We are seeking an ambitious PhD student to work on this three-year project, which should result in a PhD thesis. The goal of this PhD project is to bring more transparency in the field of commercially available AI solutions in healthcare. You will use our developed Project AIR framework to validate and compare more commercially AI products to provide insights into the performance of the products.
Another important part of the project is to develop and coordinate a national course aimed at healthcare professionals on AI for healthcare, how it works, what products are available, and what to keep in mind when evaluating and implementing AI products in healthcare. The course will consist of an online part and full-day workshops that will be held four times per year.
Furthermore, you will have the opportunity to explore the AI market beyond the field of radiology and expand the overview of commercially available products to other areas in healthcare. Background
The number of AI products in healthcare, particularly in the field of medical imaging, is rapidly growing. There are over 200 products available for the radiology market, and platforms are emerging that lower the barrier for software developers to make their solutions widely available. However, to date, few of these AI products are being used in daily practice, despite many companies striving to gain a foothold in hospitals and radiology departments.
On the other hand, management boards and radiologists are struggling with identifying products that can improve healthcare, reduce workload, or cut costs. Solid studies validating AI products in radiology are scarce. Most studies have been funded by the industry, measuring the performance of a single algorithm, while ignoring integration into clinical workflows, time and cost savings, and cost-effectiveness analysis.
The ‘AI for Radiology’ platform
, developed by Kicky van Leeuwen in her PhD project over the past few years, enables end-users to access an overview of the available products in the radiology market and provides transparency about their performance. Additionally, we have developed a framework, Project AIR
, which allows us to conduct independent multi-vendor, multi-center comparisons of similar products.
Check for more information: DIAG vacancy