Literature DB >> 32115386

The Impact of Artificial Intelligence and Machine Learning in Radiation Therapy: Considerations for Future Curriculum Enhancement.

Crispen Chamunyonga1, Christopher Edwards2, Peter Caldwell2, Peta Rutledge2, Julie Burbery2.   

Abstract

Artificial intelligence (AI) and machine learning (ML) approaches have caught the attention of many in health care. Current literature suggests there are many potential benefits that could transform future clinical workflows and decision making. Embedding AI and ML concepts in radiation therapy education could be a fundamental step in equipping radiation therapists (RTs) to engage in competent and safe practice as they utilise clinical technologies. In this discussion paper, the authors provide a brief review of some applications of AI and ML in radiation therapy and discuss pertinent considerations for radiation therapy curriculum enhancement. As the current literature suggests, AI and ML approaches will impose changes to routine clinical radiation therapy tasks. The emphasis in RT education could be on critical evaluation of AI and ML application in routine clinical workflows and gaining an understanding of the impact on quality assurance, provision of quality of care and safety in radiation therapy as well as research. It is also imperative RTs have a broader understanding of AI/ML impact on health care, including ethical and legal considerations. The paper concludes with recommendations and suggestions to deliberately embed AI and ML aspects in RT education to empower future RT practitioners.
Copyright © 2020. Published by Elsevier Inc.

Keywords:  Radiation therapist; artificial intelligence; education; machine learning

Year:  2020        PMID: 32115386     DOI: 10.1016/j.jmir.2020.01.008

Source DB:  PubMed          Journal:  J Med Imaging Radiat Sci        ISSN: 1876-7982


  7 in total

1.  Bringing Ophthalmic Graduate Medical Education into the 2020s with Information Technology.

Authors:  Emily Cole; Nita G Valikodath; April Maa; R V Paul Chan; Michael F Chiang; Aaron Y Lee; Daniel C Tu; Thomas S Hwang
Journal:  Ophthalmology       Date:  2020-12-24       Impact factor: 12.079

2.  Maintenance and Management Technology of Medical Imaging Equipment Based on Deep Learning.

Authors:  Bin Liu; Lingli Tong; Yanmei Liu; Zhizhang Guo
Journal:  Contrast Media Mol Imaging       Date:  2022-07-01       Impact factor: 3.009

3.  Volumetric modulated arc therapy dose prediction and deliverable treatment plan generation for prostate cancer patients using a densely connected deep learning model.

Authors:  Michael Lempart; Hunor Benedek; Christian Jamtheim Gustafsson; Mikael Nilsson; Niklas Eliasson; Sven Bäck; Per Munck Af Rosenschöld; Lars E Olsson
Journal:  Phys Imaging Radiat Oncol       Date:  2021-08-05

4.  Machine learning applications in radiation oncology: Current use and needs to support clinical implementation.

Authors:  Charlotte L Brouwer; Anna M Dinkla; Liesbeth Vandewinckele; Wouter Crijns; Michaël Claessens; Dirk Verellen; Wouter van Elmpt
Journal:  Phys Imaging Radiat Oncol       Date:  2020-11-30

Review 5.  Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review.

Authors:  Rebecca Charow; Tharshini Jeyakumar; Sarah Younus; Elham Dolatabadi; Mohammad Salhia; Dalia Al-Mouaswas; Melanie Anderson; Sarmini Balakumar; Megan Clare; Azra Dhalla; Caitlin Gillan; Shabnam Haghzare; Ethan Jackson; Nadim Lalani; Jane Mattson; Wanda Peteanu; Tim Tripp; Jacqueline Waldorf; Spencer Williams; Walter Tavares; David Wiljer
Journal:  JMIR Med Educ       Date:  2021-12-13

6.  Assessment of efficacy in automated plan generation for Varian Ethos intelligent optimization engine.

Authors:  Shyam Pokharel; Abilio Pacheco; Suzanne Tanner
Journal:  J Appl Clin Med Phys       Date:  2022-01-27       Impact factor: 2.102

Review 7.  Practical considerations for prostate hypofractionation in the developing world.

Authors:  Michael Yan; Andre G Gouveia; Fabio L Cury; Nikitha Moideen; Vanessa F Bratti; Horacio Patrocinio; Alejandro Berlin; Lucas C Mendez; Fabio Y Moraes
Journal:  Nat Rev Urol       Date:  2021-08-13       Impact factor: 14.432

  7 in total

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