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DIAGNOS to Present Cutting-Edge AI Solutions for Retinal Health at ARVO 2024

DIAGNOS to Present Cutting-Edge AI Solutions for Retinal Health at ARVO 2024

DIAGNOS将在ARVO 2024上展示用于视网膜健康的尖端人工智能解决方案
GlobeNewswire ·  05/06 09:00

BROSSARD, Quebec, May 06, 2024 (GLOBE NEWSWIRE) -- Diagnos Inc. ("DIAGNOS" or "the Company") (TSX Venture: ADK) (OTCQB: DGNOF), a provider of healthcare services in early detection of certain critical health issues, in collaboration with ETS, École de Technologie Supérieure, is proud to announce its participation in the Association for Research in Vision and Ophthalmology (ARVO) 2024 Annual Meeting. DIAGNOS will showcase its latest advancements in artificial intelligence applied to retinal imaging, aiming to revolutionize the way retinal anomalies are detected and diagnosed.

魁北克布罗萨德,2024年5月6日(GLOBE NEWSWIRE)——Diagnos Inc.(“DIAGNOS” 或 “公司”)(TSX Venture: ADK)(OTCQB:DGNOF)是与ETS合作提供某些关键健康问题早期发现的医疗保健服务提供商,荣幸地宣布加入研究协会在 2024 年视觉与眼科学 (ARVO) 年会上。DIAGNOS将展示其在应用于视网膜成像的人工智能方面的最新进展,旨在彻底改变视网膜异常的检测和诊断方式。

During ARVO 2024, DIAGNOS will present three groundbreaking topics:

在 ARVO 2024 期间,DIAGNOS 将呈现三个开创性的话题:

  1. AI-Assisted Automated Screening of Retinal Anomalies in OCT Images: A Deep Learning Approach
  2. All that Glitters is not Gold: Are Current Retina Foundation Models Able to Efficiently Detect Hypertensive Retinopathy?
  3. Domain Generalization for Diabetic Retinopathy Grading through Vision-Language Foundation Models
  1. 人工智能辅助自动筛查 OCT 图像中的视网膜异常:一种深度学习方法
  2. 所有闪闪发光的不是金子:当前的视网膜基金会模型是否能够有效检测高血压视网膜病变?
  3. 通过视觉语言基础模型对糖尿病视网膜病变分级进行域推广

OCT Model:
DIAGNOS Convolutional Neural Network (CNN) models, based on OCT images, have achieved remarkable accuracy in identifying subtle changes in retinal morphology indicative of various diseases, such as macular edema, diabetic retinopathy, and age-related macular degeneration. These models, trained on large-scale datasets, extract relevant features from images automatically, enabling early detection of retinal anomalies. Early intervention facilitated by these models has the potential to prevent or delay vision loss and associated complications.

OCT 型号:
基于OCT图像的DIAGNOS卷积神经网络(CNN)模型在识别视网膜形态的细微变化方面取得了显著的准确性,这些变化预示着各种疾病,例如黄斑水肿、糖尿病视网膜病变和与年龄相关的黄斑变性。这些模型在大规模数据集上训练,可自动从图像中提取相关特征,从而可以及早发现视网膜异常。这些模型促进的早期干预有可能预防或延缓视力丧失和相关的并发症。

Hypertensive Retinopathy:
The early detection of Hypertensive Retinopathy (HR) is crucial to prevent irreversible damage to the retinal microcirculation as well as risk prediction tools in cardiovascular disease prevention. DIAGNOS is utilizing Foundation Models, pre-trained on diverse datasets and tasks, to achieve high accuracy in identifying early cases of HR. These computer-aided systems offer a cost-effective solution for disease screening using fundus images, providing objective assessments and assisting clinicians in timely intervention.

高血压视网膜病变:
及早发现高血压视网膜病变(HR)对于防止视网膜微循环造成不可逆的损伤以及预防心血管疾病的风险预测工具至关重要。DIAGNOS正在利用针对不同数据集和任务进行预训练的基础模型,在识别早期的人力资源案例方面实现高精度。这些计算机辅助系统为使用眼底图像进行疾病筛查提供了具有成本效益的解决方案,可提供客观的评估并协助临床医生及时进行干预。

Vision Language Foundation Model:
DIAGNOS is exploring a foundation model for color fundus images able to encode images and text information through vision language encoders, driven by expert knowledge supervision via prompt descriptions. This interdisciplinary approach at the intersection of computer vision, natural language processing and medical imaging, aimed at improving the diagnosis and management of diabetic retinopathy through advanced machine learning techniques. DIAGNOS is at the forefront of innovation in the AI world applied to medical systems.

视觉语言基础模型:
DIAGNOS正在探索彩色眼底图像的基础模型,该模型能够通过视觉语言编码器对图像和文本信息进行编码,由专家通过即时描述进行知识监督。这种跨学科方法位于计算机视觉、自然语言处理和医学成像的交汇处,旨在通过先进的机器学习技术改善糖尿病视网膜病变的诊断和管理。DIAGNOS处于应用于医疗系统的人工智能领域创新的最前沿。

These innovative AI systems provide objective assessments and assist clinicians in interpreting complex Retinal Fundus and OCT images. By enhancing diagnostic confidence and reducing variability in interpretation among practitioners, DIAGNOS is pioneering a new era in retinal healthcare.

这些创新的人工智能系统提供客观的评估,并协助临床医生解释复杂的视网膜眼底和OCT图像。通过增强诊断信心并减少从业者之间的解释差异,DIAGNOS开创了视网膜医疗保健的新时代。

"We are excited to present our latest advancements in AI-driven retinal imaging at ARVO 2024," said Yves-Stéphane Couture, COO at DIAGNOS Inc. "Our goal is to empower clinicians with cutting-edge tools that enable early detection and intervention, ultimately improving patient outcomes in retinal health."

“我们很高兴在ARVO 2024上展示我们在人工智能驱动的视网膜成像方面的最新进展,” DIAGNOS Inc.首席运营官Yves-Stephane Couture说,“我们的目标是为临床医生提供尖端工具,实现早期发现和干预,最终改善视网膜健康方面的患者预后。”

Here are the titles of our presentations with the link to the ARVO program.

以下是我们演示文稿的标题以及ARVO计划的链接。

  1. AI-Assisted Automated Screening of Retinal Anomalies in OCT Images: A Deep Learning Approach. Hadi Chakor, Waziha Kabir, Riadh Kobbi, Jihed Chelbi, Marc-André Racine, Julio Silva-Rodríguez, Balamurali Murugesan, Jose Dolz and Ismail Ben Ayed.
  2. All that glitters is not gold: are current retina foundation models able to efficiently detect hypertensive retinopathy? Julio Silva-Rodríguez, Hadi Chakor, Riadh Kobbi, Balamurali Murugesan, Waziha Kabir, Jihed Chelbi, Marc-André Racine, Jose Dolz and Ismail Ben Ayed
  3. Domain generalization for diabetic retinopathy grading through vision-language foundation models. Balamurali Murugesan, Julio Silva-Rodríguez, Hadi Chakor, Riadh Kobbi, Waziha Kabir, Jihed Chelbi, Marc-André Racine, Jose Dolz and Ismail Ben Ayed.
  1. 人工智能辅助自动筛查 OCT 图像中的视网膜异常:一种深度学习方法。哈迪·查科尔、瓦齐哈·卡比尔、里亚德·科比、吉赫德·切尔比、马克-安德烈·拉辛、胡利奥·席尔瓦-罗德里格斯、巴拉穆拉利·穆鲁格桑、何塞·多尔兹和伊斯梅尔·本·艾德。
  2. 所有闪闪发光的不是金子:当前的视网膜基础模型是否能够有效地检测高血压视网膜病变?胡里奥·席尔瓦-罗德里格斯、哈迪·查科尔、里亚德·科比、巴拉穆拉利·穆鲁格桑、瓦齐哈·卡比尔、吉赫德·切尔比、马克-安德烈·拉辛、何塞·多尔兹和伊斯梅尔·本·艾德
  3. 通过视觉语言基础模型对糖尿病视网膜病变分级进行域推广。巴拉穆拉利·穆鲁格桑、胡里奥·席尔瓦-罗德里格斯、哈迪·查科尔、里亚德·科比、瓦齐哈·卡比尔、吉赫德·切尔比、马克-安德烈·拉辛、何塞·多尔兹和伊斯梅尔·本·艾德。

Program link:

节目链接:

About DIAGNOS

关于 DIGNOS

DIAGNOS is a publicly traded Canadian corporation dedicated to early detection of critical health problems based on its FLAIRE Artificial Intelligence (AI) platform. FLAIRE allows for quick modifying and developing of applications such as CARA (Computer Assisted Retina Analysis). CARA's image enhancement algorithms provide sharper, clearer and easier-to-analyze retinal images. CARA is a cost-effective tool for real-time screening of large volumes of patients.

DIAGNOS 是一家加拿大上市公司,致力于基于其 FLAIRE 人工智能 (AI) 平台及早发现关键健康问题。FLAIRE 允许快速修改和开发诸如 CARA(计算机辅助视网膜分析)之类的应用程序。CARA 的图像增强算法可提供更清晰、更清晰、更易于分析的视网膜图像。CARA 是一种经济实惠的工具,用于实时筛查大量患者。

Additional information is available at and

其他信息可在以下网址获得 和

Neither the TSX Venture Exchange nor its Regulation Services Provider (as that term is defined in the policies of the TSX Venture Exchange) accepts responsibility for the adequacy or accuracy of this release.

多伦多证券交易所风险投资交易所及其监管服务提供商(该术语在多伦多证券交易所风险投资交易所的政策中定义)均不对本新闻稿的充分性或准确性承担责任。

This news release contains forward-looking information. There can be no assurance that forward-looking information will prove to be accurate, as actual results and future events could differ materially from those anticipated in these statements. DIAGNOS disclaims any intention or obligation to publicly update or revise any forward-looking information, whether as a result of new information, future events or otherwise. The forward-looking information contained in this news release is expressly qualified by this cautionary statement.

本新闻稿包含前瞻性信息。无法保证前瞻性信息会被证明是准确的,因为实际结果和未来事件可能与这些陈述中的预期存在重大差异。无论是由于新信息、未来事件还是其他原因,DIAGNOS均不打算或义务公开更新或修改任何前瞻性信息。本警示声明明确限制了本新闻稿中包含的前瞻性信息。

CONTACT: For further information, please contact:  Mr. André Larente, President DIAGNOS Inc. Tel: 450-678-8882 ext. 224 alarente@diagnos.com
联系人:欲了解更多信息,请联系:DIAGNOS Inc. 总裁安德烈·拉伦特先生电话:450-678-8882 分机 224 alarente@diagnos.com

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
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