Skip to main content

Anyone interested in using AI to boost the efficiency of their radiology practice or hospital department will be initially overwhelmed by the amount of new companies in the field. Our two AI overviews are your opportunity to browse through the available solutions and get started with radiology AI.

It is often said that more than 200 AI start-up companies have well over 400 algorithms. Whether this is true or not, we can safely say that there are two ways of integrating AI algorithms into the diagnostic workflow: The classifiers can be connected to the PACS directly or via a digital platform. Our two overviews show which companies offer which algorithms, and on which digital platforms the algorithms run.

Direct integration or digital platform?

The advantage of integrating AI algorithms using digital platforms is that only one data interface needs to be configured from the PACS to the platform.

Through their cooperation with the algorithm developers, platform providers have set themselves the goal of simplifying integration, by already configuring interfaces to their cooperation partners’ validated classifiers.

This means interested users do not have to worry too much about data protection issues. However, the use of digital platforms is only recommended if numerous AI algorithms are to be used.

For our overviews, we received the data directly from the providers and researched it ourselves. Some companies that have provided us with their product lines decided to support our overview by posting logos and contact details, while others preferred to use a free entry.

As for the other providers who did not respond to our request, we evaluated their websites. We cannot guarantee that the information is complete, but we found out quite a lot!

How to get started?

There is no question that AI-based algorithms are well suited to supporting findings in radiological diagnostics. This has been proven in numerous clinical studies. But when is the right time to start? This is a question that everyone has to answer for themselves, as getting started with radiology AI depends primarily on your framework conditions:

  • Do I have a problem, that can be solved with AI?
  • Is my business running smoothly right now (never touch a running system)?
  • Do I have the time to get to grips with the new technology?
  • Was I going to invest in new technology anyway?
  • Should I optimize the workflow in my facility?
  • Do I have difficulties finding staff at my location?
  • What risk am I prepared to take?
  • Do I trust myself to make the technological change?
  • Do I have confidence in the new technology?
  • Do I trust one of the new companies?

Our overviews are intended for those still reading this text 🙂 We want to create the basis for a successful start and present the companies that offer modern solutions to cope with the constantly increasing number of examinations and mitigate staff shortages.

Clinical Decision Support was just the beginning. In further market overviews, we will gradually show other possibilities to increase your operations’ efficiency by shortening examination times and digitizing workflows.

The RSNA AI Showcase is where you will get firsthand information.

See you in Chicago Sunday!