1,707
Views
1
CrossRef citations to date
0
Altmetric
Research Article

Detection of Monkeypox from skin lesion images using deep learning networks and explainable artificial intelligence

, , , , , , & show all
Article: 2225698 | Received 10 Feb 2023, Accepted 10 Jun 2023, Published online: 27 Jun 2023

References

  • Ortiz-Martínez Y, Rodríguez-Morales AJ, Franco-Paredes C, et al. Monkeypox–a description of the clinical progression of skin lesions: a case report from Colorado, USA. Ther Adv Infect Dis. 2022 Jul;9:20499361221117726. DOI: 10.1177/20499361221117726.
  • Benyahia S, Meftah B, Lézoray O. Multi-features extraction based on deep learning for skin lesion classification. Tissue Cell. 2022 Feb 1;74:101701. doi:10.1016/j.tice.2021.101701
  • Chemnad K, Alshakhsi S, Almourad MB, et al. Smartphone usage before and during COVID-19: a comparative study based on objective recording of usage data. Informatics. 2022;9:98. doi:10.3390/informatics9040098
  • Khanna VV, Chadaga K, Sampathila N, et al. Diagnosing COVID-19 using artificial intelligence: a comprehensive review. Network Model Anal Health Informat Bioinformat. 2022 Dec;11(1):1–23. doi:10.1007/s13721-022-00367-1
  • Gessain A, Nakoune E, Yazdanpanah Y. Monkeypox. N Engl J Med. 2022 Nov 10;387(19):1783–1793. doi:10.1056/NEJMra2208860
  • Luo Q, Han J. Preparedness for a Monkeypox outbreak. Infect Med. 2022 Jul 19. doi:10.1016/j.imj.2022.07.001
  • WHO. Monkeypox outbreak 2022. 2022. Available from: https://www.who.int/news-room/fact-sheets/detail/monkeypox.
  • Rizk JG, Lippi G, Henry BM, et al. Prevention and treatment of monkeypox. Drugs. 2022 Jun 28:1–7. doi:10.1007/s40265-022-01742-y
  • Fomenko A, Weibel S, Moezi H, et al. Assessing severe acute respiratory syndrome coronavirus 2 infectivity by reverse-transcription polymerase chain reaction: a systematic review and meta-analysis. Rev Med Virol. 2022 Apr 2:e2342. doi:10.1002/rmv.2342
  • Glowacz A. Thermographic fault diagnosis of shaft of BLDC motor. Sensors. 2022;22(21):8537.
  • Irfan M, Iftikhar MA, Yasin S, et al. Role of hybrid deep neural networks (HDNNs), computed tomography, and chest X-rays for the detection of COVID-19. Int J Environ Res Public Health. 2021;18(6):3056.
  • Almalki YE, Qayyum A, Irfan M, et al. A novel method for COVID-19 diagnosis using artificial intelligence in chest X-ray images. Healthcare. 2021, April;9(5):522. MDPI.
  • Joshi AM, Nayak DR. MFL-Net: An efficient lightweight multi-scale feature learning CNN for COVID-19 diagnosis from CT images. IEEE J Biomed Health Inform. 2022;26(11):5355–5363.
  • Nayak T, Chadaga K, Sampathila N, et al. Deep learning based detection of monkeypox virus using skin lesion images. Med Novel Technol Devices. 2023;18:100243. doi:10.1016/j.medntd.2023.100243
  • An G, Akiba M, Omodaka K, et al. Hierarchical deep learning models using transfer learning for disease detection and classification based on small number of medical images. Sci Rep. 2021;11(1):4250.
  • Hoang L, Lee SH, Lee EJ, et al. Multiclass skin lesion classification using a novel lightweight deep learning framework for smart healthcare. Appl Sci. 2022;12(5):2677.
  • Glowacz A, Glowacz Z. Recognition of images of finger skin with application of histogram, image filtration and K-NN classifier. Biocybernet Biomed Eng. 2016;36(1):95–101.
  • Naseer I, Akram S, Masood T, et al. Performance analysis of state-of-the-art CNN architectures for luna16. Sensors. 2022 Jun 11;22(12):4426. doi:10.3390/s22124426
  • Fan Z, Lin H, Li C, et al. Use of parallel ResNet for high-performance pavement crack detection and measurement. Sustainability. 2022 Feb 5;14(3):1825. doi:10.3390/su14031825
  • Chowdhury D, Das A, Dey A, et al. ABCandroid: a cloud integrated android app for noninvasive early breast cancer detection using transfer learning. Sensors. 2022 Jan 22;22(3):832. doi:10.3390/s22030832
  • Ahsan MM, et al. Image data collection and implementation of deep learning-based model in detecting Monkeypox disease using modified VGG16. arXiv preprint arXiv:2206.01862. 2022. doi:10.48550/arXiv.2206.01862
  • Abdelhamid AA, et al. Classification of Monkeypox images based on transfer learning and the Al-Biruni Earth radius optimization algorithm. Mathematics. 2022;10(19):3614. doi:10.3390/math10193614
  • Sahin VH, Oztel I, Yolcu Oztel G. Human Monkeypox classification from skin lesion images with deep pre-trained network using mobile application. J Med Syst. 2022 Nov;46(11):1–0. doi:10.1007/s10916-022-01863-7
  • Islam T, Hussain MA, Chowdhury FU, et al. Can artificial intelligence detect Monkeypox from digital skin images? bioRxiv. 2022 Jan 1. doi:10.1101/2022.08.08.503193
  • Sitaula C, Shahi TB. Monkeypox virus detection using pre-trained deep learning-based approaches. J Med Syst. 2022 Nov;46(11):1–9. doi:10.1007/s10916-022-01868-2
  • Gajera HK, Nayak DR, Zaveri MA. A comprehensive analysis of dermoscopy images for melanoma detection via deep CNN features. Biomed Signal Process Control. 2023;79:104186.
  • Images dataset (MSID) a new multiclass skin-based image datatset for Monkeypox disease detection – Kaggle [cited December 1, 2022]. Available from: https://www.kaggle.com/datasets/dipuiucse/monkeypoxskinimagedataset.
  • Karthik R, Vaichole TS, Kulkarni SK, et al. Eff2Net: An efficient channel attention-based convolutional neural network for skin disease classification. Biomed Signal Process Control. 2022 Mar 1;73:103406. doi:10.1016/j.bspc.2021.103406
  • Almuhammadi WS, Agu E, King J, et al. OA-pain-sense: machine learning prediction of hip and knee osteoarthritis pain from IMU data. Informatics. 2022;9:97. doi:10.3390/informatics9040097
  • Krishnadas P, Chadaga K, Sampathila N, et al. Classification of malaria using object detection models. Informatics. 2022;9:76. doi:10.3390/informatics9040076
  • Clement D, Agu E, Obayemi J, et al. Breast cancer tumor classification using a Bag of deep multi-resolution convolutional features. InInformatics. 2022 Oct 28;9(4):91. MDPI. doi:10.3390/informatics9040091
  • Ribeiro MT, Singh S, Guestrin C. “Why should I trust you?” Explaining the predictions of any classifier. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2016, August; pp. 1135–1144.