CHICAGO, Nov. 26, 2023 /PRNewswire/ -- Today, HOPPR announces the launch of Grace, a multi-modal foundation model for medical imaging, powered by Amazon Web Services, Inc. (AWS) and available via private beta to developers, radiology PACS, and AI companies for fine tuning and application development. Together with a milestone investment from Health2047, a venture studio founded by the American Medical Association (AMA), this launch marks a significant step forward in HOPPR's quest to unlock the potential of generative AI in medical imaging.

Grace is a first-of-its-kind B2B foundation model that enables image-to-image and text-to-image learning across all medical imaging modalities, including X-rays, CTs, MRIs, and echocardiograms. Available via an API service, Grace enables application developers to more quickly build meaningful AI solutions that physicians, technicians, and support staff can use to engage interactively with medical images.

Health2047's newest portfolio company unveils medical imaging AI platform powered by Amazon Web Services

With Grace, users can unlock diagnostic, clinical, and operational value from medical imaging data. An organization's own data can be used to securely fine tune the model for use in applications that allow users to then converse with medical imaging studies about findings, alternative imaging views, suggested surgical interventions, and treatment protocols. The model also supports non-clinical use cases including workflow, billing and coding review, and QA, providing a one-API shop for all the data needed to support the imaging sector.

Grace has been meticulously developed using over a petabyte of permission-based, anonymized medical imaging study data. These studies have been enriched with corresponding reports to ensure robust training for commercial deployment across extensive datasets, spanning both 2D and 3D modalities and inclusive of longitudinal imaging studies through strategic collaborations with key partners like Gradient Health. At scale, Grace will contain approximately five trillion parameters – five times more than current commercial generative models trained on one trillion parameters. Committed to responsible AI practices, Grace has been developed with a privacy-centric approach using healthcare industry-standard quality management systems based on the ISO 13485. In preparation for widespread release, HOPPR is actively engaging with partners such as RadNet and Rad AI to refine its offerings to meet the precise needs of the healthcare sector.

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