HOPPR Unveils New AI Foundation Model for Chest CT

Adding a fifth foundation model to its AI Foundry portfolio, HOPPR has introduced the HOPPR EF Chest CT Narrative Model.

Trained on a large proprietary chest CT dataset drawn from multiple facilities, the HOPPR EF Chest CT Narrative Model offers narrative descriptions of chest CT findings across pulmonary, upper abdominal, cardiac, mediastinal and soft tissue regions with processing of 3D chest CT volumes.

HOPPR added that the AI foundation model also includes coverage of conditions such as aortic injury, pneumothorax and pulmonary embolism.

The company noted that theHOPPR EF Chest CT Narrative Model is available through HOPPR Forward Deployed Services that provide expertise in clinical workflow, machine learning and deployment support to facilitate development and customization of the foundation model to the needs of the radiology department or facility.

“Chest CT is one of the most information-dense studies in radiology. Getting AI to work well across everything it captures — the lungs, the heart, the aorta — is a genuinely hard problem, and we are pleased with what this model can do,” noted Khan Siddiqui, MD, the co-founder and CEO of HOPPR. “But the model is only part of what we are building. Our AI Foundry and Forward Deployed Services include secure infrastructure, curated data, and the clinical and technical expertise to help any organization move from a foundation model to a working application, regardless of where they are starting from. That is what makes this more than a model release.”