AI-Enhanced Diagnosis: Pediatric Chest X-ray Classification for Bronchiolitis and Pneumonia

Naveen Gehlot; Khushi Soni; Priyansh Kothari; Ankit Vijayvargiya; Rajesh Kumar

doi:10.1109/ICIIP61524.2023.10537715

AI-Enhanced Diagnosis: Pediatric Chest X-ray Classification for Bronchiolitis and Pneumonia

Naveen Gehlot
, Khushi Soni
, Priyansh Kothari
, Ankit Vijayvargiya
, Rajesh Kumar

Malaviya National Institute of Technology
Manipal University Jaipur
Dublin City University

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

1 Citation (Scopus)

Abstract

The pediatric diseases in question are bronchiolitis and pneumonia, which pose a significant threat to children, especially those under ten years of age. Rapid diagnosis often requires a chest X-ray; reading and interpreting these images is challenging, and requires the expertise of a skilled doctor. It is essential to take advantage of advanced image recognition techniques to aid in interpreting these examinations and extracting necessary information. This study employed deep transfer learning models, including VGG16, VGG19, MobileNetV2, and InceptionResNetV2, to diagnose bronchiolitis and pneumonia in pediatric chest X-rays (PCXr) for the first time. Our findings show that the InceptionResNetV2 model has achieved the highest recall rate for bronchiolitis, with an impressive value of 78.82%. Following that, VGG16 achieved a recall rate of 77.64%, MobileNetV2 at 74.11%, and VGG19 at 62.35%. Furthermore, when assessing the models comprehensively based on their performance in terms of the F-score, InceptionResNetV2 outperformed the others with an F-score of 65.68%.

Original language	English
Title of host publication	2023 7th International Conference on Image Information Processing, ICIIP 2023
Editors	Ruchi Verma, Vipul Sharma, Pankaj Dhiman, Vivek Kumar Sehgal, Pradeep Kumar Gupta
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	753-758
Number of pages	6
ISBN (Electronic)	9798350371406
DOIs	https://doi.org/10.1109/ICIIP61524.2023.10537715
Publication status	Published - 2023
Externally published	Yes
Event	7th International Conference on Image Information Processing, ICIIP 2023 - Solan, India Duration: 22 Nov 2023 → 24 Nov 2023

Publication series

Name	Proceedings of the IEEE International Conference Image Information Processing
ISSN (Print)	2640-074X

Conference

Conference	7th International Conference on Image Information Processing, ICIIP 2023
Country/Territory	India
City	Solan
Period	22/11/23 → 24/11/23

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Bronchiolitis
Convolutional Neural Network (CNN)
Pediatric Chest X-ray (PCXr)
Pneumonia

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Computer Vision and Pattern Recognition
Signal Processing
Health Informatics
Radiology, Nuclear Medicine and Imaging

Access to Document

10.1109/ICIIP61524.2023.10537715

Cite this

Gehlot, N., Soni, K., Kothari, P., Vijayvargiya, A., & Kumar, R. (2023). AI-Enhanced Diagnosis: Pediatric Chest X-ray Classification for Bronchiolitis and Pneumonia. In R. Verma, V. Sharma, P. Dhiman, V. K. Sehgal, & P. K. Gupta (Eds.), 2023 7th International Conference on Image Information Processing, ICIIP 2023 (pp. 753-758). (Proceedings of the IEEE International Conference Image Information Processing). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIIP61524.2023.10537715

Gehlot, Naveen ; Soni, Khushi ; Kothari, Priyansh et al. / AI-Enhanced Diagnosis : Pediatric Chest X-ray Classification for Bronchiolitis and Pneumonia. 2023 7th International Conference on Image Information Processing, ICIIP 2023. editor / Ruchi Verma ; Vipul Sharma ; Pankaj Dhiman ; Vivek Kumar Sehgal ; Pradeep Kumar Gupta. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 753-758 (Proceedings of the IEEE International Conference Image Information Processing).

@inproceedings{638bcd735a324ba9a2fadd06b6634155,

title = "AI-Enhanced Diagnosis: Pediatric Chest X-ray Classification for Bronchiolitis and Pneumonia",

abstract = "The pediatric diseases in question are bronchiolitis and pneumonia, which pose a significant threat to children, especially those under ten years of age. Rapid diagnosis often requires a chest X-ray; reading and interpreting these images is challenging, and requires the expertise of a skilled doctor. It is essential to take advantage of advanced image recognition techniques to aid in interpreting these examinations and extracting necessary information. This study employed deep transfer learning models, including VGG16, VGG19, MobileNetV2, and InceptionResNetV2, to diagnose bronchiolitis and pneumonia in pediatric chest X-rays (PCXr) for the first time. Our findings show that the InceptionResNetV2 model has achieved the highest recall rate for bronchiolitis, with an impressive value of 78.82\%. Following that, VGG16 achieved a recall rate of 77.64\%, MobileNetV2 at 74.11\%, and VGG19 at 62.35\%. Furthermore, when assessing the models comprehensively based on their performance in terms of the F-score, InceptionResNetV2 outperformed the others with an F-score of 65.68\%.",

keywords = "Bronchiolitis, Convolutional Neural Network (CNN), Pediatric Chest X-ray (PCXr), Pneumonia",

author = "Naveen Gehlot and Khushi Soni and Priyansh Kothari and Ankit Vijayvargiya and Rajesh Kumar",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 7th International Conference on Image Information Processing, ICIIP 2023 ; Conference date: 22-11-2023 Through 24-11-2023",

year = "2023",

doi = "10.1109/ICIIP61524.2023.10537715",

language = "English",

series = "Proceedings of the IEEE International Conference Image Information Processing",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "753--758",

editor = "Ruchi Verma and Vipul Sharma and Pankaj Dhiman and Sehgal, \{Vivek Kumar\} and Gupta, \{Pradeep Kumar\}",

booktitle = "2023 7th International Conference on Image Information Processing, ICIIP 2023",

address = "United States",

}

Gehlot, N, Soni, K, Kothari, P, Vijayvargiya, A & Kumar, R 2023, AI-Enhanced Diagnosis: Pediatric Chest X-ray Classification for Bronchiolitis and Pneumonia. in R Verma, V Sharma, P Dhiman, VK Sehgal & PK Gupta (eds), 2023 7th International Conference on Image Information Processing, ICIIP 2023. Proceedings of the IEEE International Conference Image Information Processing, Institute of Electrical and Electronics Engineers Inc., pp. 753-758, 7th International Conference on Image Information Processing, ICIIP 2023, Solan, India, 22/11/23. https://doi.org/10.1109/ICIIP61524.2023.10537715

AI-Enhanced Diagnosis: Pediatric Chest X-ray Classification for Bronchiolitis and Pneumonia. / Gehlot, Naveen; Soni, Khushi; Kothari, Priyansh et al.
2023 7th International Conference on Image Information Processing, ICIIP 2023. ed. / Ruchi Verma; Vipul Sharma; Pankaj Dhiman; Vivek Kumar Sehgal; Pradeep Kumar Gupta. Institute of Electrical and Electronics Engineers Inc., 2023. p. 753-758 (Proceedings of the IEEE International Conference Image Information Processing).

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

TY - GEN

T1 - AI-Enhanced Diagnosis

T2 - 7th International Conference on Image Information Processing, ICIIP 2023

AU - Gehlot, Naveen

AU - Soni, Khushi

AU - Kothari, Priyansh

AU - Vijayvargiya, Ankit

AU - Kumar, Rajesh

PY - 2023

Y1 - 2023

N2 - The pediatric diseases in question are bronchiolitis and pneumonia, which pose a significant threat to children, especially those under ten years of age. Rapid diagnosis often requires a chest X-ray; reading and interpreting these images is challenging, and requires the expertise of a skilled doctor. It is essential to take advantage of advanced image recognition techniques to aid in interpreting these examinations and extracting necessary information. This study employed deep transfer learning models, including VGG16, VGG19, MobileNetV2, and InceptionResNetV2, to diagnose bronchiolitis and pneumonia in pediatric chest X-rays (PCXr) for the first time. Our findings show that the InceptionResNetV2 model has achieved the highest recall rate for bronchiolitis, with an impressive value of 78.82%. Following that, VGG16 achieved a recall rate of 77.64%, MobileNetV2 at 74.11%, and VGG19 at 62.35%. Furthermore, when assessing the models comprehensively based on their performance in terms of the F-score, InceptionResNetV2 outperformed the others with an F-score of 65.68%.

AB - The pediatric diseases in question are bronchiolitis and pneumonia, which pose a significant threat to children, especially those under ten years of age. Rapid diagnosis often requires a chest X-ray; reading and interpreting these images is challenging, and requires the expertise of a skilled doctor. It is essential to take advantage of advanced image recognition techniques to aid in interpreting these examinations and extracting necessary information. This study employed deep transfer learning models, including VGG16, VGG19, MobileNetV2, and InceptionResNetV2, to diagnose bronchiolitis and pneumonia in pediatric chest X-rays (PCXr) for the first time. Our findings show that the InceptionResNetV2 model has achieved the highest recall rate for bronchiolitis, with an impressive value of 78.82%. Following that, VGG16 achieved a recall rate of 77.64%, MobileNetV2 at 74.11%, and VGG19 at 62.35%. Furthermore, when assessing the models comprehensively based on their performance in terms of the F-score, InceptionResNetV2 outperformed the others with an F-score of 65.68%.

KW - Bronchiolitis

KW - Convolutional Neural Network (CNN)

KW - Pediatric Chest X-ray (PCXr)

KW - Pneumonia

UR - https://www.scopus.com/pages/publications/85195239256

U2 - 10.1109/ICIIP61524.2023.10537715

DO - 10.1109/ICIIP61524.2023.10537715

M3 - Conference contribution

AN - SCOPUS:85195239256

T3 - Proceedings of the IEEE International Conference Image Information Processing

SP - 753

EP - 758

BT - 2023 7th International Conference on Image Information Processing, ICIIP 2023

A2 - Verma, Ruchi

A2 - Sharma, Vipul

A2 - Dhiman, Pankaj

A2 - Sehgal, Vivek Kumar

A2 - Gupta, Pradeep Kumar

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 22 November 2023 through 24 November 2023

ER -

Gehlot N, Soni K, Kothari P, Vijayvargiya A, Kumar R. AI-Enhanced Diagnosis: Pediatric Chest X-ray Classification for Bronchiolitis and Pneumonia. In Verma R, Sharma V, Dhiman P, Sehgal VK, Gupta PK, editors, 2023 7th International Conference on Image Information Processing, ICIIP 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 753-758. (Proceedings of the IEEE International Conference Image Information Processing). doi: 10.1109/ICIIP61524.2023.10537715

AI-Enhanced Diagnosis: Pediatric Chest X-ray Classification for Bronchiolitis and Pneumonia

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this