Artificial intelligence and Signal Analysis for COPD Classification: detecting and Understanding Respiratory Disease Severity

465 16 2431 3 8454 document 2431 Thesis files.zip application/zip 9c0eb2e96d8a5e25f36c61a1c0b650b5 MD5 13909877 2025-06-24 12:41:00 https://bordar.bournemouth.ac.uk/465/1/Thesis%20files.zip 8458 document 2431 Data descriptions for Thesis files zip.docx application/vnd.openxmlformats-officedocument.wordprocessingml.document 92d8842b5dedbc288729a525cfb2c91c MD5 23852 2025-06-24 12:43:36 https://bordar.bournemouth.ac.uk/465/1/Data%20descriptions%20for%20Thesis%20files%20zip.docx 465 1 1 application/zip archive Zip file contains code for output of thesis: Artificial Intelligence and Signal Analysis for COPD Classification en public cc_by_nd_4

Thesis files.zip

full_archive 2432 4 8456 document 2432 Data descriptions for Thesis files zip.docx application/vnd.openxmlformats-officedocument.wordprocessingml.document 92d8842b5dedbc288729a525cfb2c91c MD5 23852 2025-06-24 12:42:49 https://bordar.bournemouth.ac.uk/465/2/Data%20descriptions%20for%20Thesis%20files%20zip.docx 465 2 2 application/vnd.openxmlformats-officedocument.wordprocessingml.document text This Text file give File descriptions of the data in the Thesis files Zip folder en public cc_by_nd_4

Data descriptions for Thesis files zip.docx

documentation 2433 1 8466 document 2433 indexcodes.txt text/x-c++ ecac9047fb03bdd4575a39378d9cbfcf MD5 1092 2025-06-24 13:03:05 https://bordar.bournemouth.ac.uk/465/3/indexcodes.txt 465 3 3 text/x-c++ other Generate index codes conversion from text to indexcodes en public

indexcodes.txt

http://eprints.org/relation/isVersionOf https://bordar.bournemouth.ac.uk/id/document/2432 http://eprints.org/relation/isVolatileVersionOf https://bordar.bournemouth.ac.uk/id/document/2432 http://eprints.org/relation/isIndexCodesVersionOf https://bordar.bournemouth.ac.uk/id/document/2432 archive 8982 disk0/00/00/04/65 2025-10-29 13:27:24 2025-10-29 13:27:35 2025-10-29 13:27:24 data_collection show Albiges Tim s5068684@bournemouth.ac.uk Artificial intelligence and Signal Analysis for COPD Classification: detecting and Understanding Respiratory Disease Severity - dataset pub facsci Code Chronic Obstructive Pulmonary Disease (COPD) is a pressing global health issue that demands precise and prompt diagnostic methods. This thesis marks a significant advancement in the field, as it explores the utilisation of artificial intelligence (AI) and advanced signal processing techniques to enhance the diagnostic potential of pulmonary auscultation audio for automatic COPD identification and severity assessment. The Zip Folder contains the code files for the outputs of results in the thesis. 2025-10-29 published Bournemouth University 10.18746/bmth.data.00000465 Code Timothy Albiges bordar@bournemouth.ac.uk Student Albiges Tim s5068684@bournemouth.ac.uk Artificial Intelligence and Signal Analysis for COPD Classification: Detecting and Understanding of Respiratory Disease Severities thesis https://eprints.bournemouth.ac.uk/41314/ pub Bournemouth University Audio samples utilised are from the open-access ICBHI Respiratory Challenge 2017 database, and from the @TR Respiratory Database, Links listed in the text file. Code written 2021-11 2024-11 2021-11-01 2024-11-01