FDA Review of Radiologic AI Algorithms: Process and Challenges
Kuan Zhang, Bardia Khosravi, Sanaz Vahdati, Bradley J. Erickson
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.
Topics & Concepts
MedicineClearanceFood and drug administrationClinical PracticeAlgorithmMachine learningMedical physicsProcess (computing)Intensive care medicineArtificial intelligenceMedical emergencyComputer sciencePhysical therapyOperating systemUrologyArtificial Intelligence in Healthcare and EducationAdvanced X-ray and CT ImagingRadiomics and Machine Learning in Medical Imaging