Applications of artificial intelligence for machine-and patient-specific quality assurance in radiation therapy: current status and future directions

T Ono, H Iramina, H Hirashima, T Adachi… - Journal of Radiation …, 2024 - academic.oup.com
Abstract Machine-and patient-specific quality assurance (QA) is essential to ensure the
safety and accuracy of radiotherapy. QA methods have become complex, especially in high …

Prospective deployment of an automated implementation solution for artificial intelligence translation to clinical radiation oncology

CE Kehayias, Y Yan, D Bontempi, S Quirk… - Frontiers in …, 2024 - frontiersin.org
Introduction Artificial intelligence (AI)-based technologies embody countless solutions in
radiation oncology, yet translation of AI-assisted software tools to actual clinical …

Detection of suboptimal IMRT treatment plan using machine learning on radiomics features of dose distribution for lung cancers

J Valerian, DSK Sihono - Radiation Physics and Chemistry, 2023 - Elsevier
Quality assurance in radiotherapy is an important process so that the use of radiation
provides maximum benefits. Currently, the implementation of machine learning (ML) in the …

Artificial Intelligence-Assisted Delineation for Postoperative Radiotherapy in Patients with Lung Cancer: A Prospective, Multi-Center, Cohort Study

Z Han, Y Wang, W Wang, T Zhang, J Wang… - Multi-Center, Cohort … - papers.ssrn.com
Background: Postoperative radiotherapy (PORT) is an important treatment for lung cancer
patients with poor prognostic features, but accurate delineation of the clinical target volume …

Kalman Filter in Quality Assurance in Radiotherapy: A Practical Application for Daily Dose Quality Control

JB Billet, C Mazzara, A Barraud, D Reynard - Available at SSRN 5001876 - papers.ssrn.com
This study proposes to improve the daily dose quality control of radiotherapy equipment with
a Kalman filter approach. The entire radiation production system is then considered as a …

[HTML][HTML] Home Evolving Standards of Care Artificial Intelligence in Thoracic Radiation Oncology: Patient Evaluation and Treatment Planning

G Lee, F Haugg, RH Mak - ilcn.org
Author's Note: Our previous article, Demystifying AI: Current Insights on Artificial Intelligence
in Thoracic Oncology, reviews the foundational principles of AI, AI methods, and the role of …

[引用][C] PP02. 02 EXTERNALVALIDATION OF AN AI-BASED TOOL FOR THE EARLY DETECTION OF RADIOTHERAPY TREATMENT PLANNING ERRORS–AN …

P Kalendralis, S Luk, A Kalet, A Dekker, T Piotrowski… - Physica Medica, 2024 - Elsevier