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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全資子公司DeepHealth將使用CARPL.ai平台開發新的人工智能控制系統,以提高臨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建立了戰略合作關係,以創建一個獨特的人工智能(AI)控制系統用於圖像解讀,以確保AI的可擴展性、性能監測和安全性,旨在加速AI的採用。
  • DeepHealth目前在RadNet監測DeepHealth的SmartMammo AI驅動的乳腺癌檢測解決方案的性能。通過此次合作,兩家公司旨在擴大、產品化並將該控制系統推廣到其他客戶的更多應用中。
  • 此外,DeepHealth將嵌入CARPL.ai的先進AI編排能力,使得在DeepHealth的雲原生操作系統DeepHealth OS中輕鬆選擇、實施和監控適當的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.

洛杉磯和馬薩諸塞州索美維爾,2024年12月1日(全球新聞網)——DeepHealth, Inc.是全球領先的AI驅動健康信息學公司,且爲RadNet, Inc.(納斯達克:RDNT)的全資子公司,今天宣佈與領先的AI編排公司CARPL.ai建立戰略合作關係,CARPL.ai使放射科醫師能夠在其工作流程中訪問、評估和整合放射學AI解決方案。DeepHealth將利用CARPL.ai的技術開發一個可商業化的AI控制系統,旨在監測和優化影像AI性能,以改善臨床結果、提升運營效率,並加速AI在放射學中的採用。AI監測對於確保可靠、準確和公正的性能至關重要。

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.

這兩家公司將合作開發一個新的閉環AI反饋系統,不斷監測臨床環境中AI模型的準確性和相關性。該系統將自動測量和監控性能和安全指標,例如特異性、敏感性、數據-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.

"建立一個堅實的AI基礎設施並配備監控工具是安全、有效和可擴展AI在放射學中採用的關鍵。儘管當前環境充斥着大量AI驅動的點解決方案,但未來將涉及運行多個AI模型,即使是對於單一用例。DeepHealth與CARPL.ai的合作正好滿足了這一需求,通過創建一個獨特的環境來動態運行模型組合並監控性能,然後持續優化特定任務的最佳模型,”DeepHealth的首席運營和科技官Sham Sokka博士說。

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.

該合作伙伴關係將結合CARPL.ai的人工智能市場和編排平台,該平台提供簡化的選擇、實施和監控第三方FDA批准的人工智能模型的過程,以及DeepHealth的雲原生操作系統DeepHealth OS,該系統統一了臨床和運營工作流程中的數據。這些平台將集成並擴展,以持續監控現實世界的工作流程。目標是使放射科醫生能夠訪問功能強大且安全的人工智能解讀工具,這些工具深度集成在他們的工作流程中。

"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的首席執行官Vidur Mahajan博士表示:「我們非常高興能與DeepHealth合作,利用人工智能在放射科護理中的變革潛力,特別是在工作流程自動化和臨床協助方面。這個新的人工智能基礎設施將根本性地重新定義放射科,使人工智能成爲系統的一個重要組成部分。」 「監控人工智能性能是確保人工智能應用在時間上的可靠性和準確性的關鍵,我們的技術能夠實現其準確性和一致性的實時性能監控,以安全和有效地在臨床實踐中使用人工智能。」

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

有關更多信息,請訪問深健康(#1340)和CARPL.ai(#5733)在2024年美國放射學會年會的展位。

About RadNet, Inc.

關於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. 是美國最大的獨立、固定地點診斷影像服務提供商,基於其位置數量和年度影像營業收入。radnet 擁有 399 個自有和/或經營的門診影像中心。radnet 的市場包括亞利桑那州、加利福尼亞州、特拉華州、佛羅里達州、馬里蘭州、新澤西州、紐約州和德克薩斯州。此外,radnet 提供放射學信息技術和人工智能解決方案,品牌名爲 DeepHealth,遠程放射專業服務以及其他相關產品和服務,面向診斷影像行業的客戶。與關聯放射科醫生一起,包括全職和按需僱員及技術人員,radnet 的總員工超過 10,000 人。有關更多信息,請訪問。

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

關於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是一箇中立的人工智能平台,允許放射科醫生在其臨床實踐中訪問、評估和整合放射學人工智能解決方案。
CARPL提供一個單一的用戶界面、一個單一的數據通道和一個單一的採購通道,用於在臨床放射學工作流程中測試、部署和監控人工智能解決方案。
我們是全球最大的放射學人工智能市場,提供來自60多個人工智能供應商的140多個應用程序。
要獲取更多信息,請訪問

Forward Looking Statement

前瞻性聲明

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.

本新聞稿包含符合1995年美國私人證券訴訟改革法案安全港條款的「前瞻性聲明」。前瞻性聲明,包括關於radnet、CARPL.ai和DeepHealth的信息學、硬件和軟件產品組合及其對放射科實踐和醫療工作流程的影響的聲明,表達了我們當前對業務未來、未來計劃和策略、預測以及預計未來條件、事件和趨勢的信念、預期和假設。前瞻性聲明通常可以通過以下詞語識別:"預期"、"意圖"、"計劃"、"目標"、"尋求"、"相信"、"預測"、"估計"、"期望"、"策略"、"未來"、"可能"、"也許"、"應該"、"將"及類似的未來時期的引用。

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.

展望性聲明既非歷史事實,也非未來業績保證。由於展望性聲明涉及未來,它們固有地受到難以預測的不確定因素、風險和環境變化的影響,其中許多不在我們的控制範圍之內。我們的實際結果和財務狀況可能與展望性聲明中所示有實質性差異。因此,請不要過度依賴這些展望性聲明。

For media inquiries, reach out to:

如需媒體諮詢,請聯繫:

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

DeepHealth
安德拉·阿克先特
通信-半導體主任
電話:+31 614 440971
電子郵件: andra.axente@deephealth.com

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

RadNet,Inc.
Mark Stolper
執行副總裁兼首席財務官
310-445-2800

CARPL.ai
Shruti Singhal
Director – Marketing
+919811189074

CARPL.ai
Shruti Singhal
董事 – 市場營銷
+919811189074


譯文內容由第三人軟體翻譯。


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