Digital Library of Zielona Góra contains 9 465 digital objects
Object
Title: AI enabled pneumonia detection and diagnosis based on the concatenation approach: A framework for healthcare sustainability
Autor:
Malla, Prince Priya ; Sahu, Sudhakar ; Tadeusiewicz, Ryszard (1947- ) ; Pławiak, Paweł
Data wydania:
Typ zasobu:
Współtwórca:
Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.
Tytuł publikacji grupowej:
Abstract:
Early detection and diagnosis of pneumonia play a significant role in saving human life. However, detection of pneumonia from chest X-ray images with the help of radiologists is a time-consuming task. Thus, the development of an appropriate artificial intelligence (AI) enabled model for the precise detection of pneumonia becomes an important research topic. In this aspect, we develop an automated transfer learning-based pneumonia detection framework using a feature concatenation approach. ; The proposed approach uses the DenseNet pre-trained network and concatenates the features extracted from several dense blocks of DenseNet in order to obtain the dense multiscale information from the chest X-ray images. This feature concatenation process helps in improving the classification accuracy of the proposed framework and simplifies the pneumonia detection process. ; The proposed work achieves accuracy, sensitivity, specificity, and precision of 98.60%, 97.03%, 99.14%, and 97.51%, respectively, on the chest X-ray pneumonia dataset which are superior results to the existing deep learning-based pneumonia frameworks. It is concluded that the proposed AI-enabled pneumonia detection framework has the prospective to be considered as a computer-aided diagnosis support system for the early diagnosis of pneumonia.
Wydawca:
Zielona Góra: Uniwersytet Zielonogórski
Identyfikator zasobu:
DOI:
Strony:
Źródło:
AMCS, volume 35, number 2 (2025) ; click here to follow the link
Jezyk:
Licencja CC BY 4.0:
Prawa do dysponowania publikacją:
Biblioteka Uniwersytetu Zielonogórskiego
Object collections:
- Repository > Faculties > Faculty of Computer, Electrical and Control Engineering
- Repository > Types of work > Articles
- Repository > Scientific journals and UZ publishing series > International Journal of Applied Mathematics and Computer Science (AMCS) > International Journal of Applied Mathematics and Computer Science (AMCS) (2025)
Last modified:
7 sie 2025
In our library since:
7 sie 2025
Number of object content hits:
67
All available object's versions:
https://www.zbc.uz.zgora.pl/repozytorium/publication/101994
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 35, number 1 (2025)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 35, number 2 (2025)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 35, number 3 (2025)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 35, number 4 (2025)
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