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RadNet's Wholly-Owned Subsidiary, DeepHealth, to Use CARPL.ai's Platform to Develop a New AI Control System for Clinical AI Performance and Safety

RadNet's Wholly-Owned Subsidiary, DeepHealth, to Use CARPL.ai's Platform to Develop a New AI Control System for Clinical AI Performance and Safety

radnet全资子公司DeepHealth将使用CARPL.ai平台开发新的人工智能控制系统,以提高临床人工智能的性能和安全性
GlobeNewswire ·  2024/12/01 20:00
  • DeepHealth and CARPL.ai have established a strategic collaboration to create a unique Artificial Intelligence (AI) control system for image interpretation to ensure AI scalability, performance monitoring, and safety, with the aim to accelerate the adoption of AI.
  • DeepHealth currently monitors the performance of DeepHealth's SmartMammo AI-powered solution for breast cancer detection at RadNet. Through the collaboration, the two companies aim to expand, productize and scale this control system across more applications to other customers.
  • Furthermore, DeepHealth will embed CARPL.ai's cutting-edge AI orchestration capabilities that enable easy selection, implementation, and monitoring of appropriate AI models within DeepHealth's cloud-native operating system, DeepHealth OS.
  • DeepHealth和CARPL.ai建立了战略合作关系,以创建一个独特的人工智能(AI)控制系统用于图像解读,以确保AI的可扩展性、性能监测和安全性,旨在加速AI的采用。
  • DeepHealth目前在RadNet监测DeepHealth的SmartMammo AI驱动的乳腺癌检测解决方案的性能。通过此次合作,两家公司旨在扩大、产品化并将该控制系统推广到其他客户的更多应用中。
  • 此外,DeepHealth将嵌入CARPL.ai的先进AI编排能力,使得在DeepHealth的云原生操作系统DeepHealth OS中轻松选择、实施和监控适当的AI模型。

LOS ANGELES and SOMERVILLE, Mass., Dec. 01, 2024 (GLOBE NEWSWIRE) -- DeepHealth, Inc., a global leader in AI-powered health informatics and a wholly-owned subsidiary of RadNet, Inc. (NASDAQ: RDNT), today announced a strategic collaboration with CARPL.ai, a leading AI orchestration company that enables radiologists to access, assess, and integrate radiology AI solutions in their workflows. DeepHealth will use CARPL.ai's technology to develop an AI control system that can be commercialized and will be designed to monitor and optimize imaging AI performance for improved clinical outcomes, operational efficiency, and accelerated adoption of AI in radiology. AI monitoring is crucial to ensure reliable, accurate, and unbiased performance.

洛杉矶和马萨诸塞州索美维尔,2024年12月1日(全球新闻网)——DeepHealth, Inc.是全球领先的AI驱动健康信息学公司,且为RadNet, Inc.(纳斯达克:RDNT)的全资子公司,今天宣布与领先的AI编排公司CARPL.ai建立战略合作关系,CARPL.ai使放射科医师能够在其工作流程中访问、评估和整合放射学AI解决方案。DeepHealth将利用CARPL.ai的技术开发一个可商业化的AI控制系统,旨在监测和优化影像AI性能,以改善临床结果、提升运营效率,并加速AI在放射学中的采用。AI监测对于确保可靠、准确和公正的性能至关重要。

The two companies will collaborate on a new closed-loop AI feedback system that will continually monitor AI model accuracy and relevance in clinical settings. The system will automate the measurement and monitoring of performance and safety metrics such as specificity, sensitivity, data- and model drift.

这两家公司将合作开发一个新的闭环AI反馈系统,不断监测临床环境中AI模型的准确性和相关性。该系统将自动测量和监控性能和安全指标,例如特异性、敏感性、数据-模型漂移。

"Establishing a robust AI infrastructure with monitoring tools is key for safe, effective, and scalable AI adoption in radiology. While the current landscape is marked by an overwhelming array of AI-enabled point solutions, the future involves running multiple AI models, even for a single use case. DeepHealth's partnership with CARPL.ai addresses this very need by creating a unique environment to dynamically run a combination of models and monitor performance and then continuously optimize the best models for specific tasks," said Sham Sokka, PhD, Chief Operating and Technology Officer, DeepHealth.

"建立一个坚实的AI基础设施并配备监控工具是安全、有效和可扩展AI在放射学中采用的关键。尽管当前环境充斥着大量AI驱动的点解决方案,但未来将涉及运行多个AI模型,即使是对于单一用例。DeepHealth与CARPL.ai的合作正好满足了这一需求,通过创建一个独特的环境来动态运行模型组合并监控性能,然后持续优化特定任务的最佳模型,”DeepHealth的首席运营和科技官Sham Sokka博士说。

The partnership will also combine CARPL.ai's AI marketplace and orchestration platform, which offers a simplified process for selecting, implementing, and monitoring third-party FDA-cleared AI models, with DeepHealth's cloud-native operating system, DeepHealth OS, which unifies data across the clinical and operational workflows. These platforms will be integrated and extended to monitor real-world workflows on an ongoing basis. The aim is to enable radiologists to access performant and safe AI interpretation tools deeply integrated in their workflows.

该合作伙伴关系将结合CARPL.ai的人工智能市场和编排平台,该平台提供简化的选择、实施和监控第三方FDA批准的人工智能模型的过程,以及DeepHealth的云原生操作系统DeepHealth OS,该系统统一了临床和运营工作流程中的数据。这些平台将集成并扩展,以持续监控现实世界的工作流程。目标是使放射科医生能够访问功能强大且安全的人工智能解读工具,这些工具深度集成在他们的工作流程中。

"We are very excited to partner with DeepHealth to harness the transformative potential of AI within the radiology care continuum, particularly through workflow automation and clinical assistance. This new AI infrastructure is set to fundamentally redefine radiology by making AI an integral component of the system," said Dr. Vidur Mahajan, CEO of CARPL.ai. "Monitoring AI performance is essential to ensure the reliability and accuracy of AI applications over time, and our technology enables real-time performance monitoring of both their accuracy and consistency for safe and effective use of AI in clinical practice."

CARPL.ai的首席执行官Vidur Mahajan博士表示:“我们非常高兴能与DeepHealth合作,利用人工智能在放射科护理中的变革潜力,特别是在工作流程自动化和临床协助方面。这个新的人工智能基础设施将根本性地重新定义放射科,使人工智能成为系统的一个重要组成部分。” “监控人工智能性能是确保人工智能应用在时间上的可靠性和准确性的关键,我们的技术能够实现其准确性和一致性的实时性能监控,以安全和有效地在临床实践中使用人工智能。”

For more information, visit the DeepHealth (#1340) and CARPL.ai (#5733) booths at the Radiological Society of North America 2024 Annual Meeting.

有关更多信息,请访问深健康(#1340)和CARPL.ai(#5733)在2024年美国放射学会年会的展位。

About RadNet, Inc.

关于radnet公司。

RadNet, Inc. is the leading national provider of freestanding, fixed-site diagnostic imaging services in the United States based on the number of locations and annual imaging revenue. RadNet has a network of 399 owned and/or operated outpatient imaging centers. RadNet's markets include Arizona, California, Delaware, Florida, Maryland, New Jersey, New York and Texas. In addition, RadNet provides radiology information technology and artificial intelligence solutions marketed under the DeepHealth brand, teleradiology professional services and other related products and services to customers in the diagnostic imaging industry. Together with affiliated radiologists, and inclusive of full-time and per diem employees and technologists, RadNet has a total of over 10,000 employees. For more information, visit .

radnet, Inc. 是美国最大的独立、固定地点诊断影像服务提供商,基于其位置数量和年度影像营业收入。radnet 拥有 399 个自有和/或经营的门诊影像中心。radnet 的市场包括亚利桑那州、加利福尼亚州、特拉华州、佛罗里达州、马里兰州、新泽西州、纽约州和德克萨斯州。此外,radnet 提供放射学信息技术和人工智能解决方案,品牌名为 DeepHealth,远程放射专业服务以及其他相关产品和服务,面向诊断影像行业的客户。与关联放射科医生一起,包括全职和按需雇员及技术人员,radnet 的总员工超过 10,000 人。有关更多信息,请访问。

About DeepHealth

About DeepHealth

DeepHealth is a wholly-owned subsidiary of RadNet, Inc. (NASDAQ: RDNT) and serves as the umbrella brand for all companies within RadNet's Digital Health segment. DeepHealth provides AI-powered health informatics with the aim of empowering breakthroughs in care through imaging. Building on the strengths of the companies it has integrated and is rebranding (i.e., eRAD Radiology Information and Image Management Systems and Picture Archiving and Communication System, Aidence lung AI, DeepHealth and Kheiron breast AI and Quantib prostate and brain AI), DeepHealth leverages advanced AI for operational efficiency and improved clinical outcomes in lung, breast, prostate, and brain health. At the heart of DeepHealth's portfolio is a cloud-native operating system - DeepHealth OS - that unifies data across the clinical and operational workflow and personalizes AI-powered workspaces for everyone in the radiology continuum. Thousands of radiologists at hundreds of imaging centers and radiology departments around the world use DeepHealth solutions to enable earlier, more reliable, and more efficient disease detection, including in large-scale cancer screening programs. DeepHealth's human-centered, intuitive technology aims to push the boundaries of what's possible in healthcare.

DeepHealth is a wholly-owned subsidiary of RadNet, Inc. (NASDAQ: RDNT) and serves as the umbrella brand for all companies within RadNet's Digital Health segment. DeepHealth provides AI-powered health informatics with the aim of empowering breakthroughs in care through imaging. Building on the strengths of the companies it has integrated and is rebranding (i.e., eRAD Radiology Information and Image Management Systems and Picture Archiving and Communication System, Aidence lung AI, DeepHealth and Kheiron breast AI and Quantib prostate and brain AI), DeepHealth leverages advanced AI for operational efficiency and improved clinical outcomes in lung, breast, prostate, and brain health. At the heart of DeepHealth's portfolio is a cloud-native operating system - DeepHealth OS - that unifies data across the clinical and operational workflow and personalizes AI-powered workspaces for everyone in the radiology continuum. thousands of radiologists at hundreds of imaging centers and radiology departments around the world use DeepHealth solutions to enable earlier, more reliable, and more efficient disease detection, including in large-scale cancer screening programs. DeepHealth's human-centered, intuitive technology aims to push the boundaries of what's possible in healthcare.

About CARPL.ai

关于CARPL.ai

CARPL.ai is a vendor-neutral Artificial Intelligence (AI) platform that allows radiologists to access, assess, and integrate radiology AI solutions in their clinical practice.
CARPL provides a single user interface, a single data channel, and a single procurement channel for the testing, deployment, and monitoring of AI solutions in clinical radiology workflows.
We are the world's largest radiology AI marketplace offering 140+ applications from 60+ AI vendors.
For more information, visit

CARPL.ai是一个中立的人工智能平台,允许放射科医生在其临床实践中访问、评估和整合放射学人工智能解决方案。
CARPL提供一个单一的用户界面、一个单一的数据通道和一个单一的采购通道,用于在临床放射学工作流程中测试、部署和监控人工智能解决方案。
我们是全球最大的放射学人工智能市场,提供来自60多个人工智能供应商的140多个应用程序。
要获取更多信息,请访问

Forward Looking Statement

前瞻性声明

This press release contains "forward-looking statements" within the meaning of the safe harbor provisions of the U.S. Private Securities Litigation Reform Act of 1995. Forward-looking statements, including statements regarding the capabilities of RadNet, CARPL.ai, and DeepHealth's informatics, hardware and software product portfolios and the collaboration's impact on radiology practices and healthcare workflow, are expressions of our current beliefs, expectations, and assumptions regarding the future of our business, future plans and strategies, projections, and anticipated future conditions, events and trends. Forward-looking statements can generally be identified by words such as: "anticipate," "intend," "plan," "goal," "seek," "believe," "project," "estimate," "expect," "strategy," "future," "likely," "may," "should," "will" and similar references to future periods.

本新闻稿包含符合1995年美国私人证券诉讼改革法案安全港条款的“前瞻性声明”。前瞻性声明,包括关于radnet、CARPL.ai和DeepHealth的信息学、硬件和软件产品组合及其对放射科实践和医疗工作流程的影响的声明,表达了我们当前对业务未来、未来计划和策略、预测以及预计未来条件、事件和趋势的信念、预期和假设。前瞻性声明通常可以通过以下词语识别:"预期"、"意图"、"计划"、"目标"、"寻求"、"相信"、"预测"、"估计"、"期望"、"策略"、"未来"、"可能"、"也许"、"应该"、"将"及类似的未来时期的引用。

Forward-looking statements are neither historical facts nor assurances of future performance. Because forward-looking statements relate to the future, they are inherently subject to uncertainties, risks and changes in circumstances that are difficult to predict and many of which are outside of our control. Our actual results and financial condition may differ materially from those indicated in the forward-looking statements. Therefore, you should not place undue reliance on any of these forward-looking statements.

展望性声明既非历史事实,也非未来业绩保证。由于展望性声明涉及未来,它们固有地受到难以预测的不确定因素、风险和环境变化的影响,其中许多不在我们的控制范围之内。我们的实际结果和财务状况可能与展望性声明中所示有实质性差异。因此,请不要过度依赖这些展望性声明。

For media inquiries, reach out to:

如需媒体咨询,请联系:

DeepHealth
Andra Axente
Communications Director
Phone: +31 614 440971
Email: andra.axente@deephealth.com

DeepHealth
安德拉·阿克先特
通信-半导体主任
电话:+31 614 440971
电子邮件: andra.axente@deephealth.com

RadNet, Inc.
Mark Stolper
Executive Vice President and Chief Financial Officer
310-445-2800

RadNet,Inc.
Mark Stolper
执行副总裁兼首席财务官
310-445-2800

CARPL.ai
Shruti Singhal
Director – Marketing
+919811189074

CARPL.ai
Shruti Singhal
董事 – 市场营销
+919811189074


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