Since 2017, we are studying how AI applications are introduced to medical practice (so far, mainly medical imaging), how medical professionals work with these applications, and how the working and organizing practices are adapted to create social and economic values. As engaged academics, we strive to be critical to the hypes around AI, dig into the actual cases, deeply understand the complexity of working and organizing with AI, and share our findings with practitioners as well as academics.
We build on our unique team of organizational, medical, and technological professionals who are bridging the domains of digital technologies, work and organizing, and medical practices.
Prof. dr. Frans Feldberg
Full Professor, Co-founder of Amsterdam Center for Business Analytics and Data Science Alkmaar
Dr. Paul Algra
Senior radiologist at Northwest Hospitalgroup, Alkmaar (NWZ)
Research Affiliates of KIN Center for Digital Innovation
Prof. dr. Marleen Huysman
Full Professor of Knowledge and Organization, Director of KIN Center for Digital Innovation, Head of department Information Systems, Logistics and Innovation, School of Business and Economics
Ms. Bomi Kim
PhD candidate at KIN Center for Digital Innovation. Investigating how the profession of radiology reconstructs itself when AI is introduced
Current master students
Previous Master Students
We actively study the development of AI applications, how AI applications are implemented in medical practice, and how medical professionals experience and react to AI.
Investigating the experiences, perceptions, and intentions of radiologists regarding artificial intelligence
Since 2017, we have been actively conducting interviews with more than 100 professionals from medical imaging domain (primarily radiologists), from 28 countries, with diverse experiences about AI and heterogenous backgrounds and positions in medical practice. Our aim is to understand the state and changes in the professionals’ experiences with AI and its applications, their perceptions regarding the AI’s (in)capabilities for their work, its impact on their work and profession, and their reactions to cope with the AI movement. This research has been supported by Prof. Frans Feldberg and EUSOMII scientific and management boards, particularly, Dr. Paul Algra, Dr. Erik Ranschaert, and Dr. Peter van Ooijen. A team of researchers from KIN Center for Digital Innovation have been contributing to this research project: Bomi Kim, Merel Bulder, Ann Nguyen, Diana Diaz Curiel, Felix Worringen, Lorena Tol, Nabil Bouzian. We are actively continuing this research at ECR 2020. Some of the publications of this research project are:
- Kim, Bomi & Rezazade Mehrizi, Mohammad H. (2020), “Maneuvering uncertainty and urgency in working with artificial intelligence”, AI@Work conference, Amsterdam, March 2020
- Rezazade Mehrizi, Mohammad H. (2020), “Narrow Intelligence: a socio-technical perspective of the narrowness of artificial intelligence at work”, AI@Work conference, Amstedam, March 2020
- Merel Bulder (2018), “The transformation of radiology from a knowledge and learning perspective”, Master thesis, Vrije Universiteit Amsterdam, School of Business and Economics
- Merel Bulder, (2018), “De houding van de radioloog ten opzichte van artificiële intelligentie”, Memorad, vol. 3. 29-31.
- Felix Worringen (2019), “The rise of artificial intelligence in radiology: How do the perceived (in-)capabilities of artificial intelligence shape a perceived change in the set of skills performed by a radiologist?”, Master thesis, Vrije Universiteit Amsterdam, School of Business and Economics.
- Lorena Tol (2019), “Framing disruptive technology: How radiologists frame Artificial Intelligence technology and reframe their current role and work in the organization”, Master thesis, Vrije Universiteit Amsterdam, School of Business and Economics.
- Ann Nguyen (2019), “The perceived influence of technological capabilities and characteristics of skills on the radiologists’ perception about the impact of AI on their professional skills”, Master thesis, Vrije Universiteit Amsterdam, School of Business and Economics.
- Diana Diaz Curiel (2019), “Artificial Intelligence in Radiology: The impact of Trust”, Master thesis, Vrije Universiteit Amsterdam, School of Business and Economics.
Investigating the developments of AI applications in the domain of medical imaging: A technography study
To understand how startups and established firms develop AI-based applications, we have been conducting systematic research on all AI applications that are offered to the market in the domain of medical imaging. We analyzed all the applications based on their features, functionalities, their target body-part, modality, and work/task. In addition, we examined the regulatory status of these applications (e.g., having FDA or CE approval). We examine how these applications seek to impact the work of radiologists (e.g., automate, augment, or extend) and how these applications are offered to the work (e.g., on-premise, cloud-based, …) and integrated to the radiology workflow (e.g., integrated with PACS/RIS …). Our latest update in December 2019 shows more than 300 AI applications are introduced to the market. Some of the initial publications on this research are:
- Milou Homan (2019), “AI in radiology: An assessment of intelligent solutions and their potential impact on errors within the diagnostic workflow”, Master thesis, Vrije Universiteit Amsterdam, School of Business and Economics.
- Ayumindya Paramita Dewi, (2019), “The roles of artificial intelligence in diagnosis workflow in neuroradiology”, Master thesis, Vrije Universiteit Amsterdam, School of Business and Economics
Examining the implementation of AI applications in practice
We have been studying the actual implementations of AI applications at work.
- Since 2018, we have been studying one of the leading AI applications in the Netherlands in the radiology department of North-West Ziekenhuis, Alkmaar, where they are using a deep-learning AI application for the detection and comparison of lung nodules. We are conducting at-work observations to see how radiologists work with this new AI tool and how together create new modes of intelligence. Dr. Paul Algra has been a key initiator and supporting figure in this research.
- Since 2019, we have been studying one of the most advanced and comprehensive AI-implementations in the Netherlands: Leiden Medical Center. We are examining how various practices, processes, and organizational structures around medical diagnosis are reorganized to support effective and fundamental implementation of multiple AI solutions. Professor Mark van Buchem has been a key supporting figure in our study, who has been the leader of this major innovation project.
Consider to mention collaboration InHolland/Fontys/Hanzehogeschool in setting up Ai curriculum.