Location
Hilton Hawaiian Village, Honolulu, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2024 12:00 AM
End Date
6-1-2024 12:00 AM
Description
Radiology has always been considered a highly technological field in medicine. Recently, a new area of radiology has emerged with the adoption of Artificial Intelligence (AI)-based health information systems due to advancements in big data, deep learning, and increased computing power. While AI elevates prevention, diagnostics, and therapy to a new level, various obstacles hinder the adoption of AI technologies in radiology. To provide an overview on these obstacles as basis for corresponding solution approaches, we identify and comprehensively outline these obstacles by conducting a structured literature review. We find 17 obstacles, which we group into six categories. Furthermore, our research discusses relevant interrelations of the obstacles, most of which we have found to be related to user attitude. Besides, these complex interrelations we expose the necessity of approaching the obstacles simultaneously.
Recommended Citation
Hennrich, Jasmin; Fuhrmann, Hannah; and Eymann, Torsten, "Accelerating the Adoption of Artificial Intelligence Technologies in Radiology: A Comprehensive Overview on Current Obstacles" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 6.
https://aisel.aisnet.org/hicss-57/hc/adoption/6
Accelerating the Adoption of Artificial Intelligence Technologies in Radiology: A Comprehensive Overview on Current Obstacles
Hilton Hawaiian Village, Honolulu, Hawaii
Radiology has always been considered a highly technological field in medicine. Recently, a new area of radiology has emerged with the adoption of Artificial Intelligence (AI)-based health information systems due to advancements in big data, deep learning, and increased computing power. While AI elevates prevention, diagnostics, and therapy to a new level, various obstacles hinder the adoption of AI technologies in radiology. To provide an overview on these obstacles as basis for corresponding solution approaches, we identify and comprehensively outline these obstacles by conducting a structured literature review. We find 17 obstacles, which we group into six categories. Furthermore, our research discusses relevant interrelations of the obstacles, most of which we have found to be related to user attitude. Besides, these complex interrelations we expose the necessity of approaching the obstacles simultaneously.
https://aisel.aisnet.org/hicss-57/hc/adoption/6