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An FDA Guide on Indications for Use and Device Reporting of Artificial Intelligence-Enabled Devices: Significance for Pediatric Use.
Nelson, Brandon J; Zeng, Rongping; Sammer, Marla B K; Frush, Donald P; Delfino, Jana G.
  • Nelson BJ; Division of Imaging, Diagnostics and Software Reliability, Office of Science and Engineering Labs, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland.
  • Zeng R; Division of Imaging, Diagnostics and Software Reliability, Office of Science and Engineering Labs, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland.
  • Sammer MBK; Vice Chair for Clinical Affairs, Department of Radiology, Texas Children's Hospital, Houston, Texas; Chair of the Pediatric AI Workgroup in the ACR.
  • Frush DP; John Strohbehn Professor of Radiology, Associate Faculty, Duke Medical Physics Graduate Program, Department of Radiology, Duke University Medical Center, Durham, North Carolina.
  • Delfino JG; Deputy Division Director, Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Labs, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland.
J Am Coll Radiol ; 20(8): 738-741, 2023 08.
Article en En | MEDLINE | ID: mdl-37400046
ABSTRACT
Radiology has been a pioneer in adopting artificial intelligence (AI)-enabled devices into the clinic. However, initial clinical experience has identified concerns of inconsistent device performance across different patient populations. Medical devices, including those using AI, are cleared by the FDA for their specific indications for use (IFUs). IFU describes the disease or condition the device will diagnose or treat, including a description of the intended patient population. Performance data evaluated during the premarket submission support the IFU and include the intended patient population. Understanding the IFUs of a given device is thus critical to ensuring that the device is used properly and performs as expected. When devices do not perform as expected or malfunction, medical device reporting is an important way to provide feedback about the device to the manufacturer, the FDA, and other users. This article describes the ways to retrieve the IFU and performance data information as well as the FDA medical device reporting systems for unexpected performance discrepancy. It is crucial that imaging professionals, including radiologists, know how to access and use these tools to improve the informed use of medical devices for patients of all ages.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Aprobación de Recursos Límite: Child / Humans Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Aprobación de Recursos Límite: Child / Humans Idioma: En Año: 2023 Tipo del documento: Article