Deep learning and probabilistic neural networks-based identification and classification of Pneumonia-related lung diseases
N. Vinothkumarnvk.cpri@gmail.comDepartment of Computer Science and EngineeringKumaraguru College of TechnologyCoimbatore, Tamil Nadu, IndiaView full profile → , Ch. Madhava Raocmadhavarao@kluniversity.inDepartment of Computer Science and EngineeringKoneru Lakshmaiah Education FoundationVaddeswaram, Andhra Pradesh, IndiaView full profile → , Swati R. Nitnawareswatitidke02@gmail.comDepartment of Electronics EngineeringYeshwantrao Chavan College of EngineeringNagpur, Maharastra, IndiaView full profile → , M. Shakunthalashakunthalamasi@gmail.comDepartment of Electronics and Communication EngineeringKavaraipettaiR.M.D. Engineering CollegeThiruvallur, Tamil Nadu, IndiaView full profile → , K. V. Shahnazshahnaznitc@gmail.comDepartment of Electronics and Communication EngineeringVeltech Rangarajan Dr. Sagunthala R&D Institute of Science and TechnologyChennai, Tamil Nadu, IndiaView full profile → , Nelli Sreevidyasreevidya1509@gmail.comDepartment of Information TechnologySreenidhi Institute of Science and TechnologyHyderabad, Telangana, IndiaView full profile → , *L. BhagyalakshmiCorresponding authorProf.Dr.L.Bhagyalakshmi@gmail.comDepartment of Electronics and Communication EngineeringRajalakshmi Engineering CollegeChennai, Tamil Nadu, IndiaView full profile → , Nitesh Kumarrickyengineer@gmail.comDepartment of Information TechnologyL. N. Mishra College of Business ManagementMuzaffarpur, Bihar, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 07 Aug 2024
- Published Online:
- 19 Feb 2025
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-1865
- Pages:
- 213–222
Abstract
Keywords
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References
[1] S. Bharati, P. Podder, R. Mondal, A. Mahmood, and M. Raihan-Al-Masud, “Comparative performance analysis of different classification algorithm for the purpose of prediction of lung cancer,” Advances in Intelligent Systems and Computing, vol. 941, Springer, pp. 447–457 (2020), doi: 10.1007/978-3-030-16660-1_44.
[2] N. Coudray, P. S. Ocampo, T. Sakellaropoulos, M. A. L. O’Donovan, E. A. Gilmore, J. W. Jones, L. B. Roberts, G. D. Doyle, and D. M. E. De Souza, “Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning,” Nat. Med., vol. 24, pp. 1559–1567 (2018), doi: 10.1038/s41591-018-0177-5.
[3] M. R. H. Mondal, S. Bharati, P. Podder, and P. Podder, “Data analytics for novel coronavirus disease,” Informatics in Medicine Unlocked, vol. 20, Elsevier, p. 100374 (2020), doi: 10.1016/j.imu.2020.100374.
[4] K. Kuan, M. Ravaut, G. Manek, H. Chen, J. Lin, B. Nazir, C. Chen, T. C. Howe, Z. Zeng, and V. Chandrasekhar, “Deep learning for lung cancer detection: tackling the Kaggle data science bowl 2017 challenge,” (2017). [Online]. Available: https://arxiv.org/abs/1705.09435.
[5] W. Sun, B. Zheng, and W. Qian, “Automatic feature learning using multichannel ROI based on deep structured algorithms for computerized lung cancer diagnosis,” Comput. Biol. Med., vol. 89, pp. 530–539 (2017).
[6] Q. Song, L. Zhao, X. Luo, and X. Dou, “Using deep learning for classification of lung nodules on computed tomography images,” J. Healthcare Eng., vol. 2017, Art. ID 8314740 (2017), doi: 10.1155/2017/8314740.
[7] W. Sun, B. Zheng, and W. Qian, “Computer aided lung cancer diagnosis with deep learning algorithms,” in Proc. SPIE Medical Imaging, vol. 9785, pp. 97850Z (2016), doi: 10.1117/12.2216307.
[8] NIH sample Chest X-rays dataset. [Online]. Available: https://www.kaggle.com/nih-chest-xrays/sample. [Accessed: June 28, 2020].
[9] A. Abbas, M. M. Abdelsamea, and M. M. Gaber, “Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network,” Appl. Intell. (2020), doi: 10.1007/s10489-020-01829-7.
[10] N. Kumar, K. Premika, L. Bhagyalakshmi, and S. K. Suman, “Smart Traffic Rescuer using IOT,” J. Pharm. Sci. Res., vol. Special Issue 8, pp. 215–219 (2017).
[11] S. K. Suman, N. Arivazhagan, L. Bhagyalakshmi, K. A. S. L. Gajendra, A. D. Pradeep, P. S. K. S. Ranjith, and T. K. K. Rajesh, “Detection and Prediction of HMS from Drinking Water by Analyzing the Adsorbents from Residuals Using Deep Learning,” Adsorption Sci. Technol., vol. 2022, Art. ID 3265366 (2022), doi: 10.1155/2022/3265366.




