Table 4.

Other factors related to acceptance (N=77) of medical AI^a applications (14/32, 43.8%, studies).

Factor category and factors from the rapid review		Umbrella factors used in the survey
Technology-related factors
	Performance expectancy (n=4, 28.6%); design and output quality (n=4, 28.6%); accuracy (n=2, 14.3%); efficiency (n=1, 7.1%)	Performance of AI applications in medicine (reproducibility of outcomes, accuracy)
	Perceived ease of use (n=2, 14.3%); user-friendliness (n=2, 14.3%); actual system use (n=1, 7.1%); compatibility (n=1, 7.1%); facilitating conditions (n=1, 7.1%)	Possibility of integration of AI applications into existing clinical workflows
	Perceived risk (n=1, 7.1%)	Clear balance of risks and benefits of the AI application
	Transparency (n=3, 21.4%); explainability (n=2, 14.3%); evidence strength (n=1, 7.1%); trustworthiness (n=1, 7.1%)	Explainability and transparency of the processes and outcomes
Legal and ethical factors
	Adequate regulations, legislation and governance (n=2, 14.3%); ethical risks (n=1, 7.1%); political support (n=1, 7.1%)	Adequacy of the regulations and governance of AI applications in medicine
	Data protection/security (n=2, 14.3%); patients’ consent to the continuous collection and processing of data (n=1, 7.1%)	Data use transparency
	Accountability and responsibility (n=2, 14.3%); tort liability (n=1, 7.1%)	Clear accountability and responsibility of the AI application (machine vs human responsibility)
Additional factors
	Replacement of doctor/lack of human touch and moral support when evaluated by AI alone (n=1, 7.1%)	Impact on job availability (machines replacing humans)
	Trust in AI applications (n=3, 21.4%)	Acceptance emerging from trust

^aAI: artificial intelligence.