CAMBRIDGE, Mass., Sept. 05, 2024 (GLOBE NEWSWIRE) -- DeepHealth, a wholly-owned subsidiary of RadNet, Inc. (NASDAQ: RDNT) and a global leader in AI-powered radiology and health informatics, today announces a data and AI development partnership with HOPPR (www.hoppr.ai). This collaboration will commercialize a pioneering Medical-Grade Generalized Foundational Model and foster the development of Fine-Tuned models for breast, prostate, and lung cancer detection, leveraging generative medical imaging-focused AI and robust, diverse data sets.

马萨诸塞州剑桥，2024年9月5日（环球通讯社）--DeepHealth是RadNet，Inc.（纳斯达克代码：RDNT）的全资子公司，也是人工智能驱动的放射学和健康信息学的全球领导者，今天宣布与HOPPR（www.HOPPR.AI）建立数据和人工智能开发合作伙伴关系。这项合作将使开创性的医学级广义基础模型商业化，并促进乳腺癌，前列腺癌和肺癌检测的微调模型的开发，利用以生成医学成像为重点的人工智能和强大多样的数据集。

HOPPR’s Medical-Grade Generalized Foundation Model enhances medical research and hypotheses while simplifying and lowering costs for data collection and training. AI Foundational Models are versatile, pre-trained architectures that serve as a starting point for customizing specific tasks through Fine-Tuned models, for which expertise in a particular domain is critical.

HOPPR的医学级广义基础模型增强了医学研究和假设，同时简化并降低了数据收集和培训的成本。人工智能基础模型是多功能的、经过预先训练的体系结构，可以作为通过微调模型定制特定任务的起点，而特定领域的专业知识对于这些模型至关重要。

The partnership seeks to create new Fine-Tuned models, powered by HOPPR’s Medical-Grade Generalized Foundation Model, to bolster DeepHealth’s AI-powered health informatics portfolio by enabling it to create future solutions more quickly and efficiently and to support the evolution of radiology in the coming years.

该合作伙伴关系寻求在HOPPR的医学级广义基金会模型的支持下创建新的微调模型，以支持DeepHealth的人工智能支持的健康信息学组合，使其能够更快，更有效地创建未来的解决方案，并支持未来几年放射学的发展。

DeepHealth’s cloud-native operating system (OS) is designed to integrate clinical and operational tools, to provide radiology workflow efficiencies and improve patient outcomes. Sham Sokka, PhD, Chief Operating and Technology Officer, DeepHealth, said, “DeepHealth’s partnership with HOPPR is a significant leap forward in DeepHealth’s mission to empower breakthroughs in care through enabling new diagnostic imaging technologies.” “The integration of Foundational Models like those being developed by HOPPR in medical imaging is intended to boost diagnostic accura.

DeepHealth的云本机操作系统（OS）旨在集成临床和操作工具，以提供放射工作流程效率并改善患者预后。DeepHealth首席运营和技术官Sham Sokka博士表示，“DeepHealth与HOPPR的合作是DeepHealth使命的重大飞跃，通过启用新的诊断成像技术来实现护理突破。”“HOPPR在医学成像领域开发的基础模型的整合旨在提高诊断准确性。