Conference Paper


Towards a formal model of Type 1 diabetes for Artificial Intelligence

Abstract

Artificial Intelligence (AI) is potentially useful for cost effective diabetes self-management. One research priority for the development of robust and beneficial AI concerns the use of formal verification techniques to model such self-modifying systems. In the context of diabetes, formal methods may also have a role in fostering trust in the technology as well as facilitating dialogue between a multidisciplinary team to determine system requirements in a precise way. In this paper we show how the formal modelling language Event-B can be used to capture safety-critical constraints associated with AI systems for diabetes management.

Attached files

Authors

Brown, Daniel
Martin, Clare
Duce, David
Aldea, Arantza
Harrison, Rachel

Oxford Brookes departments

Faculty of Technology, Design and Environment\Department of Computing and Communication Technologies

Dates

Year: 2017


Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License


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This RADAR resource is the Accepted Manuscript of Towards a formal model of Type 1 diabetes for Artificial Intelligence

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