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RadNet’s wholly-owned subsidiary DeepHealth has forged a partnership with radiology foundation model vendor Hoppr. The move will see the commercialisation of Hoppr’s medical-grade foundation model and help foster the development of fine-tuned models for use for specific conditions, such as breast, prostate and lung cancer detection.
Why we have chosen this topic
– For many vendors, partnerships are key in these early stages of generative AI.
– Hoppr, as one of a select few vendors developing medically-focused foundation models, could be influential over time.
Why it matters
– In the long run, generative AI in medical imaging can have a significant impact on improving patient outcomes through improved accuracy in detection and streamlined workflows meaning that patients are getting better care faster.
– However, the focus in the near term is for non-clinical applications. For providers such as RadNet, which are focused on medical imaging, even small efficiency gains can have a greater impact compared to more diversified providers.
– The optimum mode of commercialisation has not yet been determined for foundation model vendors, could Hoppr’s partnership with DeepHealth set an example for the rest of the industry?
