AI/ML Innovations Inc. Introduces Its Proprietary "Long ECG Neural Network"
AI/ML Innovations Inc. Introduces Its Proprietary "Long ECG Neural Network"
Highlights:
亮點:
- 100 million+ ECGs are performed annually in the USA.
- AIML's proprietary "Long ECG Neural Net" reduces labeling of long ECGs from several days to under 5 minutes.
- Provides unsurpassed accuracy, depth and insight into the cardiac data.
- 美國每年進行超過1億次心電圖檢查。
- AIML公司的專有“開多心電神經網絡”將長時間ECG的標記從幾天縮短到不到5分鐘。
- 提供無與倫比的準確性、深度和對心臟數據的洞察。
VICTORIA, BC / ACCESSWIRE / May 6, 2024 / AI/ML Innovations Inc. ("AIML" or the "Company") (CSE:AIML)(OTCQB:AIMLF)(FWB:42FB), a leading company committed to acquiring and advancing Artificial Intelligence/Machine Learning technologies that address urgent societal needs, is proud to introduce its proprietary Long ECG Neural Net (L-ECG NN). The L-ECG NN provides cardiologists, researchers, pharmaceuticals and others, with a fast, accurate and comprehensive tool for the in-depth analysis and feature extraction of ECGs.
2024年5月6日,加拿大維多利亞/ACCESSWIRE,AI/ML創新公司(以下簡稱“AIML”或“公司”)(CSE:AIML)(OTCQB:AIMLF)(FWB:42FB)是一家致力於收購和推進解決緊急社會需求的人工智能/機器學習技術的領先公司,自豪地推出其專有的長週期心電神經網絡(L-ECG NN)。L-ECG NN爲心臟病專家、研究人員、藥企和其他人提供了一個快速、準確和全面的工具,用於ECG的深度分析和特徵提取。
The Need for Improved Utilization of ECG Data
改進ECG數據利用的需求
- "The ECG is the most commonly performed cardiovascular diagnostic procedure, with >100 million ECGs obtained annually in the United States."1 (AHA Journals)
- Typical 24/48 hour-long ECGs, that are used in clinical trial, drug discovery, and specialist cases, take many days of effort for in-depth labeling, when relying on conventional, semi-automatic methods.
- "Even for an experienced cardiologist, accurately interpreting the ECG for a patient with concurrent arrhythmias is challenging" ... "there is an urgent unmet need for an automated or assisted multilabel ECG diagnostic framework, supported by artificial intelligence technology."2 (The Lancet)
- “心電圖是最常用的心血管診斷程序,美國每年獲取超過1億次心電圖檢查。”(AHA期刊)1(AHA雜誌)
- 在臨床試驗、藥物研發和專科病例中使用的典型24/48小時長時間ECG,在依賴傳統的半自動方法進行深入標記時需要多天努力。
- “即使對於有經驗的心臟專家來說,準確地解讀同時出現心律失常患者的ECG是具有挑戰性的”……“亟需一種自動化或輔助的多標籤ECG診斷框架,支持人工智能技術。”(柳葉刀)2(柳葉刀)
The L-ECG NN Feature Set Advantage
L-ECG NN特點優勢
AIML's Long ECG Neural Net displays many advantages over conventional methods of analyzing ECG data:
AIML的長週期心電神經網絡相比傳統的ECG數據分析方法展現出了許多優勢:
- Accurate: The L-ECG NN was trained and tested on human ECG data, providing accurate labeling with minimal (2ms) error.
- In-depth: Our proprietary AI analysis algorithm enables in-depth analysis and feature extraction of ECGs, allowing clinicians and researchers to quickly identify specific changes to the heartbeats of a long recording.
- Versatile: Our advanced AI analysis algorithm provides deep analysis of ECGs from multiple sources (e.g., holters, sleep studies, clinical drug trials).
- Comprehensive: While rudimentary traditional methods of ECG analysis only spot the R-peak, we label every waveform and its duration, providing comprehensive cardiac data insights.
- Fast: We are able to label all ECG features within minutes for ECGs of any size, rather than in days, as is the present case.
- Future potential: The L-ECG NN has the potential of using the features extracted to detect and predict cardiovascular diseases, and discovering new digital biomarkers for cardiac and chronic patients.
- 準確:L-ECG NN在人體ECG數據上進行訓練和測試,提供最小誤差(2毫秒)的準確標記。
- 深度:我們的專有AI分析算法能夠對ECG進行深入分析和特徵提取,使臨床醫生和研究人員能夠快速識別長時間記錄下的心跳特徵的具體變化。
- 多功能:我們先進的AI分析算法提供了來自多個來源的ECG深度分析(例如,霍爾特器、睡眠研究、臨床藥物試驗)。
- 全面:雖然基本的傳統ECG分析方法只能檢測到R峯,但我們標記每個波形及其持續時間,提供全面的心臟數據洞見。
- 快速:我們能夠在幾分鐘內對任何大小的ECG進行標記,而不是像現在的情況一樣需要多天。
- 未來潛力:L-ECG NN有潛力使用提取的特徵檢測和預測心血管疾病,併爲心臟和慢性病患者發現新的數字生物標誌物。
Product Configurations
產品配置
The L-ECG NN is available for hardware integration (use in 1- Lead ECG wearable monitors, 1 or 3-lead Holter monitors, and more), or for use online.
L-ECG NN可用於硬件集成(在單導聯ECG可穿戴監測器、1或3導聯Holter監測器等中的使用)或在線使用。
- Available as a REST API, allowing developers to integrate L-ECG NN into third-party applications.
- A web application for easy use, without technical knowledge.
- 作爲RESt API,可讓開發人員將L-ECG NN集成到第三方應用程序中。
- 一個易於使用的Web應用程序,無需技術知識。
Our Targeted Market Segments/Users
我們的目標市場細分/用戶
While the potential user base for our technology is both broad and deep, we have identified several potential market segments that represent our "path of least resistance" to market penetration. Some of these include:
雖然我們的技術潛在用戶基礎廣泛而深入,但我們已經確定了幾個潛在的市場細分,它們代表着我們進入市場的“最小阻力路徑”。其中一些包括:
- Pharmaceuticals & Clinical Drug Trials
- Device/ECG hardware companies (e.g. Holter monitors or patches)
- Researchers
- Cardiology specialists
- 藥品和臨床藥物試驗
- 設備/ECG硬件公司(例如Holter監視器或補丁)
- 研究者
- 心臟病專家
Future Development Plans
未來發展計劃
AIML has several plans for the expansion of both the potential use and the users of the L-ECG NN technology going forward. Some of these include:
AIML有幾個計劃,旨在進一步擴大L-ECG NN技術的潛在用途和用戶。其中一些包括:
- Regulatory approval: FDA submission for approval as a medical device.
- Online access: An incorporated User Interface (UI) for users to directly interact with the NN Store. Users will be able to directly upload their ECG data and have a full display of resulting graphs and labels to analyze and download.
- Diagnosis: Training of the L-ECG NN to analyze ECGs for heart abnormalities to accelerate and automate diagnoses
- Prediction: Accelerate and, eventually, automate the analysis of existing ECG databases to enable early detection and prediction of cardiovascular diseases (CVDs).
- 監管批准:提交FDA作爲醫療器械批准申請。
- 在線訪問:用於用戶直接與NN Store互動的用戶界面(UI)。用戶將能夠直接上傳他們的ECG數據,並全面顯示結果圖表和標籤以進行分析和下載。
- 診斷:對L-ECG NN進行訓練,以加速和自動化ECG心臟異常的分析。
- 預測:加速並最終自動化現有ECG數據庫的分析,以提前檢測和預測心血管疾病(CVD)。
Paul Duffy, CEO of AI/ML Innovations Inc. added, "With this announcement AI/ML embarks on our next era of innovation. This groundbreaking Long ECG Neural Net technology has the potential to revolutionize ECG analysis, saving time and costs while enhancing patient care." Duffy continues "What I am truly excited about is the L-ECG signal processing algorithms and their versatility to extend to any signal data presenting distinctive traits that warrant identification and analysis. Our advanced Neural Net models now learn the hidden structure of a signal and classify important features to detect other conditions. We will begin to apply this proprietary Neural Net technology to all biometric signals opening entirely new untapped markets for AI/ML."
AI/ML Innovations Inc.首席執行官Paul Duffy補充說:“通過此次宣佈,AI/ML開啓了我們下一個創新時代。這項開創性的Long ECG Neural Net技術具有革命性的潛力,可以節省時間和成本,同時提高患者護理水平。”Duffy繼續說:“我真正感到興奮的是L-ECG信號處理算法以及它們的多功能性,可以擴展到任何具有值得識別和分析的獨特特徵的信號數據。我們的先進神經網絡模型現在可以學習信號的隱藏結構並分類重要特徵以檢測其他條件。我們將開始將這項專有的神經網絡技術應用於所有生物測量信號,開闢全新的未開發市場,爲AI/ML帶來更廣闊的前景。”
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About AI/ML Innovations Inc.
執行董事Tim Daniels
AI/ML Innovations Inc. has realigned its business operations to capitalize on the burgeoning fields of artificial intelligence (AI) and machine learning (ML), with an initial investment focus on emerging digital health and wellbeing companies that leverage AI, ML, cloud computing and digital platforms to drive transformative healthcare management solutions and precision support delivery across the health continuum. Through strategic partnerships with Health Gauge (95.2% owned by AIML), Tech2Heal (up to 22% ownership rights, with 12.44% currently owned by AIML), AI Rx Inc. (70% owned by AIML) and other planned accretive investments, the Company continues to capitalize on expanding growth areas, to the benefit of all the Company's stakeholders. AI/ML's shares are traded on the Canadian Securities Exchange under the symbol "AIML", the OTCQB Venture Market under "AIMLF", and the Frankfurt Stock Exchange under "42FB".
更多關於AI/ML創新公司的信息
On behalf of the Board of Directors
Tim Daniels, Executive Chairman
謹代表董事會
AI/ML Innovations Inc.已重新調整其業務運營以利用人工智能(AI)和機器學習(ML)的蓬勃發展,初始投資重點放在利用AI、ML、雲計算和數字平台推動變革性健康管理解決方案和精準支持交付的新興數字健康和健康公司上。通過與健康儀表盤(AIML持有95.2%的所有權)、Tech2Heal(最高持股22%,目前AIML擁有12.44%的所有權)、AI Rx Inc.(AIML持有70%的所有權)和其他計劃中的增值投資進行戰略合作,該公司繼續利用不斷擴大的增長領域,造福於公司的所有利益相關者。AI/ML的股票在加拿大證券交易所上市,代碼爲“AIML”,在OTCQB Venture Market上市,代碼爲“AIMLF”,在Frankfurt Stock Exchange上市,代碼爲“42FB”。
For more information about AI/ML Innovations:
For detailed information please see AI/ML's website or the Company's filed documents at
For further information, contact: Blake Fallis at (778) 405-0882 or info@aiml-innovations.com
執行董事Tim Daniels:
有關詳細信息,請參閱AI/ML網站或公司歸檔文件。
更多信息請聯繫:Blake Fallis (778) 405-0882或info@aiml-innovations.com。
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For AI/ML Innovations Investors
針對AI/ML Innovations投資者
Certain statements made in this press release that are not based on historical information are forward-looking statements that involve substantial known and unknown risks and uncertainties. This press release contains express or implied forward-looking statements relating to, among other things, AI/ML Innovations' expectations concerning management's plans, objectives, and strategies, including strategies for defending the Company's intellectual property. These statements are neither promises nor guarantees but are subject to a variety of risks and uncertainties, many of which are beyond our control, which could cause actual results to differ materially from those contemplated in these forward-looking statements. Existing and prospective investors are cautioned not to place undue reliance on these forward-looking statements, which speak only as of the date hereof. AI/ML Innovations Inc. undertakes no obligation to update or revise the information contained in this press release, whether as a result of new information, future events, or circumstances or otherwise except as expressly required by applicable securities law. Further information regarding the uncertainties and risks can be found in the disclosure documents filed by AI/ML with the securities regulatory authorities, available at .
此新聞稿中的某些陳述不是基於歷史信息,而是涉及到許多已知和未知風險和不確定性的前瞻性陳述。本新聞稿包含明示或暗示的關於AI/ML Innovations期望的前瞻性陳述,涉及到管理層的計劃、目標和策略,包括保護公司知識產權的策略。這些陳述既不是承諾也不是保證,但是受到各種風險和不確定性的影響,其中許多超出了我們的控制範圍,這可能導致實際結果與這些前瞻性陳述所預期的結果彼此不同。現有和潛在投資者被告知不要過度依賴這些前瞻性陳述,這些前瞻性陳述僅代表其所在日期的意見。AI/ML Innovations Inc.無需更新或修訂此新聞稿中所包含的信息,除非適用的證券法明確要求或有新信息或未來事件或情況。有關不確定性和風險的更多信息可以在AI / ML向證券監管機構提交的披露文件中找到,網址爲 。
SOURCE: AI/ML Innovations Inc.
來源:AI/ML Innovations Inc.