Table 2.

Main findings on patients’ psycho-cognitive attitudes toward Artificial Intelligence and communication issues.

References	Methods	Analysis	Main Variables
Ongena et al., 2020 [32]	Internet Survey with ad hoc 5-point Likert Scale	Quantitative analysis	Patients’ education levels shape trust and attitudes toward AI (low education is associated with low trust)
Adams et al., 2020 [33]	Patient engagement Workshop and interviews	Qualitative analysis (thematic analysis)	Trust is linked to the fear of the unknown uses of AI in radiology and the lack of human connections and empathy
Carter et al., 2019 [34]	Narrative review and perspective	Analysis of the ethical issues in doctor–patient communication	Knowledge and understanding of the way AI works are pivotal for the ethical use of AI
Mendelson, 2019 [35]	Narrative review and perspective	Analysis of the pros and cons of using AI in breast cancer imaging	Knowledge and education about AI for patients are as important as the empowerment of skills in communication for physicians
Kapoor et al., 2020 [36]	Overview of the applications of AI in radiology	Qualitative synthesis	Closed-loop communication to provide improved and personalized feedback for patients