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The Steep Road to Artificial Intelligence–mediated Radiology
4
Zitationen
2
Autoren
2023
Jahr
Abstract
A rtificial intelligence (AI) is an area of rapid develop- ment in data-driven fields, including radiology.Its many potential applications in radiology range from administrative tasks to image quality improvement, scan acceleration, and diagnostic tasks.Accordingly, the Data Science Institute of the American College of Radiology (ACR) has begun to define worthwhile use cases for AI in radiology (1).Regulatory requirements must be higher for AI that impacts patient diagnoses compared with a tool that predicts how many patients will not attend their appointment to optimize scheduling.This is reflected in the framework of risk categories proposed by the International Medical Device Regulators Forum and is considered in proposals for legislation (2).Faced with both enthusiasm and skepticism, the adoption of AI-enabled workflows in clinical practice has been slow.In a 2020 survey, the ACR Data Science Institute found that 33.5% of respondents employed AI in their clinical practice (3).Approximately half of them used AI for image interpretation, while the other half used AI for
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