Current trends and future orientation in diagnosing lung pathologies: A systematic survey

Lung diseases pose a significant threat to public health worldwide, resulting in a substantial number of fatalities. Diseases such as chronic obstructive pulmonary disease and lung cancer constitute two of the three deadliest diseases worldwide, contributing to over 3 million deaths annually. This s...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Noorizadeh, Mohammad (author)
مؤلفون آخرون: Bensaali, Faycal (author), Meskin, Nader (author), Ait Hssain, Ali (author), Al-Hasan, Tamim M. (author)
التنسيق: article
منشور في: 2025
الموضوعات:
الوصول للمادة أونلاين:http://dx.doi.org/10.1016/j.imed.2024.09.004
https://www.sciencedirect.com/science/article/pii/S2667102624000664
http://hdl.handle.net/10576/66690
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author Noorizadeh, Mohammad
author2 Bensaali, Faycal
Meskin, Nader
Ait Hssain, Ali
Al-Hasan, Tamim M.
author2_role author
author
author
author
author_facet Noorizadeh, Mohammad
Bensaali, Faycal
Meskin, Nader
Ait Hssain, Ali
Al-Hasan, Tamim M.
author_role author
dc.creator.none.fl_str_mv Noorizadeh, Mohammad
Bensaali, Faycal
Meskin, Nader
Ait Hssain, Ali
Al-Hasan, Tamim M.
dc.date.none.fl_str_mv 2025-07-31T10:37:03Z
2025-02
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://dx.doi.org/10.1016/j.imed.2024.09.004
Al-Hasan, T. M., Noorizadeh, M., Bensaali, F., Meskin, N., & Hssain, A. A. (2025). Current trends and future orientation in diagnosing lung pathologies: A systematic survey. Intelligent Medicine, 5(01), 23-36.
https://www.sciencedirect.com/science/article/pii/S2667102624000664
http://hdl.handle.net/10576/66690
23-36
1
5
2667-1026
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv Elsevier
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Biosensors
Bio-signal processing
Electronic nose
Lung disease
Nosocomial infections
Ventilator-associated pneumonia
dc.title.none.fl_str_mv Current trends and future orientation in diagnosing lung pathologies: A systematic survey
dc.type.none.fl_str_mv Article
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description Lung diseases pose a significant threat to public health worldwide, resulting in a substantial number of fatalities. Diseases such as chronic obstructive pulmonary disease and lung cancer constitute two of the three deadliest diseases worldwide, contributing to over 3 million deaths annually. This study offered a comparative analysis of different diagnostic techniques used for lung pathologies from an engineering standpoint. The review concentrated on intelligent detection methods, including electronic nose, computer vision (CV), or image processing, and biosensors such as graphene-field effect transistor (FET). The E-nose-based detection technique uses electronic sensors to recognize volatile organic compounds (VOCs) in the exhaled breath. These VOCs can aid in the diagnosis of lung pathologies such as pneumonia. The CV processing method involves the application of advanced imaging techniques and machine learning algorithms to scrutinize and diagnose lung pathologies and ventilator-associated pneumonia (VAP). Lastly, biosensors employ the exceptional properties of these materials to identify specific biomarkers in biological samples. This information can be used to diagnose lung pathologies and VAP. This study examined the current state-of-the-art methods and offers a comprehensive analysis of their advantages and disadvantages from an engineering perspective. The study underscored the potential of these techniques to enhance the diagnosis of lung pathologies and VAP and presents the advances in the field of smart biomedical applications. Additionally, it emphasized the necessity for further research to optimize their performance and clinical usefulness.
eu_rights_str_mv openAccess
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identifier_str_mv Al-Hasan, T. M., Noorizadeh, M., Bensaali, F., Meskin, N., & Hssain, A. A. (2025). Current trends and future orientation in diagnosing lung pathologies: A systematic survey. Intelligent Medicine, 5(01), 23-36.
23-36
1
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2667-1026
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spelling Current trends and future orientation in diagnosing lung pathologies: A systematic surveyNoorizadeh, MohammadBensaali, FaycalMeskin, NaderAit Hssain, AliAl-Hasan, Tamim M.BiosensorsBio-signal processingElectronic noseLung diseaseNosocomial infectionsVentilator-associated pneumoniaLung diseases pose a significant threat to public health worldwide, resulting in a substantial number of fatalities. Diseases such as chronic obstructive pulmonary disease and lung cancer constitute two of the three deadliest diseases worldwide, contributing to over 3 million deaths annually. This study offered a comparative analysis of different diagnostic techniques used for lung pathologies from an engineering standpoint. The review concentrated on intelligent detection methods, including electronic nose, computer vision (CV), or image processing, and biosensors such as graphene-field effect transistor (FET). The E-nose-based detection technique uses electronic sensors to recognize volatile organic compounds (VOCs) in the exhaled breath. These VOCs can aid in the diagnosis of lung pathologies such as pneumonia. The CV processing method involves the application of advanced imaging techniques and machine learning algorithms to scrutinize and diagnose lung pathologies and ventilator-associated pneumonia (VAP). Lastly, biosensors employ the exceptional properties of these materials to identify specific biomarkers in biological samples. This information can be used to diagnose lung pathologies and VAP. This study examined the current state-of-the-art methods and offers a comprehensive analysis of their advantages and disadvantages from an engineering perspective. The study underscored the potential of these techniques to enhance the diagnosis of lung pathologies and VAP and presents the advances in the field of smart biomedical applications. Additionally, it emphasized the necessity for further research to optimize their performance and clinical usefulness.This work was supported by the International Research Collaboration Co-Fund of Qatar University (Grant No. IRCC-2022-569).Elsevier2025-07-31T10:37:03Z2025-02Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://dx.doi.org/10.1016/j.imed.2024.09.004Al-Hasan, T. M., Noorizadeh, M., Bensaali, F., Meskin, N., & Hssain, A. A. (2025). Current trends and future orientation in diagnosing lung pathologies: A systematic survey. Intelligent Medicine, 5(01), 23-36.https://www.sciencedirect.com/science/article/pii/S2667102624000664http://hdl.handle.net/10576/6669023-36152667-1026enhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:qspace.qu.edu.qa:10576/666902025-07-31T19:06:13Z
spellingShingle Current trends and future orientation in diagnosing lung pathologies: A systematic survey
Noorizadeh, Mohammad
Biosensors
Bio-signal processing
Electronic nose
Lung disease
Nosocomial infections
Ventilator-associated pneumonia
status_str publishedVersion
title Current trends and future orientation in diagnosing lung pathologies: A systematic survey
title_full Current trends and future orientation in diagnosing lung pathologies: A systematic survey
title_fullStr Current trends and future orientation in diagnosing lung pathologies: A systematic survey
title_full_unstemmed Current trends and future orientation in diagnosing lung pathologies: A systematic survey
title_short Current trends and future orientation in diagnosing lung pathologies: A systematic survey
title_sort Current trends and future orientation in diagnosing lung pathologies: A systematic survey
topic Biosensors
Bio-signal processing
Electronic nose
Lung disease
Nosocomial infections
Ventilator-associated pneumonia
url http://dx.doi.org/10.1016/j.imed.2024.09.004
https://www.sciencedirect.com/science/article/pii/S2667102624000664
http://hdl.handle.net/10576/66690