Some radiologists may argue that workflows are not optimized until AI (artificial intelligence) is fully integrated, but to us, AI doesn’t have to be all or nothing. While deep integration of AI can be helpful, it is not the only way to be successful.

If disruption of existing workflows makes you hesitant to consider AI in mammography, here are some guidelines to consider when integrating AI into already-established workflows. Understanding these three areas related to adopting AI in your radiology practice can ease your mind and prove that AI can be a solid footprint in the full path of your imaging process.

  • Assess your current tech stack and integration needs. Each radiology practice has varying set-ups and tools. You don’t have to start from scratch, but you do want to make sure that your chosen AI software integrates with the tools necessary for your process. This doesn’t mean, however, that AI needs to integrate with all your software. For instance, it’s not necessary for certain AI solutions to integrate with your patient tracking tool(s). It is, however, quite common for radiologists to choose AI tools that integrate with PACS, RIS as well as your viewer and reporting software.
  • Understand how AI can assist with image analysis. You have a standard of image analysis, interpretation and reporting. Think about how deep-learning AI tools can help strengthen this analysis and reporting process. Think about your current workflow and how, with the addition of AI, this may help or free up certain aspects of the process. It may be more of a complement to your current process versus an entire change to the process.
  • Evaluate the ultimate return on investment or costs. The financial impact of AI in radiology practices will depend on the financial model tied to the software. While some may think that investing in this new technology will be a financial burden, it is not always a highly expensive solution. For instance, if you choose a SaaS AI software solution, you typically do not have an investment upfront and there is more flexibility to scale—lower scan volume, higher price; high scan volume, lower price, and often the flexibility to stop the subscription at any time.

Not all AI interfaces are the same which is why it’s important not to make blanket judgements or overarching assumptions about what the software may or may not do to existing workflows. In fact, some AI used in mammography may add features that your current workflow doesn’t have such as color coding, unified scoring or interpretation systems, and specific findings within a scan (rather than showing all findings at once). In these instances, it can be an added benefit to investigate AI software that can amplify current workflows.

Communicate clearly with your AI vendor

Before you sign on the dotted line, ask your vendor to provide a run-down of everything that is (and is not) included in the AI software. Ask them to walk you through examples of set-ups or how the AI tools have aided in existing workflows. For instance, our deep-learning AI software does not require additional hardware set-up. Have a list of questions that are in line with your current workflow and platforms. The right AI vendor will work with you to ensure the least burden on your current practices and that you are comfortable setting up the system to coincide with established workflows.

It is our belief that AI will continue to move to the forefront of the standard of care and we have the tools that can be easily integrated into your current workflow. Contact us for a 10-minute demo to see what it’s like to have MammoScreen® AI at your side.