FDA Review of Radiologic AI Algorithms: Process and Challenges

Kuan Zhang, Bardia Khosravi, Sanaz Vahdati, Bradley J. Erickson

Research output: Contribution to journalReview articlepeer-review

Abstract

A Food and Drug Administration (FDA)–cleared artificial intelligence (AI) algorithm misdiagnosed a finding as an intracranial hemorrhage in a patient, who was finally diagnosed with an ischemic stroke. This scenario highlights a notable failure mode of AI tools, emphasizing the importance of human-machine interaction. In this report, the authors summarize the review processes by the FDA for software as a medical device and the unique regulatory designs for radiologic AI/machine learning algorithms to ensure their safety in clinical practice. Then the challenges in maximizing the efficacy of these tools posed by their clinical implementation are discussed.

Original languageEnglish (US)
Article numbere230242
JournalRadiology
Volume310
Issue number1
DOIs
StatePublished - Jan 2024

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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