RadNet’s DeepHealth, a leader in AI-powered health informatics, is partnering with HOPPR in an effort to commercialize a medical-grade generalized foundational AI model and develop fine-tuned models targeting breast, prostate, and lung cancer detection.
The arrangement combines DeepHealth’s expertise in radiology and HOPPR’s AI infrastructure.
HOPPR’s foundational models are designed to streamline data collection and enhance medical research, reducing development costs. These models serve as a base for creating task-specific Fine-Tuned models, which DeepHealth plans to incorporate into its AI portfolio to improve radiology workflows and patient outcomes.
Sham Sokka, chief operating and technology officer at DeepHealth, described the partnership as a “significant leap forward” in the company’s mission to integrate advanced diagnostic imaging technologies. HOPPR CEO Khan Siddiqui highlighted the potential to enhance clinical care by leveraging AI to improve both the efficiency and quality of medical imaging.
DeepHealth’s technology is currently used in over 800 clinical sites, supporting millions of exams annually. Its solutions have demonstrated real-world efficacy, particularly in breast cancer screening, where they have the potential to improve detection rates by up to 18%.
This partnership aims to bring new AI-driven innovations to medical imaging, with plans to unveil additional use cases later this year.
