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Applying a Computational Model Credibility Framework to Physiological Closed-loop Controlled Medical Device Testing.
Scully, Christopher G; Pathmanathan, Pras; Daluwatte, Chathuri; Yaghouby, Farid; Gray, Richard A; Weininger, Sandy; Morrison, Tina M; Parvinian, Bahram.
Afiliação
  • Scully CG; Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD.
  • Pathmanathan P; Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD.
  • Daluwatte C; Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD.
  • Yaghouby F; Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD.
  • Gray RA; Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD.
  • Weininger S; Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD.
  • Morrison TM; Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD.
  • Parvinian B; Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD.
IEEE Life Sci Conf ; 2018: 130-133, 2018 Oct.
Article em En | MEDLINE | ID: mdl-34514471
Physiological closed-loop controlled medical devices are safety-critical systems that combine patient monitors with therapy delivery devices to automatically titrate therapy to meet a patient's current need. Computational models of physiological systems can be used to test these devices and generate pre-clinical evidence of safety and performance before using the devices on patients. The credibility, utility, and acceptability of such model-based test results will depend on, among other factors, the computational model used. We examine how a recently developed risk-informed framework for establishing the credibility of computational models in medical device applications can be applied in the evaluation of physiological closed-loop controlled devices.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2018 Tipo de documento: Article