CHICAGO--(BUSINESS WIRE)--GE HealthCare (Nasdaq: GEHC) today announced a new AI Innovation Lab, an initiative designed to accelerate early-concept AI innovations within the company. These projects are one part of GE HealthCare’s broader AI and digital strategy, which is focused on integrating AI into medical devices, building AI applications that enhance decision-making across the care journey and disease states, and using AI to support better outcomes and operational efficiencies system-wide.

芝加哥--（商业新闻短讯）--GE HealthCare（纳斯达克：GEHC）今天宣布成立一个新的人工智能创新实验室，旨在加速公司内部早期概念人工智能创新。这些项目是GE HealthCare更广泛的人工智能和数字战略的一部分，该战略的重点是将人工智能集成到医疗设备中，构建人工智能应用程序，以增强整个护理过程和疾病状态的决策，并使用人工智能支持全系统更好的结果和运营效率。

The company’s investment in cloud technology underpins this strategy, providing the computing power to drive the development of AI at scale..

该公司对云技术的投资支持了这一战略，提供了计算能力来推动人工智能的大规模发展。。

'The AI Innovation Lab lifts the curtain on the work we are undertaking at the vanguard of healthcare innovation. At GE HealthCare, we're not just developing technology—we're striving to break new ground by exploring novel ways that AI could enable healthcare. For example, through projects like Health Companion, we are evaluating ways to apply agentic AI in order to bring the clinical knowledge and problem-solving insights of a multi-disciplinary medical team to clinicians’ fingertips and help them take action,” said Dr.

“人工智能创新实验室揭开了我们在医疗创新先锋所做工作的帷幕。在GE HealthCare，我们不仅在开发技术，还通过探索人工智能可以实现医疗保健的新方法，努力开创新局面。例如，通过像Health Companion这样的项目，我们正在评估应用代理人工智能的方法，以便将多学科医疗团队的临床知识和解决问题的见解带到临床医生的指尖，并帮助他们采取行动。

Taha Kass-Hout, GE HealthCare's Global Chief Science and Technology Officer. “The pioneering projects we’re showcasing today are just some of the innovations we have underway, enabled by our AI and cloud computing capabilities. We will continue to gather feedback from our customers as we find ways to help them apply AI to their health data and convert information into actionable, care-enhancing strategies.”.

GE HealthCare全球首席科技官塔哈·卡斯·霍特（Taha Kass Hout）。。

GE HealthCare’s AI and cloud-related research and development efforts are focused on redefining the day-to-day experience of clinicians by creating new concepts to enhance the accuracy of diagnostics, reduce administrative burdens, and ensure that every patient receives the most informed, personalized care possible.

GE HealthCare的人工智能和云相关研究与开发工作的重点是通过创建新概念来重新定义临床医生的日常经验，以提高诊断的准确性，减轻管理负担，并确保每位患者都能获得尽可能多的知情个性化护理。

Examples of these concept projects:.

这些概念项目的例子：。

Bringing the knowledge of a multi-disciplinary team to clinicians’ fingertips with agentic AI: The Health Companion project explores whether an agentic AI approach driven by multiple agents, each an expert in a particular area (i.e., genomics, radiology, pathology, etc.), could help physicians streamline their clinical decision-making and deliver more personalized care.

通过代理人工智能将多学科团队的知识带到临床医生的指尖：Health Companion项目探索由多个代理驱动的代理人工智能方法，每个代理都是特定领域的专家（即基因组学，放射学，病理学等），是否可以帮助医生简化临床决策并提供更个性化的护理。

The project’s vision is for these agents to collaborate and analyze multi-modal data in order to proactively generate treatment plan recommendations, continuously adapting based on new information. For example, GE HealthCare is exploring whether multi-agentic AI could understand the difference between an expected symptom as a function of treatment, and the same symptom as a signal of disease progression, such as cancer spread with the goal to alert the care team as appropriate with suggested next steps.

该项目的愿景是让这些代理协作并分析多模式数据，以便主动生成治疗计划建议，并根据新信息不断调整。例如，GE HealthCare正在探索多代理AI是否可以理解作为治疗功能的预期症状与作为疾病进展信号的相同症状之间的差异，例如癌症传播，目的是提醒护理团队适当采取建议的下一步措施。

Health Companion aims to provide the collaboration and discussion similar to a multi-disciplinary care team that is made up of specialized clinicians. This project is being built to incorporate safety and explainability principles..

Health Companion旨在提供类似于由专业临床医生组成的多学科护理团队的合作和讨论。该项目旨在纳入安全性和可解释性原则。。

Using AI to better predict triple negative breast cancer recurrence: GE HealthCare is supporting the Winship Cancer Institute of Emory University on research focused on the early prediction of triple negative breast cancer recurrence. Triple negative breast cancer is the most aggressive breast cancer subtype, however, there is a shortage of tools to predict its recurrence.

使用人工智能更好地预测三阴性乳腺癌复发：GE HealthCare正在支持埃默里大学Winship癌症研究所进行专注于早期预测三阴性乳腺癌复发的研究。三阴性乳腺癌是最具侵袭性的乳腺癌亚型，然而，缺乏预测其复发的工具。

Today, as many as 50% of patients diagnosed with early-stage triple negative breast cancer (stages I to III) experience recurrence.i The goal of this research is to use deep learning to evaluate multi-modal data including genomics and pathology information to investigate if AI can better predict the likelihood of recurrence, and help the care team inform a treatment plan and monitoring schedule.

今天，多达50%的被诊断患有早期三阴性乳腺癌（I至III期）的患者经历了复发。本研究的目的是利用深度学习来评估多模式数据，包括基因组学和病理学信息，以调查AI是否可以更好地预测复发的可能性，并帮助护理团队告知治疗计划和监测时间表。

This research is being funded by a grant from the National Institutes of Health (NIH Grant# 1R01CA281932-01A1). Dr. Sunil Badve from Emory University is the Principal Investigator (PI), and Dr. Soumya Ghose is the Co-PI from GE HealthCare for this project..

这项研究由美国国立卫生研究院（NIH grant#1R01CA281932-01A1）资助。埃默里大学的Sunil Badve博士是该项目的首席研究员（PI），Soumya Ghose博士是GE HealthCare的联合PI。。

Innovating solutions to enhance care for moms and babies: Preventable risks associated with childbirth are one of the most pressing health issues facing women today. GE HealthCare is working directly with health systems and their care teams to develop solutions that help address this challenge. For example, GE HealthCare is working on a care companion initiative that is investigating how generative AI could minimize the effort spent searching through data and seeking best practices.

创新解决方案以加强对母亲和婴儿的护理：与分娩相关的可预防风险是当今女性面临的最紧迫的健康问题之一。。例如，GE HealthCare正在开展一项护理伴侣计划，该计划正在调查生成性人工智能如何最大程度地减少搜索数据和寻求最佳实践的工作量。

Powered by a large language model, this initiative intends to further explore how to make it easy for care teams to quickly find information about standard care protocols and clinical definitions and generate patient summarizations using historical and current multi-modal data for potential use in handoffs and care transitions..

在大型语言模型的支持下，该计划旨在进一步探索如何使护理团队能够轻松快速找到有关标准护理协议和临床定义的信息，并使用历史和当前的多模式数据生成患者摘要，以潜在地用于交接和护理过渡。。

Researching multi-modal X-ray foundation model: GE HealthCare is working on a research project to create a full-body foundation model, built on a dataset of 1.2 million anonymized PHI-free X-ray images from diverse regions across the body. This model shows great potential, and is yielding promising early internal benchmark testing on key tasks including segmentation, classification, and visual localization.

研究多模式X射线基金会模型：GE HealthCare正在进行一项研究项目，以创建一个全身基金会模型，该模型基于来自全身不同区域的120万张匿名无PHI X射线图像的数据集。该模型显示出巨大的潜力，并在关键任务（包括分割，分类和视觉定位）上产生了有前途的早期内部基准测试。

The project is also experimenting with having the model automate medical report generation and interpret images into text to accelerate the workflow for radiologists, with the aim to help alleviate care teams’ administrative burdens. The goal of GE HealthCare’s research in this area is to provide practical value by reducing the cognitive burden to healthcare professionals seeking efficient and reliable tools for diagnostics.

该项目还尝试让该模型自动生成医疗报告并将图像解释为文本，以加速放射科医生的工作流程，旨在帮助减轻护理团队的管理负担。GE HealthCare在这一领域的研究目标是通过减轻寻求高效可靠诊断工具的医疗保健专业人员的认知负担来提供实用价值。

The model is being developed as a result of GE HealthCare’s strategic collaboration with Amazon Web Services..

该模型是GE HealthCare与亚马逊网络服务战略合作的结果。。

Helping radiologists scale mammography screenings: Approximately 90% of screening mammograms in the U.S. are normal, yet there is no efficient way for radiologists to quickly separate the clearly normal scans from potentially suspicious ones.ii GE HealthCare is developing this cloud-based AI concept to explore how foundation models can help clinicians quickly identify normal breast screening exams, allowing radiologists to focus more of their time on suspicious cases.

帮助放射科医生扩大乳房X光检查的规模：美国大约90%的乳房X光检查是正常的，但放射科医生没有有效的方法来快速区分明显正常的扫描和潜在可疑的扫描。GE HealthCare正在开发这种基于云的AI概念，以探索基础模型如何帮助临床医生快速识别正常的乳房筛查检查，从而使放射科医生将更多的时间集中在可疑病例上。

As countries grapple with a radiologist shortage, GE HealthCare aims to work with strategic and clinical collaborators to make advances in this space to help enhance accuracy, scale screenings, and improve access to this critical type of preventive care globally..

随着各国努力解决放射科医生短缺的问题，GE HealthCare旨在与战略和临床合作者合作，在这一领域取得进展，以帮助提高准确性，扩大筛查规模，并在全球范围内改善对这一关键类型预防保健的获取。。

GE HealthCare is working on AI-enabled innovations that run the gamut in terms of maturity and market-readiness. For example, GE HealthCare has submitted a 510(k) with the U.S. Food and Drug Administration (FDA) requesting clearance of a new solution to address the needs of clinicians in providing care for moms and babies.

GE HealthCare正在致力于AI支持的创新，这些创新在成熟度和市场准备度方面都有广泛的应用。例如，GE HealthCare向美国食品和药物管理局（FDA）提交了510（k），要求批准一种新的解决方案，以满足临床医生在为母亲和婴儿提供护理方面的需求。

This AI-powered fetal heart rate interpretation feature (FHR AI, FDA 510(k)-submitted)iii applies deep learning to waveform data to analyze fetal heart rate. This feature is designed to identify events such as accelerations and decelerations of fetal heart rates to help care teams quickly understand the baby’s health, improving what is currently a highly manual and subjective task..

这种人工智能驱动的胎儿心率解释功能（FHR AI，FDA 510（k）-提交）iii将深度学习应用于波形数据以分析胎儿心率。此功能旨在识别胎儿心率加速和减速等事件，以帮助护理团队快速了解婴儿的健康状况，改善目前高度手动和主观的任务。。

These projects showcase the groundbreaking work underway at GE HealthCare, a company that applies a 125-year legacy of innovation with the energy of a start-up as it works to help solve the healthcare industry’s most pressing challenges. GE HealthCare has been investing in AI for years and has topped an FDA list of AI-enabled device authorizations for three years in a row with 80 authorizations.iv.

这些项目展示了GE HealthCare正在进行的开创性工作。GE HealthCare是一家拥有125年创新传统的公司，以初创企业的活力帮助解决医疗行业最紧迫的挑战。GE HealthCare多年来一直在投资人工智能，并连续三年以80项授权名列FDA人工智能设备授权榜首。

To learn more about these projects, visit GE HealthCare in the AI Pavilion at booth #3816 at HLTH 2024 in Las Vegas, NV from October 20-23 or visit https://www.gehealthcare.com.

要了解有关这些项目的更多信息，请于10月20日至23日在内华达州拉斯维加斯HLTH 2024的AI展馆（展位#3816）参观GE HealthCare，或访问https://www.gehealthcare.com.

About GE HealthCare Technologies Inc.

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GE HealthCare is a leading global medical technology, pharmaceutical diagnostics, and digital solutions innovator, dedicated to providing integrated solutions, services, and data analytics to make hospitals more efficient, clinicians more effective, therapies more precise, and patients healthier and happier.

GE HealthCare是全球领先的医疗技术、药物诊断和数字解决方案创新者，致力于提供集成的解决方案、服务和数据分析，使医院更高效、临床医生更有效、治疗更精确，患者更健康、更快乐。

Serving patients and providers for more than 125 years, GE HealthCare is advancing personalized, connected, and compassionate care, while simplifying the patient’s journey across the care pathway. Together our Imaging, Ultrasound, Patient Care Solutions, and Pharmaceutical Diagnostics businesses help improve patient care from diagnosis, to therapy, to monitoring.

GE HealthCare为患者和提供者服务了125多年，正在推进个性化、互联化和富有同情心的护理，同时简化患者跨越护理路径的旅程。我们的成像、超声波、患者护理解决方案和药物诊断业务共同帮助改善患者护理，从诊断到治疗再到监测。

We are a $19.6 billion business with approximately 51,000 colleagues working to create a world where healthcare has no limits..

我们是一家价值196亿美元的企业，拥有约51000名员工，致力于创造一个医疗保健无限的世界。。

Follow us on LinkedIn, X , Facebook, Instagram, and Insights for the latest news, or visit our website https://www.gehealthcare.com/ for more information.

在LinkedIn、X、Facebook、Instagram和Insights上关注我们的最新消息，或访问我们的网站https://www.gehealthcare.com/了解更多信息。

i National Institutes of Health, “Early prediction of lethal phenotypes in triple negative breast cancer using multiscale, multi-modality platforms,” https://reporter.nih.gov/project-details/10883284.

i National Institutes of Health，“使用多尺度，多模式平台早期预测三阴性乳腺癌的致命表型”https://reporter.nih.gov/project-details/10883284.

ii “Breast Cancer Screening (PDQ®)–Health Professional Version,” March 28, 2024, https://www.cancer.gov/types/breast/hp/breast-screening-pdq.

ii“乳腺癌筛查（PDQ®）-健康专业版”，2024年3月28日，https://www.cancer.gov/types/breast/hp/breast-screening-pdq.

iii The FHR AI 510(k) has been submitted to the FDA and is not currently available for sale in the United States.

iii FHR AI 510（k）已提交给FDA，目前尚未在美国销售。

iv U.S. Food and Drug Administration, “Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices,” August 7, 2024, https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices.

iv美国食品和药物管理局，“人工智能和机器学习（AI/ML）支持的医疗设备”，2024年8月7日，https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices.