View source for NEWSOUTH INNOVATIONS PTY LIMITED (20240341715). METHOD AND SYSTEMS FOR RESPIRATORY SOUND CLASSIFICATION simplified abstract

=METHOD AND SYSTEMS FOR RESPIRATORY SOUND CLASSIFICATION=


==Organization Name==

[[:Category:NEWSOUTH INNOVATIONS PTY LIMITED|NEWSOUTH INNOVATIONS PTY LIMITED]]


[[Category:NEWSOUTH INNOVATIONS PTY LIMITED]]

==Inventor(s)==

[[:Category:Hao Xue of Melbourne, Victoria (AU)|Hao Xue of Melbourne, Victoria (AU)]][[Category:Hao Xue of Melbourne, Victoria (AU)]]

[[:Category:Flora D. Salim of Melbourne, Victoria (AU)|Flora D. Salim of Melbourne, Victoria (AU)]][[Category:Flora D. Salim of Melbourne, Victoria (AU)]]

==METHOD AND SYSTEMS FOR RESPIRATORY SOUND CLASSIFICATION - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240341715 titled 'METHOD AND SYSTEMS FOR RESPIRATORY SOUND CLASSIFICATION

==Simplified Explanation==
The patent application relates to methods, systems, and computer-readable media for training a feature encoder to encode sound samples, such as respiratory sounds. It also involves training an audio classifier, like a respiratory sound classifier, using the pre-trained feature encoder. Additionally, it covers classifying audio files, such as respiratory sounds, as positive or negative examples of a condition, like a respiratory condition.

* Training a feature encoder for encoding sound samples
* Training an audio classifier using the pre-trained feature encoder
* Classifying audio files as positive or negative examples of a condition

==Key Features and Innovation==
* Training a feature encoder for encoding sound samples
* Training an audio classifier using the pre-trained feature encoder
* Classifying audio files as positive or negative examples of a condition

==Potential Applications==
The technology can be applied in various fields such as healthcare, telemedicine, medical diagnostics, and research.

==Problems Solved==
The technology addresses the need for efficient encoding and classification of sound samples, particularly in the context of respiratory sounds and conditions.

==Benefits==
* Improved accuracy in classifying respiratory sounds
* Enhanced efficiency in encoding and classifying sound samples
* Potential for early detection and diagnosis of respiratory conditions

==Commercial Applications==
* Healthcare industry for respiratory sound analysis
* Telemedicine platforms for remote diagnosis
* Research institutions for studying respiratory conditions

==Prior Art==
Readers can explore prior research on feature encoding, audio classification, and respiratory sound analysis in the medical and technology fields.

==Frequently Updated Research==
Researchers are constantly developing new methods and technologies for improving the accuracy and efficiency of sound sample encoding and classification, particularly in the context of respiratory conditions.

==Questions about the Technology==
===What are the potential commercial applications of this technology?===
The potential commercial applications include healthcare, telemedicine, and research industries.

===How does this technology improve the classification of respiratory sounds?===
This technology improves classification accuracy by training a feature encoder and an audio classifier for efficient encoding and classification of sound samples.


==Original Abstract Submitted==

described embodiments relate to methods, systems, and computer-readable media for training a feature encoder for encoding sound samples, such as respiratory sounds. some embodiments further relate to methods, systems, and computer-readable media for training an audio classifier, such as a respiratory sound classifier, using the pre-trained feature encoder. some embodiments relate to methods, systems, and computer-readable media for classifying a sample of an audio file, such as a respiratory sound, as being a positive example or a negative example of a condition, such as a respiratory condition.



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