About the initiative

Want to cite this website?

Please refer to www.HealthAIregister.com and/or our related publication.

van Leeuwen, K.G., Schalekamp, S., Rutten, M.J.C.M. et al. Artificial intelligence in radiology: 100 commercially available products and their scientific evidence. Eur Radiol 31, 3797–3804 (2021). https://doi.org/10.1007/s00330-021-07892-z

Increasing transparency in AI for radiology

Health AI Register increases transparency in the commercial artificial intelligence software available for radiology. The supply of commercial software products has rapidly increased. For the potential customers, it might not always be clear what is out there, with what regulatory clearance, and at what maturity level. Therefore, we want to increase transparency in the available AI software for radiology in Europe and aid the selection and implementation of such software.

The most comprehensive overview

We provide an overview of available AI based software for clinical radiology practice. The focus is on the European market, therefore CE certification is a requirement for software to be on the main product page. Vendors are asked to provide information about their products ensuring high quality information. If not provided, the company and product profile will be more limited and consisting of public information (from e.g. websites, news articles, etc.). Currently, we are the most comprehensive overview out there.

We are independent

Vendors do not pay to be listed on our platform. All content is created independently by our team and is not influenced by external payments. At Health AI Register we have a strict policy against sponsored content. Health AI Register is maintained by the team of Romion Health, an independent consultancy on the responsible adoption of AI in healthcare.

Your product missing?

Do you think your software product meets our criteria? Please, get in touch. You will then receive further instructions on the information to supply.

The data aggregation and maintenance of this website was performed as part of Kicky van Leeuwen’s PhD trajectory at the Diagnostic Image Analysis Group (DIAG) from the Radboud University Medical Center in the Netherlands from 2019 to December 2022. Radboud university medical center cannot be held responsible for the content of this website.