<status value="active"/> <experimental value="false"/> <date value="2026-07-31T11:07:29+00:00"/> <publisher value="Selina Adlberger"/> <description value="Codes identifying performance characteristics used to document the evaluation of an AI system."/> <caseSensitive value="true"/> <content value="complete"/> <count value="4"/> <concept> <code value="accuracy"/> <display value="Accuracy"/> <definition value="The proportion of evaluated cases for which the AI system produced the correct result."/> </concept> <concept> <code value="sensitivity"/> <display value="Sensitivity"/> <definition value="The proportion of relevant positive cases correctly identified by the AI system."/> </concept> <concept> <code value="specificity"/> <display value="Specificity"/> <definition value="The proportion of relevant negative cases correctly identified by the AI system."/> </concept> <concept> <code value="robustness"/> <display value="Robustness"/> <definition value="The ability of the AI system to maintain appropriate performance under variations, disturbances, or reasonably foreseeable conditions of use."/> </concept> </CodeSystem>

Generated Narrative: CodeSystem eu-ai-performance-metric-cs

This case-sensitive code system http://example.org/fhir/eu-ai-transparency/CodeSystem/eu-ai-performance-metric-cs defines the following codes:

Code	Display	Definition
accuracy	Accuracy	The proportion of evaluated cases for which the AI system produced the correct result.
sensitivity	Sensitivity	The proportion of relevant positive cases correctly identified by the AI system.
specificity	Specificity	The proportion of relevant negative cases correctly identified by the AI system.
robustness	Robustness	The ability of the AI system to maintain appropriate performance under variations, disturbances, or reasonably foreseeable conditions of use.