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

Technological advances and clinical research over the past few decades have given
radiation oncologists the capability to personalize treatments for accurate delivery of …

With the advancement of treatment modalities in radiation therapy for cancer patients,
outcomes have improved, but at the cost of increased treatment plan complexity and …

The treatment planning process for patients with head and neck (H&N) cancer is regarded
as one of the most complicated due to large target volume, multiple prescription dose levels …

Purpose Automated and knowledge-based planning techniques aim to reduce variations in
plan quality. RapidPlan uses a library consisting of different patient plans to make a model …

Purpose The use of neural networks to directly predict three‐dimensional dose distributions
for automatic planning is becoming popular. However, the existing methods use only patient …

Radiotherapy is a discipline closely integrated with computer science. Artificial intelligence
(AI) has developed rapidly over the past few years. With the explosive growth of medical big …

Developers and users of artificial-intelligence-based tools for automatic contouring and
treatment planning in radiotherapy are expected to assess clinical acceptability of these …

We present a method to include robustness in a multi-criteria optimization (MCO) framework
for intensity-modulated proton therapy (IMPT). The approach allows one to simultaneously …

Online adaptive radiation therapy aims at adapting a patient's treatment plan to their current
anatomy to account for inter-fraction variations before daily treatment delivery. As this …