvard Medical School, 25 Shattuck Street, Boston, 01225, Massachusetts, USA. cgibbons2@bwh.harvard.edu.