Picardi, Chiara and Habli, Ibrahim orcid.org/0000-0003-2736-8238 (2019) Perspectives on Assurance Case Development for Retinal Disease Diagnosis Using Deep Learning. In: AIME 2019: Artificial Intelligence in Medicine. Lecture Notes in Artificial Intelligence . Springer , pp. 365-370.
Abstract
We report our experience with developing an assurance case for a deep learning system used for retinal disease diagnosis and referral. We investigate how an assurance case could clarify the scope and structure of the primary argument and identify sources of uncertainty. We also explore the need for an assurance argument pattern that could provide developers with a reusable template for communicating and structuring the different claims and evidence and clarifying the clinical context rather than merely focusing on meeting or exceeding performance measures.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer Nature Switzerland AG 2019. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 03 Mar 2020 14:20 |
Last Modified: | 04 Jan 2025 00:27 |
Published Version: | https://doi.org/10.1007/978-3-030-21642-9 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Artificial Intelligence |
Identification Number: | 10.1007/978-3-030-21642-9 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:157975 |