HOPPR announces the release of its 2D Mammography Foundation Model, a Vision Transformer-based model built to accelerate AI development in breast imaging. The model supports fine-tuning across diverse diagnostic tasks, empowering faster innovation in early detection and breast health.

Some firms, such as Aidoc, are working directly with the FDA. Others, such as HOPPR, are offering their foundation models for medtech companies to build their own AI tools.

TestDynamics has partnered with HOPPR to offer a secure development infrastructure for medical imaging within a quality management system, traceability of data provenance, and version control as part of its Satori AI Platform.

Imaging AI software developer HOPPR and TestDynamics have collaborated on the creation of an AI-based development infrastructure for medical imaging that can be incorporated into a quality management system.

The HOPPR Marie Curie Chest Radiography Model enables partners to fine-tune and deploy binary classifiers for chest X-ray images using their own data with API access, structured outputs, and usage billing. 

Backed by top-tier investors, HOPPR is scaling its secure platform for enabling developers and medical imaging vendors to build, refine, and deploy AI applications for medical imaging.    

HOPPR, a leader in AI for medical imaging, has strengthened its leadership team by appointing four new executives, including Dr. William Boonn as CMO, Dr. Woojin Kim as Chief Strategy and CMO, Dr. Melanie Traughber as COO, and Keith Corbin as CFO. These additions come as HOPPR accelerates its mission to revolutionize radiology with its AI-powered platform. The company also announced a strategic partnership with the University of Miami's CARTA center to advance AI validation and improve medical imaging tools, aiming to enhance AI accuracy and performance in clinical settings.

HOPPR is teaming up with Amazon Web Services (AWS) to launch a cutting-edge AI platform designed to transform chest X-ray and mammography diagnostics. By harnessing AWS’s powerful cloud infrastructure and AI tools, this platform allows developers to fine-tune models for faster, more accurate diagnostic results. Aimed at enhancing early detection and streamlining radiology workflows, this collaboration promises to drive innovation and improve patient outcomes in healthcare.

HOPPR and Viz.ai have announced a five-year partnership to integrate HOPPR’s medical-grade AI foundation model with Viz.ai’s care coordination tools. The collaboration will debut solutions for detecting pulmonary fibrosis and screening lung CTs, aiming to transform diagnostics and streamline clinical workflows.

HOPPR, a leader in scalable medical-grade infrastructure for medical imaging AI, has partnered with NSF University of Miami’s Center for Accelerated Real-Time Analytics (CARTA). This collaboration seeks to develop innovative tools for evaluating and deploying medical-grade AI foundational models in healthcare, paving the way for advanced clinical AI applications.

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.

HOPPR is thrilled to partner with DeepHealth to redefine the possibilities in health informatics!

Together, we’re driving innovation in radiology with a cutting-edge Medical-Grade Generalized Foundational Model, backed by DeepHealth’s deep clinical expertise and proven success in scaling AI tools for real-world use.

Serial entrepreneur, world renowned radiologist and AI pioneer, Dr Khan Siddiqui's impact in both healthcare & AI is undeniable.

HOPPR, a portfolio company created via investment from the AMA, recently announced the launch of a generative augmented intelligence (AI) model that aims to dramatically improve the way physicians interact with medical images. 

HOPPR has officially announced the launch of a new multi-modal foundation model for medical imaging called Grace. Powered by Amazon Web Services, Grace is the first-of-its-kind B2B foundation model which enables image-to-image and text-to-image learning across all medical imaging modalities, including X-rays, CTs, MRIs, and echocardiograms.