With the use of artificial intelligence (AI) now on the rise in the field of medical imaging, more and more hospitals have trialled or integrated one or more AI-based solutions into their diagnostic workflows. These figures will vary depending on whether the clinical practice is private, public, or academic.
For the implementation and integration of AI-based solutions, hospitals now have the following options:
Alongside these solutions, we are also seeing a more recent trend of individual AI vendors working together to offer their applications through one common platform. The initiative often comes from one of the vendors, usually the one with the largest installation base.
While option (1) enables AI vendors to work independently, it doesn’t respond to scalability & efficiency requirements that hospitals face in the long run. We will therefore leave it out of the scope of the current analysis.
The second and third possibilities (2, 3), are worthy of comparison. Here we take the OSIMIS Platform as an example of a vendor-neutral independent solution. As an objective complement to this document, we highly recommend you to read this article, which covers the key elements to consider when working with AI marketplaces.
In summary, vendor neutral artificial intelligence (VNAI) solutions such as the OSIMIS Platform offer greater flexibility and support for the clinical application of AI. The stated goal should be a long-term collaboration, based on a relationship of trust, good communication and a thorough understanding of the local workflow. A VNAI platform allows for a step-by-step approach that is more personalised, ensuring the evaluation and monitoring of the AI applications used are given the right amount of oversight and evaluation. Additionally, it is possible to roll out these applications in a broader context, such as in a network of different imaging centres, even if they have a different PACS.
Here are some key benefits for using the OSIMIS Platform: