Deep self-supervised machine learning algorithms with a novel feature elimination and selection approaches for blood test-based multi-dimensional health risks classification.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Blood test is extensively performed for screening, diagnoses and surveillance purposes. Although it is possible to automatically evaluate the raw blood test data with the advanced deep self-supervised machine learning approaches, it has not been profoundly investigated and implemented yet.

Authors

  • Onder Tutsoy
  • Gizem Gul KoƧ
    Adana Alparslan Turkes Science and Technology University, Adana, Turkey.