Comparison of Transfer Learning vs. Hyperparameter Tuning to Improve Neural Networks Precision in the Early Detection of Pneumonia in Chest X-Rays

Paúl Idrovo-Berrezueta; Denys Dutan-Sanchez; Vladimir Robles-Bykbaev

doi:10.1007/978-3-031-33258-6_24

Comparison of Transfer Learning vs. Hyperparameter Tuning to Improve Neural Networks Precision in the Early Detection of Pneumonia in Chest X-Rays

Paúl Idrovo-Berrezueta, Denys Dutan-Sanchez, Vladimir Robles-Bykbaev

Artificial Intelligence and Assistive Technologies Research Group (GI-IATa)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

The WHO (World Health Organization) has updated a publication where they discuss the topic of Covid-19 vaccination for children, and in this document, they mention the vulnerability that this illness has caused among children under the age of 5, exposing them to a higher risk of other diseases such as pneumonia. For this reason, this research is focused on the early detection of pneumonia using children’s chest X-rays and the implementation of artificial intelligence. CNN (Convolutional Neural Network) is the best tool to use as an image processor for the chest X-rays, hence a variety of deep learning techniques were used such as VGG16, VGG16-W VGG19, VGG19-W HT, ResNet50, ResNet50-W, MobileNet, and MobileNet-W. To enhance the accuracy of these deep learning techniques, transfer learning, and hyperparameters were applied to the training process. As a result of this research, we’ve obtained an accuracy of 0.9684 and a loss of 0.0793, and hope that with this research we can help the medical areas in the early detection of pneumonia and save doctors time.

Original language	English
Title of host publication	Information Technology and Systems - ICITS 2023
Editors	Álvaro Rocha, Carlos Ferrás, Waldo Ibarra
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	263-272
Number of pages	10
ISBN (Print)	9783031332579
DOIs	https://doi.org/10.1007/978-3-031-33258-6_24
State	Published - 2023
Event	International Conference on Information Technology and Systems, ICITS 2023 - Cusco, Peru Duration: 24 Apr 2023 → 26 Apr 2023

Publication series

Name	Lecture Notes in Networks and Systems
Volume	691 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	International Conference on Information Technology and Systems, ICITS 2023
Country/Territory	Peru
City	Cusco
Period	24/04/23 → 26/04/23

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Artificial intelligence
Convolutional neural network
Hyperparameter tuning
Image classification
Pneumonia
Transfer learning
X-ray

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-031-33258-6_24

Cite this

Idrovo-Berrezueta, P., Dutan-Sanchez, D., & Robles-Bykbaev, V. (2023). Comparison of Transfer Learning vs. Hyperparameter Tuning to Improve Neural Networks Precision in the Early Detection of Pneumonia in Chest X-Rays. In Á. Rocha, C. Ferrás, & W. Ibarra (Eds.), Information Technology and Systems - ICITS 2023 (pp. 263-272). (Lecture Notes in Networks and Systems; Vol. 691 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-33258-6_24

Idrovo-Berrezueta, Paúl ; Dutan-Sanchez, Denys ; Robles-Bykbaev, Vladimir. / Comparison of Transfer Learning vs. Hyperparameter Tuning to Improve Neural Networks Precision in the Early Detection of Pneumonia in Chest X-Rays. Information Technology and Systems - ICITS 2023. editor / Álvaro Rocha ; Carlos Ferrás ; Waldo Ibarra. Springer Science and Business Media Deutschland GmbH, 2023. pp. 263-272 (Lecture Notes in Networks and Systems).

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title = "Comparison of Transfer Learning vs. Hyperparameter Tuning to Improve Neural Networks Precision in the Early Detection of Pneumonia in Chest X-Rays",

abstract = "The WHO (World Health Organization) has updated a publication where they discuss the topic of Covid-19 vaccination for children, and in this document, they mention the vulnerability that this illness has caused among children under the age of 5, exposing them to a higher risk of other diseases such as pneumonia. For this reason, this research is focused on the early detection of pneumonia using children{\textquoteright}s chest X-rays and the implementation of artificial intelligence. CNN (Convolutional Neural Network) is the best tool to use as an image processor for the chest X-rays, hence a variety of deep learning techniques were used such as VGG16, VGG16-W VGG19, VGG19-W HT, ResNet50, ResNet50-W, MobileNet, and MobileNet-W. To enhance the accuracy of these deep learning techniques, transfer learning, and hyperparameters were applied to the training process. As a result of this research, we{\textquoteright}ve obtained an accuracy of 0.9684 and a loss of 0.0793, and hope that with this research we can help the medical areas in the early detection of pneumonia and save doctors time.",

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Idrovo-Berrezueta, P, Dutan-Sanchez, D & Robles-Bykbaev, V 2023, Comparison of Transfer Learning vs. Hyperparameter Tuning to Improve Neural Networks Precision in the Early Detection of Pneumonia in Chest X-Rays. in Á Rocha, C Ferrás & W Ibarra (eds), Information Technology and Systems - ICITS 2023. Lecture Notes in Networks and Systems, vol. 691 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 263-272, International Conference on Information Technology and Systems, ICITS 2023, Cusco, Peru, 24/04/23. https://doi.org/10.1007/978-3-031-33258-6_24

Comparison of Transfer Learning vs. Hyperparameter Tuning to Improve Neural Networks Precision in the Early Detection of Pneumonia in Chest X-Rays. / Idrovo-Berrezueta, Paúl; Dutan-Sanchez, Denys; Robles-Bykbaev, Vladimir.
Information Technology and Systems - ICITS 2023. ed. / Álvaro Rocha; Carlos Ferrás; Waldo Ibarra. Springer Science and Business Media Deutschland GmbH, 2023. p. 263-272 (Lecture Notes in Networks and Systems; Vol. 691 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Idrovo-Berrezueta P, Dutan-Sanchez D, Robles-Bykbaev V. Comparison of Transfer Learning vs. Hyperparameter Tuning to Improve Neural Networks Precision in the Early Detection of Pneumonia in Chest X-Rays. In Rocha Á, Ferrás C, Ibarra W, editors, Information Technology and Systems - ICITS 2023. Springer Science and Business Media Deutschland GmbH. 2023. p. 263-272. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-33258-6_24