Algorithms can enable efficient and effective medical diagnosis for patients. Unfortunately, investments in algorithmic technologies often do not yield the aspired benefits, noticed professor Mohammad Rezazade Mehrizi and assistant professor Wendy Günther. With this research project, they want to facilitate the creation of effective solutions. They will create a learning community which enables relevant stakeholders to collaboratively experiment with and learn from specific use cases.
“This project results in insights for novel educational trainings and developing safe, effective, and efficient ways of using these new technologies for medical diagnosis,” says Rezazade Mehrizi. "As organisational scientists, we are well equipped to think about how these technologies can best be implemented in organisations."
The researchers work together with Willem Grootjans (Leiden University Medical Center, LUMC), Mark van Buchem (LUMC) en Harmen Bijwaard (Hogeschool Inholland). They will also work together with several partners: CMRAD, Contextflow, Oxipit, Nederlandse Vereniging Medische Beeldvorming en Radiotherapie, Nederlandse Vereniging voor Radiologie, Longkanker Nederland (patient community).
Günther: “By also including associations of doctors and patients, we can ensure that all relevant stakeholder perspectives are considered in the development of new technologies such as AI.”
About the grant
The grant is part of the Knowledge and Innovation covenant (KIC) 2020-2023 of the Dutch Research Council (NWO). Within the KIC call ‘Human Capital Learning communities needed for societal and technological transitions to succeed’, four projects have been awarded funding. Consortia consisting of knowledge institutions, private and public partners will conduct research into, among other things, how workplace learning and innovation can form a logical part of a learning community, how a learning community should designed and how the design can make the connection between learning and innovating.