HOPPR’s Foundation Model enables deep interactions with medical images, providing insights beyond human perception. Clinicians and caregivers can ask questions and add clinical context to inform real-time decisions—whether in the OR, billing, or bedside care.

HOPPR reduces workload, enhances accuracy, and boosts efficiency. It pre-generates full reports with highlighted findings, measurements, and impressions while supporting interactive API-driven exploration of images and reports. Radiologists can refine and finalize reports with their assessments, backed by comparison studies, key images, and research, for quick approval.  

For procedures like aneurysm coiling, HOPPR characterizes aneurysms (e.g., size, neck orientation) and predicts optimal approaches, materials, and success rates using multi-modality imaging. It also surfaces relevant research and similar cases while automating OR scheduling and resource allocation to improve outcomes and efficiency.

HOPPR-powered applications prioritize high-risk patients by flagging critical findings, such as bleeding or fractures, immediately after a scan. Surgeons can interact with the images to confirm details, schedule OR time, and coordinate care quickly, improving outcomes. 

Beyond clinical needs, academic centers benefit from HOPPR’s ability to automate research tasks like case curation and classification. As imaging drives advancements in diagnosis, treatment, and drug discovery, automating these functions becomes increasingly vital.

HOPPR automates billing and claims review, flagging discrepancies between images, reports, and claims before submission. It ensures facilities receive full payment and supports detailed claim investigations by providing insights into patient histories and outcomes.