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

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


==Organization Name==

[[:Category:Georgia Tech Research Corporation|Georgia Tech Research Corporation]]


[[Category:Georgia Tech Research Corporation]]

==Inventor(s)==

[[:Category:Pinzhi Zhang of Chicago IL (US)|Pinzhi Zhang of Chicago IL (US)]][[Category:Pinzhi Zhang of Chicago IL (US)]]

[[:Category:Alagappan Swaminathan of Atlanta GA (US)|Alagappan Swaminathan of Atlanta GA (US)]][[Category:Alagappan Swaminathan of Atlanta GA (US)]]

[[:Category:Ahmed Uddin of Atlanta GA (US)|Ahmed Uddin of Atlanta GA (US)]][[Category: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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