AI Cardio

Heart attacks, particularly those without persistent ST-segment elevation, pose a significant challenge in diagnosis and treatment. The timely detection of total coronary thrombosis is crucial in ensuring appropriate patient management and improving outcomes. However, traditional diagnostic methods may miss subtle signs or require expert interpretation, leading to delays and potential misdiagnosis.

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Cardio IA is an innovative AI model designed to address these challenges. By incorporating deep neural networks and clinical parameters, our model analyzes electrocardiograms (ECGs) to improve the detection of total coronary thrombosis in patients with acute coronary syndrome. The AI algorithms learn from vast amounts of data, continuously improving accuracy and performance.

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The collaboration between the Mexican Health Foundation (FUNSALUD), the National Institute of Cardiology Ignacio Chávez, the Department of Computer Science at ITAM, and EYEX Vision aims to validate the algorithm in a clinical setting. We are committed to publishing scientific findings, raising awareness about the project's potential, and utilizing cloud functionality to integrate the algorithm into the existing IAM-Mx application or an alternative platform. By doing so, we aim to achieve immediate detection, reduce dependence on specialists, and significantly impact cardiovascular prevention and treatment in Mexico.

 

Healthcare Benefits: 

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• Early and accurate detection: Cardio IA's advanced AI model improves sensitivity in detecting total coronary thrombosis, enabling early intervention and appropriate patient management.

• Reduced dependence on specialists: By integrating the AI model into existing healthcare systems, Cardio IA reduces the need for specialized expertise, allowing broader access to timely and accurate diagnoses.

• Improved Patient Outcomes: Timely detection and appropriate intervention facilitated by Cardio IA can significantly impact patient outcomes, reducing morbidity and mortality associated with undetected heart attacks.

• Enhanced efficiency: Cardio IA streamlines the diagnostic process, providing healthcare providers with a reliable tool for detecting total coronary thrombosis, leading to optimized workflows and improved resource allocation.

 

Health & Social Impact: 

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Cardio IA presents a cutting-edge solution in the field of cardiovascular diagnostics, incorporating AI and deep neural networks. The potential impact of Cardio IA goes beyond individual patient care, extending to the overall improvement of cardiovascular health in Mexico.

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1. Improved Diagnosis Accuracy: By enhancing the sensitivity of total coronary thrombosis detection, Cardio IA can improve the accuracy of diagnoses. This impact can be measured by comparing the rate of correct diagnoses before and after implementing the AI model.

2. Reduction in Undetected Heart Attacks: Cardio IA aims to detect undetected heart attacks, reducing the number of missed cases. This impact can be quantified by tracking the total coronary thrombosis detection rate increase.

3. Optimized Resource Allocation: By reducing the need for specialized expertise, Cardio IA can optimize resource allocation in healthcare systems, improving efficiency and reducing costs associated with delayed or misdiagnosed cases.

4. Improved Patient Outcomes: The publication of scientific findings and presentations at medical conferences will raise awareness about Cardio IA's potential, promoting its adoption and integration into clinical practice.

5. Increased Awareness and Adoption: Eyex Vision's scalable solution can help address the scarcity of specialized doctors and increase access to diagnostic imaging services, particularly in underserved areas. The impact on accessibility can be measured by tracking the number of patients served in previously underserved regions or populations.

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