ESTRO 2024 - Abstract Book

S2859

Interdisciplinary - Health economics & health services research

ESTRO 2024

Conclusion:

The survey results indicated a relatively high level of trust in AI. Our follow-up analysis yielded similar findings. The inconsistency of our findings with the literature suggests that trust in AI within RT is higher than in other medical disciplines. RT stands out as a technology-driven field, potentially making RT professionals more receptive and possibly educated to AI compared to clinicians in other medical domains. However, although trust is higher than in other domains it is important to note that the implementation of AI applications in RT also is still relatively limited. Overcoming the barriers to AI implementation is, thus, imperative. Our subsequent analyses underscored the importance of thorough AI validation, as well as the need for explainability, education, and reproducibility. To gain a deeper understanding of the factors influencing clinicians' willingness to adopt AI, our future efforts will involve conducting in-depth interviews with RT professionals.

Keywords: Trust, Artificial Intelligence

References:

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[2] J. Zhang et al., “An interactive dashboard to track themes, development maturity, and global equity in clinical artificial intelligence research.” medRxiv, p. 2021.11.23.21266758, Nov. 24, 2021. doi: 10.1101/2021.11.23.21266758.

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