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Title:Increasing trust through the design of algorithm-based lesion segmentation support systems
Author(s):Gryska, Emilia; Cerna, Katerina; Heckemann, Rolf A.
Subject(s):Algorithm-based support systems
Brain lesion segmentation
Trust
Design for clinical practice
Abstract:The adoption rate of algorithm-based lesion segmentation support systems in clinical practice is very low. This is partly due to low trust levels radiologists have in such systems. To increase the trust, the design and validation of the support tools must comply with the needs and expectations of radiologists. We interviewed four clinicians who work with brain images on a daily basis to understand the needs, current methods and practices of image interpretation, and their opinion of automatic brain lesion segmentation tools. In the interviews, we identified the necessity to state the error of the automated decision support tool and its clinical relevance in a given context.
Issue Date:2020-03-23
Publisher:iSchools
Series/Report:iConference 2020 Proceedings
Genre:Conference Poster
Type:Text
image
Language:English
URI:http://hdl.handle.net/2142/106560
Rights Information:Copyright 2020 Emilia Gryska, Katerina Cerna, and Rolf A. Heckemann
Date Available in IDEALS:2020-03-17


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