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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將在ARVO 2024上展示用於視網膜健康的尖端人工智能解決方案
GlobeNewswire ·  05/06 21:00

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.

魁北克布羅薩德,2024年5月6日(GLOBE NEWSWIRE)——Diagnos Inc.(“DIAGNOS” 或 “公司”)(TSX Venture: ADK)(OTCQB:DGNOF)是與ETS合作提供某些關鍵健康問題早期發現的醫療保健服務提供商,榮幸地宣佈加入研究協會在 2024 年視覺與眼科學 (ARVO) 年會上。DIAGNOS將展示其在應用於視網膜成像的人工智能方面的最新進展,旨在徹底改變視網膜異常的檢測和診斷方式。

During ARVO 2024, DIAGNOS will present three groundbreaking topics:

在 ARVO 2024 期間,DIAGNOS 將呈現三個開創性的話題:

  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. 人工智能輔助自動篩查 OCT 圖像中的視網膜異常:一種深度學習方法
  2. 所有閃閃發光的不是金子:當前的視網膜基金會模型是否能夠有效檢測高血壓視網膜病變?
  3. 通過視覺語言基礎模型對糖尿病視網膜病變分級進行域推廣

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 型號:
基於OCT圖像的DIAGNOS卷積神經網絡(CNN)模型在識別視網膜形態的細微變化方面取得了顯著的準確性,這些變化預示着各種疾病,例如黃斑水腫、糖尿病視網膜病變和與年齡相關的黃斑變性。這些模型在大規模數據集上訓練,可自動從圖像中提取相關特徵,從而可以及早發現視網膜異常。這些模型促進的早期干預有可能預防或延緩視力喪失和相關的併發症。

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.

高血壓視網膜病變:
及早發現高血壓視網膜病變(HR)對於防止視網膜微循環造成不可逆的損傷以及預防心血管疾病的風險預測工具至關重要。DIAGNOS正在利用針對不同數據集和任務進行預訓練的基礎模型,在識別早期的人力資源案例方面實現高精度。這些計算機輔助系統爲使用眼底圖像進行疾病篩查提供了具有成本效益的解決方案,可提供客觀的評估並協助臨床醫生及時進行干預。

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.

視覺語言基礎模型:
DIAGNOS正在探索彩色眼底圖像的基礎模型,該模型能夠通過視覺語言編碼器對圖像和文本信息進行編碼,由專家通過即時描述進行知識監督。這種跨學科方法位於計算機視覺、自然語言處理和醫學成像的交匯處,旨在通過先進的機器學習技術改善糖尿病視網膜病變的診斷和管理。DIAGNOS處於應用於醫療系統的人工智能領域創新的最前沿。

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.

這些創新的人工智能系統提供客觀的評估,並協助臨床醫生解釋複雜的視網膜眼底和OCT圖像。通過增強診斷信心並減少從業者之間的解釋差異,DIAGNOS開創了視網膜醫療保健的新時代。

"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."

“我們很高興在ARVO 2024上展示我們在人工智能驅動的視網膜成像方面的最新進展,” DIAGNOS Inc.首席運營官Yves-Stephane Couture說,“我們的目標是爲臨床醫生提供尖端工具,實現早期發現和干預,最終改善視網膜健康方面的患者預後。”

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

以下是我們演示文稿的標題以及ARVO計劃的鏈接。

  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. 人工智能輔助自動篩查 OCT 圖像中的視網膜異常:一種深度學習方法。哈迪·查科爾、瓦齊哈·卡比爾、里亞德·科比、吉赫德·切爾比、馬克-安德烈·拉辛、胡利奧·席爾瓦-羅德里格斯、巴拉穆拉利·穆魯格桑、何塞·多爾茲和伊斯梅爾·本·艾德。
  2. 所有閃閃發光的不是金子:當前的視網膜基礎模型是否能夠有效地檢測高血壓視網膜病變?胡里奧·席爾瓦-羅德里格斯、哈迪·查科爾、里亞德·科比、巴拉穆拉利·穆魯格桑、瓦齊哈·卡比爾、吉赫德·切爾比、馬克-安德烈·拉辛、何塞·多爾茲和伊斯梅爾·本·艾德
  3. 通過視覺語言基礎模型對糖尿病視網膜病變分級進行域推廣。巴拉穆拉利·穆魯格桑、胡里奧·席爾瓦-羅德里格斯、哈迪·查科爾、里亞德·科比、瓦齊哈·卡比爾、吉赫德·切爾比、馬克-安德烈·拉辛、何塞·多爾茲和伊斯梅爾·本·艾德。

Program link:

節目鏈接:

About DIAGNOS

關於 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,致力於基於其 FLAIRE 人工智能 (AI) 平台及早發現關鍵健康問題。FLAIRE 允許快速修改和開發諸如 CARA(計算機輔助視網膜分析)之類的應用程序。CARA 的圖像增強算法可提供更清晰、更清晰、更易於分析的視網膜圖像。CARA 是一種經濟實惠的工具,用於實時篩查大量患者。

Additional information is available at and

其他信息可在以下網址獲得 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.

多倫多證券交易所風險投資交易所及其監管服務提供商(該術語在多倫多證券交易所風險投資交易所的政策中定義)均不對本新聞稿的充分性或準確性承擔責任。

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.

本新聞稿包含前瞻性信息。無法保證前瞻性信息會被證明是準確的,因爲實際結果和未來事件可能與這些陳述中的預期存在重大差異。無論是由於新信息、未來事件還是其他原因,DIAGNOS均不打算或義務公開更新或修改任何前瞻性信息。本警示聲明明確限制了本新聞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
聯繫人:欲了解更多信息,請聯繫:DIAGNOS Inc. 總裁安德烈·拉倫特先生電話:450-678-8882 分機 224 alarente@diagnos.com

譯文內容由第三人軟體翻譯。


以上內容僅用作資訊或教育之目的,不構成與富途相關的任何投資建議。富途竭力但無法保證上述全部內容的真實性、準確性和原創性。
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