Project Details
The recommended practice identifies best practices for establishing a quality management system for datasets used for artificial intelligence medical device.
The recommended practice covers a full cycle of dataset management, including items such as but not limited to data collection, transfer, utilization, storage, maintenance and update.
The recommended practice recommends a list of critical factors that impact the quality of datasets, such as but not limited to data sources, data quality, annotation, privacy protection, personnel qualification/training/evaluation, tools, equipment, environment, process control and documentation.
Standards Committee | |
PAR Approval |
2018-12-05
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PARs |
Working Group Details
Working Group |
AIMDWG - Artificial Intelligence Medical Device Working Group
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Standards Committee | |
Society | |
IEEE Program Manager | |
Active Projects |
The standard establishes terminology used in artificial intelligence medical device, 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 device.
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