Georgia Tech Research Corporation (20240335134). PULMONARY LUNG DISEASE DIAGNOSTICS SYSTEM COMPRISED OF DEEP LEARNING ALGORITHMS AND NETWORK INTERFACE simplified abstract

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PULMONARY LUNG DISEASE DIAGNOSTICS SYSTEM COMPRISED OF DEEP LEARNING ALGORITHMS AND NETWORK INTERFACE

Organization Name

Georgia Tech Research Corporation

Inventor(s)

Pinzhi Zhang of Chicago IL (US)

Alagappan Swaminathan of Atlanta GA (US)

Ahmed Uddin of Atlanta GA (US)

PULMONARY LUNG DISEASE DIAGNOSTICS SYSTEM COMPRISED OF DEEP LEARNING ALGORITHMS AND NETWORK INTERFACE - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240335134 titled 'PULMONARY LUNG DISEASE DIAGNOSTICS SYSTEM COMPRISED OF DEEP LEARNING ALGORITHMS AND NETWORK INTERFACE

Simplified Explanation:

This patent application describes a system that uses digital stethoscopes to record lung sounds and diagnose lung diseases using deep learning algorithms.

  • Digital stethoscopes are used to capture respiratory sounds from the patient's lungs.
  • The recorded audio files are analyzed using deep learning algorithms to diagnose various lung ailments.
  • A neural network is trained with a large dataset of audio files to accurately diagnose patients with specific lung diseases.
  • The system includes a fullstack web application with embedded deep learning algorithms for diagnosis.

Key Features and Innovation:

  • Utilization of digital stethoscopes for recording lung sounds.
  • Application of deep learning algorithms for diagnosing lung diseases.
  • Training a neural network with a vast collection of audio files for accurate diagnosis.

Potential Applications:

The technology can be used in healthcare settings for diagnosing pulmonary diseases, monitoring lung health, and improving patient care.

Problems Solved:

The system addresses the challenges of accurately diagnosing lung diseases based on respiratory sounds and provides a more efficient and reliable method for healthcare professionals.

Benefits:

  • Early detection of lung diseases.
  • Improved accuracy in diagnosis.
  • Enhanced patient care and treatment planning.

Commercial Applications:

The technology can be commercialized as a diagnostic tool for healthcare providers, medical facilities, and research institutions. It has the potential to revolutionize the field of pulmonary diagnostics.

Questions about Lung Disease Diagnostics:

1. How does the system differentiate between different lung diseases based on respiratory sounds? 2. What are the potential limitations of using digital stethoscopes for diagnosing lung ailments?


Original Abstract Submitted

a pulmonary lung disease diagnostics system uses digital stethoscopes to record sounds emitted from a patient's lungs including respiratory or breathing audio. digital audio files are leveraged to diagnose patients with a variety of lung ailments using deep learning algorithms and a network interface. a neural network is trained using a large collection of audio files to accurately diagnose patients with certain lung diseases. the neural network includes deep learning algorithms embedded into a minimum viable product (mvp) fullstack web application. the algorithms are used to affirm, contradict, or further investigate a patient's lung disease diagnosis.

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