AI/ML Innovations Inc. Introduces its Proprietary "Long ECG Neural Network" - Seite 2

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.

• 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.

Our Targeted Market Segments/Users

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:

• Pharmaceuticals & Clinical Drug Trials
• Device/ECG hardware companies (e.g. Holter monitors or patches)
• Researchers
• Cardiology specialists

Future Development Plans

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:

• 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).

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."