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Homepage>IEEE Standards>35 INFORMATION TECHNOLOGY. OFFICE MACHINES>35.240 Applications of information technology>35.240.80 IT applications in health care technology>IEEE 2802-2022 - IEEE Standard for Performance and Safety Evaluation of Artificial Intelligence Based Medical Devices: Terminology
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Released: 05.05.2023

IEEE 2802-2022 - IEEE Standard for Performance and Safety Evaluation of Artificial Intelligence Based Medical Devices: Terminology

IEEE Standard for Performance and Safety Evaluation of Artificial Intelligence Based Medical Devices: Terminology

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Standard number:IEEE 2802-2022
Released:05.05.2023
ISBN:978-1-5044-9501-1
Pages:31
Status:Active
Language:English
DESCRIPTION

IEEE 2802-2022

The standard establishes terminology used in artificial intelligence medical devices, including definitions of fundamental concepts and methodology that describe the safety, effectiveness, risks and quality management of artificial intelligence medical device. The standard provides definitions using the following forms, such as but not limited to literal description, equations, tables, figures and legends. The standard also establishes a vocabulary for the development of future standards for artificial intelligence medical devices.

The establishment of this consistent terminology promotes a more expansive and streamlined approach to research, development, testing and quality control for the medical Artificial Intelligence (AI) industry. The evaluation of AI will use terminology, which include, but are not limited, to terminology related to performance metrics, safety hazards, cyber security, and software reliability. The standard also provides vocabulary for the development of future general or specific standards of AI medical devices and helps different parties clarify understanding of AI quality considerations.

New IEEE Standard - Active. This standard is aimed at establishing concepts and terminology for the performance and safety evaluation of artificial intelligence medical device, which covers basic technology, dataset, quality characteristics, quality evaluation and application scenario. The annex further provides basic equations for quality evaluation purpose.