This paper is in the following e-collection/theme issue:

Artificial Intelligence (1189) Clinical Information and Decision Making (1315) Decision Support for Health Professionals (1129) Machine Learning (1373) Adoption and Change Management of eHealth Systems (670) Formative Evaluation of Digital Health Interventions (2194) Imaging Informatics (182) User Needs and Competencies (271)

Published on in Vol 23, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27122, first published .
Radiation Oncologists’ Perceptions of Adopting an Artificial Intelligence–Assisted Contouring Technology: Model Development and Questionnaire Study

Radiation Oncologists’ Perceptions of Adopting an Artificial Intelligence–Assisted Contouring Technology: Model Development and Questionnaire Study

Radiation Oncologists’ Perceptions of Adopting an Artificial Intelligence–Assisted Contouring Technology: Model Development and Questionnaire Study

Authors of this article:

Huiwen Zhai1, 2 Author Orcid Image ;   Xin Yang3 Author Orcid Image ;   Jiaolong Xue4, 5 Author Orcid Image ;   Christopher Lavender1 Author Orcid Image ;   Tiantian Ye6 Author Orcid Image ;   Ji-Bin Li7 Author Orcid Image ;   Lanyang Xu2 Author Orcid Image ;   Li Lin3 Author Orcid Image ;   Weiwei Cao8 Author Orcid Image ;   Ying Sun3 Author Orcid Image
Article Authors Cited by (20) Tweetations (4) Metrics

Journals

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  12. Alanzi T, Alotaibi R, Alajmi R, Bukhamsin Z, Fadaq K, AlGhamdi N, Bu Khamsin N, Alzahrani L, Abdullah R, Alsayer R, Al Muarfaj A, Alanzi N. Barriers and Facilitators of Artificial Intelligence in Family Medicine: An Empirical Study With Physicians in Saudi Arabia. Cureus 2023 View
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