By Kerim Genc, Product Manager, Synopsys Simpleware Product Group
1. More and more Medical Device companies that have tried to build/deploy their own AI-enabled automation for their current patchwork of patient specific workflows are going to start realizing their inefficiencies and turn to third-party companies that specialize in delivering AI solutions.
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- Since patient-specific workflows are set to drive the growth of the global 3D printing medical device market , the biggest bottleneck, image segmentation, needs to be addressed at scale. Companies can no longer afford to rely on an army of technicians clicking away at images to manually segment them. Therefore, they will turn to AI solutions to automate the process, and will run into the “build or buy” dilemma. Some can build and deploy internally, but many have been at it for a while and are struggling to realize the promise of a fully automated, single-click image segmentation solution.
It takes more than simply hiring a few AI developers to build robust AI-enabled solutions that are accurate, repeatable, and scalable to their specific workflow, all the while being deployed quickly and able to pass regulatory approval. Many are two to three years into “building it themselves,” and although their internal solutions may be able to automate 60-70% of the cases, the last 30% is proving elusive; they are realizing that, although they are a Medical Device company with sophisticated software capabilities and very talented developers, extracting the full potential value of AI needs a specialized partner. I think we will see an acceleration of companies ceding control of their workflow development in exchange for faster and more robust deployment of AI solutions.