Real-time Online Probabilistic Medical Computation using Bayesian Networks

EasyChair Preprint 2744

Abstract

Advances in both computing power and novel Bayesian inference algorithms have enabled Bayesian Networks (BN) to be applied for decision-support in healthcare and other domains. This work presents CardiPro, a flexible, online application for interfacing with non-trivial causal BN models. Designed especially to make BN use easy for less-technical users like patients and clinicians, CardiPro provides near real-time probabilistic computation. CardiPro was developed as part of the PamBayesian research project (www.pambayesian.org) and represents the first of a new generation of online BN-based applications that may benefit adoption of AI-based clinical decision-support.

Keyphrases: Bayesian networks, Healthcare, mHealth

@booklet{EasyChair:2744,
  author    = {Scott Mclachlan and Haydn Paterson and Kudakwashe Dube and Evangelia Kyrimi and Eugene Dementiev and Martin Neil and Bridget Daley and Graham Hitman and Norman Fenton},
  title     = {Real-time Online Probabilistic Medical Computation using Bayesian Networks},
  howpublished = {EasyChair Preprint 2744},
  year      = {EasyChair, 2020}}