- Lunit to unveil four oral presentations and three poster presentations at ECR 2024, highlighting Lunit INSIGHT's expansive capability, ranging from adaptability in different use cases to the potential to replace a human reader in mammography double-reading settings SEOUL, South Korea, Feb. 28, 2024 /PRNewswire/ -- Lunit (KRX:328130.KQ), a leading provider of AI-powered solutions for cancer diagnostics and therapeutics, today announced the presentation of seven studies at the European Congress of Radiology (ECR) 2024, to be held in Vienna, Austria, from February 28 to March 3.

-Lunit将在ECR 2024上推出四个口头演示和三个海报演示，突出Lunit INSIGHT的扩展能力，从在不同用例中的适应性到在乳腺X线摄影双重阅读环境中替代人类读者的潜力，韩国首尔，2024年2月28日/PRNewswire/--Lunit（KRX:328130.KQ），一家领先的人工智能癌症诊断和治疗解决方案提供商今天宣布，将于2月28日至3月3日在奥地利维也纳举行的2024年欧洲放射学大会（ECR）上介绍七项研究。

Four will be presented through oral presentations and three as E-posters..

其中四份将通过口头演示呈现，三份将作为电子海报呈现。。

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Lunit to present seven studies featuring the Lunit INSIGHT suite at ECR 2024

Lunit将在ECR 2024上展示以Lunit INSIGHT suite为特色的七项研究

In a featured oral presentation led by Dr. Carolyn Horst from King's College London, UK, 16,996 chest radiographs were retrospectively analyzed by Lunit's AI-powered chest X-ray analysis solution, Lunit INSIGHT CXR. With a maximum sensitivity of 0.94 and specificity of 0.99, among various abnormalities, researchers were able to better understand the accuracy of Lunit INSIGHT CXR at different thresholds for different use cases and abnormalities..

在英国伦敦国王学院的Carolyn Horst博士主持的一次专题口头报告中，使用Lunit的人工智能胸部X射线分析解决方案Lunit INSIGHT CXR对16996张胸部X光片进行了回顾性分析。在各种异常中，最大灵敏度为0.94，特异性为0.99，研究人员能够更好地了解Lunit INSIGHT CXR在不同阈值下针对不同用例和异常的准确性。。

Specifically, the AI model with high sensitivity could be appropriate for emergency findings like pneumothorax. Meanwhile, a high specificity is preferable to triage low-risk studies for reporting without missing actionable pathology. This dual approach highlighted the adaptability of Lunit's AI tool to different clinical needs in routine practice.

具体而言，具有高灵敏度的AI模型可能适用于气胸等紧急情况。同时，高特异性优于分流低风险研究以进行报告，而不遗漏可操作的病理学。这种双重方法突出了Lunit的AI工具对常规实践中不同临床需求的适应性。

The research also indicates that AI can offer a valuable balance between sensitivity and specificity in the analysis of common chest abnormalities, showcasing its potential to reduce radiologists' workload and enhance efficiency in reporting..

该研究还表明，人工智能可以在常见胸部异常的分析中提供敏感性和特异性之间的有价值的平衡，展示其减少放射科医生工作量和提高报告效率的潜力。。

In another oral presentation, a research team from Radboud University Medical Center, Netherlands, showcased their result of an independent validation of multiple commercial AI products from leading vendors.Among seven AI-powered algorithms, Lunit INSIGHT CXR achieved the highest AUC (Area Under the Curve) of 0.93 in lung nodule detection, outperforming human readers (mean AUC 0.81).

在另一次口头报告中，荷兰拉德布德大学医学中心的一个研究小组展示了他们对领先供应商的多种商业人工智能产品进行独立验证的结果。在七种AI驱动的算法中，Lunit INSIGHT CXR在肺结节检测中实现了最高的AUC（曲线下面积）0.93，优于人类读者（平均AUC 0.81）。

The sensitivity of Lunit INSIGHT CXR reached 89%, outperforming human readers while maintaining specificity comparable to that of human readers at 80%. Four out of seven AI products, including Lunit INSIGHT CXR, showed superior performance compared to human readers. This validation provides crucial comparative performance data for AI algorithms, contributing to the ongoing discussions about the integration of AI in clinical practice.Lunit INSIGHT MMG, Lunit's AI-powered solution for early breast cancer detection, was highlighted in an award-winning study by Odense University Hospital, Denmark.

Lunit INSIGHT CXR的敏感性达到89%，优于人类读者，同时保持与人类读者相当的特异性为80%。与人类读者相比，包括Lunit INSIGHT CXR在内的七种AI产品中有四种表现出优异的性能。该验证为AI算法提供了至关重要的比较性能数据，有助于正在进行的关于AI在临床实践中整合的讨论。Lunit INSIGHT MMG是Lunit用于早期乳腺癌检测的人工智能解决方案，在丹麦欧登塞大学医院的一项获奖研究中得到了强调。

Based on 249,402 consecutive screening mammograms in three distinct AI-integrated scenarios, the study assessed the software's ability to replace one or more human readers in mammography double-reading settings. Scenario 1: AI replaces the first reader, Scenario 2: AI replaces the second reader in case it agrees with the decision of the first reader, and Scenario 3: AI acts as a standalone reader.All three scenarios showed that AI-integrated screening can partially or fully replace one or both readers without affecting screening accuracy.

该研究基于在三种不同的人工智能集成场景中的249402张连续筛查乳房X线照片，评估了该软件在乳房X线摄影双读设置中替代一个或多个人类读取器的能力。场景1：AI替换第一个阅读器，场景2：如果AI同意第一个阅读器的决定，AI替换第二个阅读器，场景3：AI充当独立阅读器。这三种情况都表明，人工智能综合筛选可以部分或完全取代一个或两个读者，而不会影响筛选的准确性。

Specifically, in Scenario 2, AI-assisted screening indicated significantly higher specificity (+0.6%) and positive predictive value (+4.7%). This groundbreaking research points towards a future where AI seamlessly integrates into double screening processes, enhancing.

具体而言，在情景2中，AI辅助筛查显示出显着更高的特异性（+0.6%）和阳性预测值（+4.7%）。这项开创性的研究指出，人工智能将无缝集成到双重筛选过程中，从而增强。

'The performance of a commercial artificial intelligence algorithm in an external quality assurance scheme regularly used by humans in the NHS breast screening programme' (ACV 2024 Research Stage 2, February 28, 3:00-4:00 pm)

“商业人工智能算法在NHS乳房筛查计划中人类经常使用的外部质量保证计划中的表现”（ACV 2024研究第二阶段，2月28日，下午3:00-4:00）

'The Multi- Sixteen Thousand and Counting: Performance of an Artificial Intelligence Tool for Identifying Common Pathologies on Chest Radiographs and Report Prioritisation' (ACV 2024 Research Stage 1, February 29, 2:00-3:30 pm)

“一万六千人和计数：人工智能工具的性能，用于识别胸片上的常见病理并报告优先级”（ACV 2024研究阶段1，2月29日，下午2:00-3:30）

'Recent development in AI for lung nodule detection' (ACV 2024 Research Stage 2, March 1, 8:00-9:00 am)

“AI用于肺结节检测的最新进展”（ACV 2024研究阶段2，3月1日，上午8:00-9:00）

'Integration of artificial intelligence (AI) in double-read population-based mammography screening: simulated replacement of one reader and beyond' (ACV 2024 Research Stage 1, March 3, 11:30-12:30 pm)

“人工智能（AI）在基于人群的双读乳腺X线摄影筛查中的整合：模拟替换一个阅读器及其后”（ACV 2024研究阶段1，3月3日，下午11:30-12:30）

Poster presentations featuring Lunit INSIGHT at ECR 2024 include:

Lunit INSIGHT在ECR 2024上的海报展示包括：

'Can artificial intelligence decrease the time to histological diagnosis of lung cancer - a retrospective-cohort study' (EPOS Area -2 Level)

“人工智能能否缩短肺癌组织学诊断的时间-一项回顾性队列研究”（EPOS区域-2级）

'Deep Learning for Chest Radiograph Evaluation in Children: Repurposed Use of a Commercially Available AI Tool Developed for Adults (EPOS Area -2 Level)

“儿童胸部X光片评估的深度学习：重新使用为成人开发的商用AI工具（EPOS区域-2级）

'Comparison of three AI breast density tools with a human reader' (EPOS Area -2 Level)

“三种人工智能乳房密度工具与人类阅读器的比较”（EPOS区域-2级）

About LunitFounded in 2013, Lunit is a deep learning-based medical AI company on a mission to conquer cancer. We are committed to harnessing AI to ensure accurate diagnosis and optimal treatment for each cancer patient using AI-powered medical image analytics and AI biomarkers.As a medical AI company grounded on clinical evidence, our findings are presented in major peer-reviewed journals, such as the Journal of Clinical Oncology and the Lancet Digital Health, and global conferences, including ASCO and RSNA.After receiving FDA clearance and the CE Mark, our flagship Lunit INSIGHT suite is clinically used in approximately 3,000+ hospitals and medical institutions across 40+ countries.

关于Lunit成立于2013年，Lunit是一家基于深度学习的医疗AI公司，其使命是征服癌症。我们致力于利用人工智能，使用人工智能支持的医学图像分析和人工智能生物标志物，确保每位癌症患者的准确诊断和最佳治疗。作为一家基于临床证据的医学人工智能公司，我们的研究结果发表在主要的同行评审期刊上，如《临床肿瘤学杂志》和《柳叶刀数字健康》，以及包括ASCO和RSNA在内的全球会议上。在获得FDA许可和CE标志后，我们的旗舰Lunit INSIGHT套件已在40多个国家的大约3000多家医院和医疗机构中临床使用。

Lunit is headquartered in Seoul, South Korea, with offices and representatives worldwide. For more information, please visit lunit.io.SOURCE Lunit.

Lunit总部位于韩国首尔，在全球设有办事处和代表。有关更多信息，请访问lunit.io.SOURCE lunit。