Search Results for author: Ibrahim Habli

Found 6 papers, 1 papers with code

Review of the AMLAS Methodology for Application in Healthcare

no code implementations1 Sep 2022 Shakir Laher, Carla Brackstone, Sara Reis, An Nguyen, Sean White, Ibrahim Habli

In recent years, the number of machine learning (ML) technologies gaining regulatory approval for healthcare has increased significantly allowing them to be placed on the market.

A Principles-based Ethical Assurance Argument for AI and Autonomous Systems

no code implementations29 Mar 2022 Zoe Porter, Ibrahim Habli, John McDermid, Marten Kaas

Assurance cases are structured arguments, supported by evidence, that are often used to establish confidence that a software-intensive system, such as an aeroplane, will be acceptably safe in its intended context.

The Role of Explainability in Assuring Safety of Machine Learning in Healthcare

no code implementations1 Sep 2021 Yan Jia, John McDermid, Tom Lawton, Ibrahim Habli

Established approaches to assuring safety-critical systems and software are difficult to apply to systems employing ML where there is no clear, pre-defined specification against which to assess validity.

BIG-bench Machine Learning

Guidance on the Assurance of Machine Learning in Autonomous Systems (AMLAS)

1 code implementation2 Feb 2021 Richard Hawkins, Colin Paterson, Chiara Picardi, Yan Jia, Radu Calinescu, Ibrahim Habli

Machine Learning (ML) is now used in a range of systems with results that are reported to exceed, under certain conditions, human performance.

BIG-bench Machine Learning

A Framework for Assurance of Medication Safety using Machine Learning

no code implementations11 Jan 2021 Yan Jia, Tom Lawton, John McDermid, Eric Rojas, Ibrahim Habli

As healthcare is now data rich, it is possible to augment safety analysis with machine learning to discover actual causes of medication error from the data, and to identify where they deviate from what was predicted in the safety analysis.

BIG-bench Machine Learning

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