Bayesian networks in healthcare: Distribution by medical condition

Artif Intell Med. 2020 Jul:107:101912. doi: 10.1016/j.artmed.2020.101912. Epub 2020 Jun 10.

Abstract

Bayesian networks (BNs) have received increasing research attention that is not matched by adoption in practice and yet have potential to significantly benefit healthcare. Hitherto, research works have not investigated the types of medical conditions being modelled with BNs, nor whether there are any differences in how and why they are applied to different conditions. This research seeks to identify and quantify the range of medical conditions for which healthcare-related BN models have been proposed, and the differences in approach between the most common medical conditions to which they have been applied. We found that almost two-thirds of all healthcare BNs are focused on four conditions: cardiac, cancer, psychological and lung disorders. We believe there is a lack of understanding regarding how BNs work and what they are capable of, and that it is only with greater understanding and promotion that we may ever realise the full potential of BNs to effect positive change in daily healthcare practice.

Keywords: Bayesian networks; Healthcare; Medical conditions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bayes Theorem
  • Delivery of Health Care*
  • Humans