Artificial Intelligence (AI) is currently being introduced into different domains, including
medicine. Specifically in radiation oncology, machine learning models allow automation and …

Treatment planning plays an important role in the process of radiotherapy (RT). The quality
of the treatment plan directly and significantly affects patient treatment outcomes. In the past …

This paper surveys the data‐driven dose prediction methods investigated for knowledge‐
based planning (KBP) in the last decade. These methods were classified into two major …

Background. Creating a clinically acceptable plan in the time-sensitive clinic workflow of
brachytherapy is challenging. Deep learning-based dose prediction techniques have been …

Purpose Automated planning techniques aim to reduce manual planning time and inter-
operator variability without compromising the plan quality which is particularly challenging …

Purpose The purposes of this work are to (a) investigate whether the use of auto‐planning
and multiple iterations improves quality of head and neck (HN) radiotherapy plans;(b) …

Background and purpose Automatic approaches are widely implemented to automate dose
optimization in radiotherapy treatment planning. This study systematically investigates how …

Purpose To quantify inter-institute variability of Knowledge-Based (KB) models for right
breast cancer patients treated with tangential fields whole breast irradiation (WBI). Materials …

The increasing uptake of machine learning solutions for segmentation and planning leaves
no doubt that artificial intelligence (AI) will soon be providing input into a range of …

Purpose Although the knowledge-based dose-volume histogram (DVH) prediction has been
largely researched and applied in External Beam Radiation Therapy, it is still less …