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💡[Feature]: ML model for Pulmonary Infection Detection #203
An application that receives the persons respiratory audio as input and the trained model will analyze the audio and output what kind of infection is being affected to the person.
Use Case
In food processing industries, ensuring the health and safety of workers is of utmost importance. Respiratory problems pose a significant risk to workers in food processing industries, where exposure to airborne particles and contaminants is common. Early detection of respiratory issues is crucial for preventing long-term health complications and ensuring the well-being of employees.
Benefits
An AI model that receives the employee’s respiratory audio as input and the trained model will analyze the audio and output what kind of infection is being affected to the employee. The Pulmonary Infection Detection is a deep learning-based system designed to analyze audio recordings of respiratory sounds and classify them into different respiratory diseases. This project will encompass various stages from data collection to model deployment, providing a comprehensive solution for diagnosing respiratory ailments.
TAHIR0110
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1 week ago
Is there an existing issue for this?
Feature Description
An application that receives the persons respiratory audio as input and the trained model will analyze the audio and output what kind of infection is being affected to the person.
Use Case
In food processing industries, ensuring the health and safety of workers is of utmost importance. Respiratory problems pose a significant risk to workers in food processing industries, where exposure to airborne particles and contaminants is common. Early detection of respiratory issues is crucial for preventing long-term health complications and ensuring the well-being of employees.
Benefits
An AI model that receives the employee’s respiratory audio as input and the trained model will analyze the audio and output what kind of infection is being affected to the employee. The Pulmonary Infection Detection is a deep learning-based system designed to analyze audio recordings of respiratory sounds and classify them into different respiratory diseases. This project will encompass various stages from data collection to model deployment, providing a comprehensive solution for diagnosing respiratory ailments.
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