Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence
of disruptive technical advances and impressive experimental results, notably in the field of …

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 …

Purpose Radiation therapy treatment planning is a time‐consuming and iterative manual
process. Consequently, plan quality varies greatly between and within institutions. Artificial …

Purpose Although large datasets are available, to learn a robust dose prediction model from
a limited dataset still remains challenging. This work employed cascaded deep learning …

Recently, artificial intelligence technologies and algorithms have become a major focus for
advancements in treatment planning for radiation therapy. As these are starting to become …

Automatic and accurate dose distribution prediction plays an important role in radiotherapy
plan. Although previous methods can provide promising performance, most methods did not …

Background and purpose Geometric information such as distance information is essential for
dose calculations in radiotherapy. However, state-of-the-art dose prediction methods use …

Purpose This study aimed to use deep learning–based dose prediction to assess head and
neck (HN) plan quality and identify suboptimal plans. Methods and Materials A total of 245 …

Purpose Deep learning–based knowledge‐based planning (KBP) methods have been
introduced for radiotherapy dose distribution prediction to reduce the planning time and …

Radiation therapy (RT) is currently the main clinical treatment of tumors. Before treatment
initiation, precise delineation of the planned target volume (PTV) and organs at risk (OAR) is …