Abstract
Advancements in artificial intelligence (AI) are redefining innovation in healthcare. In the radiology do‐ main, advanced AIsystemshaveshownpromisingperformanceinmedicaltaskssuchastumordetection and treatment plan. Given the multidisciplinary nature of the medical AIdevelopmentteam, challenges in collaboration, design, and integration are common. Forexample, the design lens is less present, researchers from different disciplines speak different languages, andcliniciansastheend‐usersoftenplaytheexternal consultant role rather than team members. To address these gaps, wepresentthedevelopmentofacol‐ labor ation platform, anAI‐assistedcomputer‐aideddiagnosis (CAD) system for radiology, usinga Research through Design (RtD) methodology. Throughathree‐phasecasestudy, weshowcaseanovelwayofoper‐ ation ali zing multidisciplinary collaboration with design team playing the coordinating and integrating role, highlightingtheimportanceofincludingsubject‐matterexpertsdirectlyindevelopmentteams. Wealso provideadesignanddevelopmentguidelineformultidisciplinaryresearchteam. Moreover, this case study demonstrate show design struggles and decisions contribute to knowledge generation, offering strategies tobalancehuman‐andtechno‐centricperspectives. Reflecting on the process, we provide pertinent input for design research, HCI, and design and collaboration implications for developing AIsystemsinradiology, and for healthcare AImoregenerally.
Keywords
Researchthroughdesign; Multidisciplinaryteams; Healthcare AI; Prototyping
DOI
https://doi.org/10.21606/iasdr.2025.1100
Citation
Fang, N., Bruno, V., Ruijs, N., Pluyter, J., Chen, L.,and Funk, M.(2025) The Many Chefs in the AI Kitchen: Collaborative AI Design and Development in Oncology, in Chang, C.-Y., and Hsu, Y. (eds.), IASDR 2025: Design Next, 02-05 December, Taiwan. https://doi.org/10.21606/iasdr.2025.1100
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
Track 9 - Healthcare Design
The Many Chefs in the AI Kitchen: Collaborative AI Design and Development in Oncology
Advancements in artificial intelligence (AI) are redefining innovation in healthcare. In the radiology do‐ main, advanced AIsystemshaveshownpromisingperformanceinmedicaltaskssuchastumordetection and treatment plan. Given the multidisciplinary nature of the medical AIdevelopmentteam, challenges in collaboration, design, and integration are common. Forexample, the design lens is less present, researchers from different disciplines speak different languages, andcliniciansastheend‐usersoftenplaytheexternal consultant role rather than team members. To address these gaps, wepresentthedevelopmentofacol‐ labor ation platform, anAI‐assistedcomputer‐aideddiagnosis (CAD) system for radiology, usinga Research through Design (RtD) methodology. Throughathree‐phasecasestudy, weshowcaseanovelwayofoper‐ ation ali zing multidisciplinary collaboration with design team playing the coordinating and integrating role, highlightingtheimportanceofincludingsubject‐matterexpertsdirectlyindevelopmentteams. Wealso provideadesignanddevelopmentguidelineformultidisciplinaryresearchteam. Moreover, this case study demonstrate show design struggles and decisions contribute to knowledge generation, offering strategies tobalancehuman‐andtechno‐centricperspectives. Reflecting on the process, we provide pertinent input for design research, HCI, and design and collaboration implications for developing AIsystemsinradiology, and for healthcare AImoregenerally.