Araştırma Makalesi

Classification of Monkeypox Skin Lesion using the Explainable Artificial Intelligence Assisted Convolutional Neural Networks

Sayı: 40 30 Eylül 2022
Avrupa Bilim ve Teknoloji Dergisi Kapak
Avrupa Bilim ve Teknoloji Dergisi
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Classification of Monkeypox Skin Lesion using the Explainable Artificial Intelligence Assisted Convolutional Neural Networks

Öz

The World Health Organization (WHO) has given people various protective warnings for Monkeypox. If monkeypox spreads rapidly, it becomes a serious public health problem. In this case, it creates a serious congestion in hospitals. Therefore, auxiliary systems can be needed in hospitals. In this study, explainable artificial intelligence (xAI) assisted convolutional neural networks (CNNs) based a decision support system was proposed. The data set was used for this task consists of 572 images in two classes, such as Monkeypox and Normal. 12 different CNN models were used for Monkeypox and Normal skin classification. MobileNet V2 model achieved best performance with the accuracy of 98.25%, sensitivity of 96.55%, specificity of 100.00% and F1-Score of 98.25%. This model was supported by explainable AI methods. As a result, an artificial intelligence (AI) assisted auxiliary diagnosis system has been proposed for Monkeypox skin lesion.

Anahtar Kelimeler

Teşekkür

This paper has been prepared by AKGUN Computer Incorporated Company. We would like to thank AKGUN Computer Inc. for providing all kinds of opportunities and funds for the execution of this project.

Kaynakça

  1. World Health Organization. (2022). Monkeypox outbreak 2022 - Global. https://www.who.int/emergencies/situations/monkeypox-oubreak-2022
  2. Kumar, N., Acharya, A., Gendelman, H. E., & Byrareddy, S. N. (2022). The 2022 outbreak and the pathobiology of the monkeypox virus. Journal of Autoimmunity, 102855. https://doi.org/10.1016/j.jaut.2022.102855
  3. Al-Shamsi, M. (2017). Addressing the physicians’ shortage in developing countries by accelerating and reforming the medical education: Is it possible? Journal of Advances in Medical Education & Professionalism, 5(4), 210–219. /pmc/articles/PMC5611431/
  4. Islam, T., Hussain, M. A., Uddin, F., Chowdhury, H., & Islam, B. M. R. (2022). A Web-scraped Skin Image Database of Monkeypox, Chickenpox, Smallpox, Cowpox, and Measles. BioRxiv, 2022.08.01.502199. https://doi.org/10.1101/2022.08.01.502199
  5. Islam, T., Hussain, M. A., Uddin, F., Chowdhury, H., & Islam, B. M. R. (2022). Can Artificial Intelligence Detect Monkeypox from Digital Skin Images? BioRxiv, 2022.08.08.503193. https://doi.org/10.1101/2022.08.08.503193
  6. Ahsan, M. M., Uddin, M. R., & Luna, S. A. (2022). Monkeypox Image Data collection. https://arxiv.org/abs/2206.01774v1
  7. Ahsan, M. M., Uddin, M. R., Farjana, M., Sakib, A. N., Momin, K. Al, & Luna, S. A. (2022). Image Data collection and implementation of deep learning-based model in detecting Monkeypox disease using modified VGG16. https://arxiv.org/abs/2206.01862v1
  8. Ali, S. N., Ahmed, M. T., Paul, J., Jahan, T., Sani, S. M. S., Noor, N., & Hasan, T. (2022). Monkeypox Skin Lesion Detection Using Deep Learning Models: A Feasibility Study. https://arxiv.org/abs/2207.03342v1

Ayrıntılar

Birincil Dil

İngilizce

Konular

Mühendislik

Bölüm

Araştırma Makalesi

Yazarlar

Yayımlanma Tarihi

30 Eylül 2022

Gönderilme Tarihi

6 Eylül 2022

Kabul Tarihi

23 Eylül 2022

Yayımlandığı Sayı

Yıl 2022 Sayı: 40

DOI

https://doi.org/10.31590/ejosat.1171816

IZ

https://izlik.org/JA75EK89SD

Kaynak Göster

RIS / Bibtex
APA
Akın, K. D., Gurkan, C., Budak, A., & Karataş, H. (2022). Classification of Monkeypox Skin Lesion using the Explainable Artificial Intelligence Assisted Convolutional Neural Networks. Avrupa Bilim ve Teknoloji Dergisi, 40, 106-110. https://doi.org/10.31590/ejosat.1171816
AMA
1.Akın KD, Gurkan C, Budak A, Karataş H. Classification of Monkeypox Skin Lesion using the Explainable Artificial Intelligence Assisted Convolutional Neural Networks. EJOSAT. 2022;(40):106-110. doi:10.31590/ejosat.1171816
Chicago
Akın, Korhan Deniz, Caglar Gurkan, Abdulkadir Budak, ve Hakan Karataş. 2022. “Classification of Monkeypox Skin Lesion using the Explainable Artificial Intelligence Assisted Convolutional Neural Networks”. Avrupa Bilim ve Teknoloji Dergisi, sy 40: 106-10. https://doi.org/10.31590/ejosat.1171816.
EndNote
Akın KD, Gurkan C, Budak A, Karataş H (01 Eylül 2022) Classification of Monkeypox Skin Lesion using the Explainable Artificial Intelligence Assisted Convolutional Neural Networks. Avrupa Bilim ve Teknoloji Dergisi 40 106–110.
IEEE
[1]K. D. Akın, C. Gurkan, A. Budak, ve H. Karataş, “Classification of Monkeypox Skin Lesion using the Explainable Artificial Intelligence Assisted Convolutional Neural Networks”, EJOSAT, sy 40, ss. 106–110, Eyl. 2022, doi: 10.31590/ejosat.1171816.
ISNAD
Akın, Korhan Deniz - Gurkan, Caglar - Budak, Abdulkadir - Karataş, Hakan. “Classification of Monkeypox Skin Lesion using the Explainable Artificial Intelligence Assisted Convolutional Neural Networks”. Avrupa Bilim ve Teknoloji Dergisi. 40 (01 Eylül 2022): 106-110. https://doi.org/10.31590/ejosat.1171816.
JAMA
1.Akın KD, Gurkan C, Budak A, Karataş H. Classification of Monkeypox Skin Lesion using the Explainable Artificial Intelligence Assisted Convolutional Neural Networks. EJOSAT. 2022;:106–110.
MLA
Akın, Korhan Deniz, vd. “Classification of Monkeypox Skin Lesion using the Explainable Artificial Intelligence Assisted Convolutional Neural Networks”. Avrupa Bilim ve Teknoloji Dergisi, sy 40, Eylül 2022, ss. 106-10, doi:10.31590/ejosat.1171816.
Vancouver
1.Korhan Deniz Akın, Caglar Gurkan, Abdulkadir Budak, Hakan Karataş. Classification of Monkeypox Skin Lesion using the Explainable Artificial Intelligence Assisted Convolutional Neural Networks. EJOSAT. 01 Eylül 2022;(40):106-10. doi:10.31590/ejosat.1171816

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