Impact of Using an AI-CAD Tool in Radiology Training

Beatriz Rodrigues Leite, Sippo Rossi, Tariq Osman Andersen

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

The integration of Artificial Intelligence (AI) in radiology, particularly through Computer-Aided Detection (CAD) systems, promises significant advancements in diagnostic accuracy, workflow optimization, and educational outcomes. Despite the potential benefits, challenges such as professional deskilling, overreliance on AI, and regulatory issues are still feared. This study aims to evaluate the practical, educational, and personal implications of introducing a CAD AI-tool in radiology residency. Through a mixed-methods approach involving ten radiology residents, we want to assess the impact of AI on diagnostics, bias, workflow, and resident-supervisor interactions. In the study, we monitor and interview residents that are analyzing chest X-rays using the CAD system. Preliminary findings from pilot studies indicate a generally positive reception but highlight the need for improvements. This research seeks to provide insights into the responsible deployment of AI in radiology training.

Original languageEnglish
Title of host publicationNordiCHI '24 Adjunct : Adjunct Proceedings of the 13th Nordic Conference on Human-Computer Interaction, NordiCHI 2024
PublisherACM - Association for Computing Machinery
Publication date13.10.2024
Article number22
ISBN (Electronic)979-8-4007-0965-4
DOIs
Publication statusPublished - 13.10.2024
MoE publication typeA4 Article in conference proceedings
Event13th Nordic Conference on Human-Computer Interaction, NordiCHI 2024 - Uppsala, Sweden
Duration: 13.10.202416.10.2024
Conference number: 13
https://dl.acm.org/doi/proceedings/10.1145/3677045

Publication series

NameACM International Conference Proceeding Series

Keywords

  • 113 Computer and information sciences
  • Artificial Intelligence
  • Computer-Aided Detection
  • Human-AI Collaboration
  • Radiology
  • Resident Training

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