Model driven development for AI-based healthcare systems: A review
We review our experience with integrating Artificial Intelligence (AI) into healthcare systems following the Model-Driven Development (MDD) approach. At a time when AI has the potential to instigate a paradigm shift in the health sector, better integrating healthcare experts in the development of these technologies is of paramount importance. We see MDD as a useful way to better embed non-technical stakeholders in the development process. The main goal of this review is to reflect on our experiences to date with MDD and AI in the context of developing healthcare systems. Four case studies that fall within that scope but have different profiles are introduced and summarised: the MyMM application for Multiple Myeloma diagnosis; CNN-HAR, that studies the ability to do AI on the edge for IoT-supported human activity recognition; the HIPPP web based portal for patient information in public health; and Cinco de Bio, a new model driven platform used for the first time to support a better cell-level understanding of diseases. Based on the aforementioned case studies we discuss the characteristics, the challenges faced and the positive outcomes achieved.
History
Publication
Bridging the Gap Between AI and Reality (AISoLA 2023) 14129, pp. 245–265Publisher
Springer NatureNote
From Conference Bridging the Gap Between AI and Reality (AISoLA 2023)Also affiliated with
- Health Research Institute (HRI)
- LERO - The Science Foundation Ireland Research Centre for Software
External identifier
Department or School
- Computer Science & Information Systems