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The AI Taxonomy provides and defines distinct categories to describe the work done by the machine on behalf of the physician based on: Technical features and performance of emerging AI products and services Effect on the work of the physician or other QHP Discrete components of work in order to facilitate valuation Goals of the AI Taxonomy Establish foundational definitions Define elements of differentiation Be understood by stakeholders who are not AI experts AI has been classified into one of these three categories: Assistive – The machine detects clinically relevant data without analysis or generated conclusions Requires physician or other QHP interpretation and report Augmentative – The machine analyzes and/or quantifies data in a clinically meaningful way

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A researcher who encounters "clinically studied" without "endpoints not met" has been given half a sentence