IEEE Standard for Performance and Safety Evaluation of Artificial Intelligence Based Medical Devices: Terminology
IEEE Std 2802-2022
Year: 2023
IEEE - The Institute of Electrical and Electronics Engineers, Inc.
Abstract: 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.
Subject: IEEE 2802
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IEEE Standard for Performance and Safety Evaluation of Artificial Intelligence Based Medical Devices: Terminology
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contributor author | IEEE - The Institute of Electrical and Electronics Engineers, Inc. | |
date accessioned | 2024-12-17T08:09:11Z | |
date available | 2024-12-17T08:09:11Z | |
date copyright | 05 May 2023 | |
date issued | 2023 | |
identifier other | 10117469.pdf | |
identifier uri | http://yse.yabesh.ir/std;query=autho47037D83FCDCAC4261598F1EFDEC014A/handle/yse/336333 | |
description abstract | 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. | |
language | English | |
publisher | IEEE - The Institute of Electrical and Electronics Engineers, Inc. | |
title | IEEE Standard for Performance and Safety Evaluation of Artificial Intelligence Based Medical Devices: Terminology | en |
title | IEEE Std 2802-2022 | num |
type | standard | |
page | 31 | |
status | Active | |
tree | IEEE - The Institute of Electrical and Electronics Engineers, Inc.:;2023 | |
contenttype | fulltext | |
subject keywords | IEEE 2802 | |
subject keywords | evaluation of performance and safety | |
subject keywords | artificial intelligence medical device | |
subject keywords | dataset | |
identifier DOI | 10.1109/IEEESTD.2023.10117469 |