Quantifying Accuracy and Cost in Public Preferences for Artificial Intelligence in Radiation Therapy

Abstract

 

We read with great interest the recent article by Lewandowska and colleagues on public preferences for adopting artificial intelligence (AI) in radiation therapy, derived from a discrete choice experiment (DCE) of 533 Australian respondents. The study offers timely, practical evidence that the public places highest value on improved diagnostic accuracy and clinician oversight, while weighing trade-offs with cost, timeliness, and data use. We welcome the authors’ rigorous approach and would like to offer several constructive observations that, if clarified or extended, could strengthen the study’s interpretability and policy relevance.

 

Authors

Weihao Cheng Zekai Yu

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