share_log

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 ·  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 已建立战略合作,为图像解释创建独特的人工智能 (AI) 控制系统,以确保人工智能的可扩展性、性能监控和安全性,旨在加速人工智能的采用。
  • DeepHealth目前在RadNet上监控DeepHealth由人工智能驱动的乳腺癌检测解决方案的性能。通过合作,两家公司的目标是将该控制系统扩展、产品化并扩展到更多应用程序,以供其他客户使用。
  • 此外,DeepHealth 将嵌入 CARPL.ai 尖端的人工智能编排功能,从而在DeepHealth的云原生操作系统DeepHealth OS中轻松选择、实施和监控适当的人工智能模型。

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萨默维尔,2024年12月1日(GLOBE NEWSWIRE)——人工智能健康信息学领域的全球领导者、RadNet, Inc.(纳斯达克股票代码:RDNT)的全资子公司DeepHealth, Inc.今天宣布与领先的人工智能编排公司 CARPL.ai 进行战略合作,使放射科医生能够访问、评估放射学人工智能解决方案并将其集成到其工作流程中。DeepHealth 将使用 CARPL.ai 的技术开发一种可以商业化的人工智能控制系统,旨在监测和优化成像 AI 性能,以改善临床结果、运营效率并加快人工智能在放射学中的采用。人工智能监控对于确保可靠、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.

两家公司将合作开发一个新的闭环人工智能反馈系统,该系统将持续监测人工智能模型在临床环境中的准确性和相关性。该系统将自动测量和监控性能和安全指标,例如特异性、灵敏度、数据和模型漂移。

"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.

“使用监控工具建立强大的人工智能基础设施是放射学领域安全、有效和可扩展地采用人工智能的关键。尽管当前的格局以大量支持人工智能的单点解决方案为标志,但未来将涉及运行多个人工智能模型,即使是单个用例也是如此。DeepHealth 与 CARPL.ai 的合作通过创建独特的环境来动态运行模型组合和监控性能,然后持续优化针对特定任务的最佳模型,从而满足这一需求。” DeepHealth首席运营和技术官沙姆·索卡博士说。

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.

该合作伙伴关系还将把 CARPL.ai 的人工智能市场和编排平台与 DeepHealth 的云原生操作系统 DeepHealth 的云原生操作系统 DeepHealth OS 相结合,后者为选择、实施和监控第三方 FDA 批准的人工智能模型提供了简化的流程,后者统一了临床和运营工作流程中的数据。这些平台将进行集成和扩展,以持续监控现实世界的工作流程。目的是使放射科医生能够访问深度集成到其工作流程中的高性能和安全的人工智能解释工具。

"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."

“我们很高兴与DeepHealth合作,利用人工智能在放射科护理领域的变革潜力,特别是通过工作流程自动化和临床援助。CARPL.ai 首席执行官维杜尔·马哈詹博士说,这种新的人工智能基础设施将使人工智能成为系统不可或缺的组成部分,从而从根本上重新定义放射学。“监控人工智能性能对于确保人工智能应用程序在一段时间内的可靠性和准确性至关重要,我们的技术可以实时监控其准确性和一致性,从而在临床实践中安全有效地使用人工智能。”

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

欲了解更多信息,请访问北美放射学会2024年年会的DeepHealth (#1340) 和 CARPL.ai (#5733) 展位。

About RadNet, Inc.

关于 RadNet, Inc.

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 .

根据地点数量和年度成像收入,RadNet, Inc. 是美国领先的独立固定站点诊断成像服务全国提供商。RadNet拥有由399个自有和/或运营的门诊成像中心组成的网络。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还向诊断成像行业的客户提供以DeepHealth品牌销售的放射学信息技术和人工智能解决方案、远程放射学专业服务以及其他相关产品和服务。加上附属的放射科医生,包括全职和每日津贴的员工和技术人员,RadNet共拥有超过10,000名员工。欲了解更多信息,请访问。

About DeepHealth

关于深度健康

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是RadNet公司(纳斯达克股票代码:RDNT)的全资子公司,是RadNet数字健康领域所有公司的旗下品牌。DeepHealth 提供人工智能驱动的健康信息,旨在通过成像推动医疗领域的突破。凭借其整合并正在进行品牌重塑的公司(即eRad放射学信息和图像管理系统及图片存档和通信系统、Aidence肺部人工智能、DeepHealth和Kheiron乳房人工智能以及Quantib前列腺和大脑人工智能)的优势,DeepHealth利用先进的人工智能来提高运营效率并改善肺部、乳房、前列腺和大脑健康方面的临床结果。DeepHealth产品组合的核心是云原生操作系统——DeepHealth OS,它统一了临床和运营工作流程中的数据,并为放射学领域的每个人提供个性化的人工智能工作空间。全球数百个成像中心和放射科室的数千名放射科医生使用DeepHealth解决方案来实现更早、更可靠、更有效的疾病检测,包括在大规模癌症筛查计划中。DeepHealth 以人为本的直观技术旨在突破医疗保健领域可能性的界限。

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 是一个供应商中立的人工智能 (AI) 平台,允许放射科医生访问、评估放射学 AI 解决方案并将其集成到临床实践中。
CARPL 为临床放射学工作流程中的 AI 解决方案的测试、部署和监控提供单一用户界面、单一数据通道和单一采购渠道。
我们是世界上最大的放射学人工智能市场,提供来自60多家人工智能供应商的140多种应用程序。
欲了解更多信息,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1995年《美国私人证券诉讼改革法》安全港条款所指的 “前瞻性陈述”。前瞻性陈述,包括有关RadNet、CARPL.ai 和DeepHealth的信息学、硬件和软件产品组合的能力以及合作对放射学实践和医疗保健工作流程的影响的陈述,表达了我们当前对业务未来、未来计划和战略、预测以及预期的未来状况、事件和趋势的信念、期望和假设。前瞻性陈述通常可以用诸如 “预测”、“打算”、“计划”、“目标”、“寻求”、“相信”、“项目”、“估计”、“预期”、“战略”、“未来”、“可能”、“应该”、“将” 等词语以及对未来时期的类似提法来识别。

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.

前瞻性陈述既不是历史事实,也不是对未来表现的保证。由于前瞻性陈述与未来有关,因此它们本质上会受到不确定性、风险和环境变化的影响,这些不确定性、风险和情况变化难以预测,其中许多是我们无法控制的。我们的实际业绩和财务状况可能与前瞻性陈述中显示的业绩和财务状况存在重大差异。因此,您不应过分依赖任何前瞻性陈述。

For media inquiries, reach out to:

媒体垂询,请联系:

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

深度健康
安德拉·阿森特
传播总监
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.
马克·斯托珀
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—营销
+919811189074


声明:本内容仅用作提供资讯及教育之目的,不构成对任何特定投资或投资策略的推荐或认可。 更多信息
    抢沙发