Automatic quality assurance of radiotherapy treatment plans using Bayesian networks: A multi-institutional study.

ABSTRACT:

Purpose

Artificial intelligence applications in radiation oncology have been the focus of study in the last decade. The introduction of automated and intelligent solutions for routine clinical tasks, such as treatment planning and quality assurance, has the potential to increase safety and efficiency of radiotherapy. In this work, we present a multi-institutional study across three different institutions internationally on a Bayesian network (BN)-based initial plan review assistive tool that alerts radiotherapy professionals for potential erroneous or suboptimal treatment plans.

Methods

Clinical data were collected from the oncology information systems in three institutes in Europe (Maastro clinic - 8753 patients treated between 2012 and 2020) and the United States of Americ

SUBMITTER: Kalendralis P 

PROVIDER: S-EPMC10012863 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature