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Artificial Intelligence – Life Cycle Processes and Quality Requirements – Part 3: Explainability; Text in English

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Last Updated: 28 Nov 2025

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Health Informatics. Interoperability and integration reference architecture. Model and framework

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Last Updated: 28 Nov 2025

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Security and resilience. Vocabulary

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Last Updated: 28 Nov 2025

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Dentistry – Artificial intelligence (AI) and augmented intelligence (AuI) based 2D radiograph analysis – Data generation, data annotation and data processing

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Last Updated: 28 Nov 2025

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Information technology. Biometric performance estimation methodologies using statistical models

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Last Updated: 28 Nov 2025

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Validation framework for the use of AI within healthcare – Specification

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Last Updated: 28 Nov 2025

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Artificial intelligence Ñ Data quality for analytics and machine learning (ML) Ñ Part 3: Data quality management requirements and guidelines

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Last Updated: 28 Nov 2025

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Artificial intelligence Ñ Data quality for analytics and machine learning (ML) Ñ Part 2: Data quality measures

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Last Updated: 28 Nov 2025

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Geographic information. Data quality – Part 1. General requirements

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Last Updated: 28 Nov 2025

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Architecture for a spontaneous dialogue processing system for language learning

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Last Updated: 28 Nov 2025

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Architectural framework for machine learning sandbox in future networks including IMT-2020

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Last Updated: 28 Nov 2025

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Architectural framework for machine learning model serving in future networks including IMT-2020

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Share your thoughts on this standard with the AI Standards Hub community here.

Last Updated: 28 Nov 2025

Content Type

Artificial Intelligence – Life Cycle Processes and Quality Requirements – Part 3: Explainability; Text in English

Health Informatics. Interoperability and integration reference architecture. Model and framework

Security and resilience. Vocabulary

Dentistry – Artificial intelligence (AI) and augmented intelligence (AuI) based 2D radiograph analysis – Data generation, data annotation and data processing

Information technology. Biometric performance estimation methodologies using statistical models

Validation framework for the use of AI within healthcare – Specification

Artificial intelligence Ñ Data quality for analytics and machine learning (ML) Ñ Part 3: Data quality management requirements and guidelines

Artificial intelligence Ñ Data quality for analytics and machine learning (ML) Ñ Part 2: Data quality measures

Geographic information. Data quality – Part 1. General requirements

Architecture for a spontaneous dialogue processing system for language learning

Architectural framework for machine learning sandbox in future networks including IMT-2020

Architectural framework for machine learning model serving in future networks including IMT-2020

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