Understanding the Role of Expert Intuition in Medical Image Annotation: A Cognitive Task Analysis Approach
Understanding the Role of Expert Intuition in Medical Image Annotation: A Cognitive Task Analysis Approach
dc.contributor.author | Leiser, Florian | |
dc.contributor.author | Warsinsky, Simon | |
dc.contributor.author | Daum, Marie | |
dc.contributor.author | Schmidt-Kraepelin, Manuel | |
dc.contributor.author | Thiebes, Scott | |
dc.contributor.author | Wagner, Martin | |
dc.contributor.author | Sunyaev, Ali | |
dc.date.accessioned | 2022-12-27T19:05:46Z | |
dc.date.available | 2022-12-27T19:05:46Z | |
dc.date.issued | 2023-01-03 | |
dc.description.abstract | To improve contemporary machine learning (ML) models, research is increasingly looking at tapping in and incorporating the knowledge of domain experts. However, expert knowledge often relies on intuition, which is difficult to formalize for incorporation into ML models. Against this backdrop, we investigate the role of intuition in the context of expert medical image annotation. We apply a cognitive task analysis approach, where we observe and interview six expert medical image annotators to gain insights into pertinent decision cues and the role of intuition during annotation. Our results show that intuition plays an important role in various steps of the medical image annotation process, particularly in the appraisals of very easy or very difficult images, and in case purely cognitive appraisals remain inconclusive. Overall, we contribute to a better understanding of expert intuition in medical image annotation and provide possible interfaces to incorporate said intuition into ML models. | |
dc.format.extent | 10 | |
dc.identifier.doi | 10.24251/HICSS.2023.351 | |
dc.identifier.isbn | 978-0-9981331-6-4 | |
dc.identifier.uri | https://hdl.handle.net/10125/102982 | |
dc.language.iso | eng | |
dc.relation.ispartof | Proceedings of the 56th Hawaii International Conference on System Sciences | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.subject | Decision Support for Healthcare Processes and Services | |
dc.subject | cognitive task analysis | |
dc.subject | expert knowledge | |
dc.subject | intuition | |
dc.subject | machine learning | |
dc.subject | medical image annotation | |
dc.title | Understanding the Role of Expert Intuition in Medical Image Annotation: A Cognitive Task Analysis Approach | |
dc.type.dcmi | text | |
prism.startingpage | 2850 |
Files
Original bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- 0278.pdf
- Size:
- 550.7 KB
- Format:
- Adobe Portable Document Format
- Description: