1. Priya, M.M.A. and J.S. Joseph, 2023. Dropout AlexNet-extreme learning optimized with fast gradient descent optimization algorithm for brain tumor classification. Concurrency Comput., Vol. 35. 10.1002/cpe.7543.
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2. Priya, M.M.A., S.J. Jawhar and J.M. Geisa, 2021. Optimal deep belief network with opposition based pity beetle algorithm for lung cancer classification: A DBNOPBA approach. Comput. Methods Programs Biomed., Vol. 199. 10.1016/j.cmpb.2020.105902.
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3. Priya, M.M.A. and S.J. Jawhar, 2020. Advanced lung cancer classification approach adopting modified graph clustering and whale optimisation-based feature selection technique accompanied by a hybrid ensemble classifier. IET Image Process, 14: 2204-2215.
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4. Priya, M.M.A. and S.J. Jawhar, 2019. Lung disease identification and segmentation in medical images. Int. J. Eng. Trends Technol., 67: 87-91.
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5. Priya, M.M.A. and S.J. Jawhar, 2019. Detection of lung nodules in CT images using random forest classifier. Int. J. Adv. Eng. Technol., 3: 72-76.
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6. Priya, M.M.A., 2018. An automatic lung segmentation method for the diagnosis of lung cancer in CT imaging. Int. J. Res. Anal. Rev., 5: 291-295.
7. Priya, M.M.A. and S.J. Jawhar, 2018. Techniques for lung nodule extraction in medical images: A review. Int. J. Res. Anal. Rev., 5: 315-321.
8. Priya, M.M.A. and S.J. Jawhar, 2018. A novel lung nodule detection technique for lung cancer in CT images. Int. J. Adv. Innov. Res., 7: 1-4.
9. Priya, M.M.A. and S.J. Jawhar, 2017. An efficient lung cancer identification and segmentation based on contour extraction. Int. J. Image Process. Networking Tech., 1: 1-6.
10. Priya, M.M.A. and S.J. Jawhar, 2016. A novel approach for lung lesion detection in medical images. Int. J. Image Process. Networking Tech., 6: 183-186.