Table 2.

Technological characteristics and human factors influencing and shaping the relationship and collaboration between AI-enabled clinical decision support systems (CDSSs) and human actors.

Parameters		Definition	Study
Technological characteristics
	Training data quality	Information used for training of AI-enabled CDSSs to create a truthful, reliable, and representative system	[53]
	Performance	The accuracy and reliability of an AI-enabled CDSS	[30,55]
	Explainability or transparency	An AI-enabled CDSS' ability to ensure that a human actor understands the processes that lead to the prediction and the prediction itself	[30,31,54-56]
	Adapted output or adaptability	The degree to which an AI-enabled CDSS fits into a specific context or environment according to the subdimensions simplicity, granularity, and concreteness	[31]
Human factors
	Medical expertise	The degree of medical experience of a human actor within the context of collaboration with an AI-enabled CDSS	[30,31,54,57]
	Technological expertise	The degree of technological experience of a human actor with regard to an AI-enabled CDSS	[30,54]
	Personality	A medical professional’s attributes and characteristics that influence the interaction with AI-enabled a CDSS	[54]
	Cognitive biases	The cognitive processes that alter rational decision-making and perceptions of an AI-enabled CDSS	[30,54]
	Trust	The subjective impression of a medical professional that an AI-enabled CDSS is truthful and reliable	[30,53,54]