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International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
VIII. REFERENCES [9] Rajpurkar, P., Irvin, J., Zhu, K., Yang, B., Mehta, H.,
[1] Usha Kosarkar, Gopal Sakarkar, Shilpa Gedam (2022), Duan, T., ... & Ng, A. Y. (2017). CheXNet: Radiologist-
“An Analytical Perspective on Various Deep Learning level pneumonia detection on chest X-rays with deep
Techniques for Deepfake Detection”, 1st International learning. arXiv preprint arXiv:1711.05225
Conference on Artificial Intelligence and Big Data [10] Divya Jain (2020). Chronic Disease Prediction using
Analytics (ICAIBDA), 10th & 11th June 2022, 2456- Machine Learning. The Northcap University (Formerly
3463, Volume 7, PP. 25-30, ITM University, Gurgaon). Available at:
https://doi.org/10.46335/IJIES.2022.7.8.5
Shodhganga@INFLIBNET.
[2] Usha Kosarkar, Gopal Sakarkar, Shilpa Gedam (2022), [11]
“Revealing and Classification of Deepfakes Videos Rakibul Islam, Azrin Sultana, & Mohammad Rashedul
Islam (2024). A comprehensive review for chronic
Images using a Customize Convolution Neural
disease prediction using machine learning algorithms.
Network Model”, International Conference on
Journal of Electrical Systems and Information
Machine Learning and Data Engineering (ICMLDE),
Technology, 11, Article number: 27. Available at:
7th & 8th September 2022, 2636-2652, Volume 218,
SpringerOpen.
PP. 2636-2652,
https://doi.org/10.1016/j.procs.2023.01.237 [12] Shaofu Lin, Shiwei Zhou, Han Jiao, Mengzhen Wang,
[3] Usha Kosarkar, Gopal Sakarkar (2023), “Unmasking Haokang Yan, Peng Dou, & Jianhui Chen (2025). CDR-
Deep Fakes: Advancements, Challenges, and Ethical Detector: a chronic disease risk prediction model
combining pre-training with deep reinforcement
Considerations”, 4th International Conference on
learning. Complex & Intelligent Systems, 11, Article
Electrical and Electronics Engineering (ICEEE),19th &
20th August 2023, 978-981-99-8661-3, Volume 1115, number: 104
PP. 249-262, https://doi.org/10.1007/978-981-99- [13] Usha Kosarkar, Gopal Sakarkar, Shilpa Gedam (2022),
8661-3_19 “An Analytical Perspective on Various Deep Learning
st
[4] Usha Kosarkar, Gopal Sakarkar, Shilpa Gedam (2021), Techniques for Deepfake Detection”, 1 International
“Deepfakes, a threat to society”, International Journal Conference on Artificial Intelligence and Big Data
th
th
of Scientific Research in Science and Technology Analytics (ICAIBDA), 10 & 11 June 2022, 2456-
(IJSRST), 13th October 2021, 2395-602X, Volume 9, 3463, Volume 7, PP. 25-30,
Issue 6, PP. 1132-1140, https://doi.org/10.46335/IJIES.2022.7.8.5
https://ijsrst.com/IJSRST219682 [14] Usha Kosarkar, Gopal Sakarkar, Shilpa Gedam (2022),
[5] Islam, R., Sultana, A., & Islam, M. R. (2024). A “Revealing and Classification of Deepfakes Videos
comprehensive review for chronic disease prediction Images using a Customize Convolution Neural
Network Model”, International Conference on Machine
using machine learning algorithms. Journal of Learning and Data Engineering (ICMLDE), 7 & 8
th
th
Electrical Systems and Information Technology, 11, September 2022, 2636-2652, Volume 218, PP. 2636-
27.
2652, https://doi.org/10.1016/j.procs.2023.01.237
[6] Lin, S., Zhou, S., Jiao, H., Wang, M., Yan, H., Dou, P., & [15]
Chen, J. (2025). CDR-Detector: a chronic disease risk Usha Kosarkar, Gopal Sakarkar (2023), “Unmasking
Deep Fakes: Advancements, Challenges, and Ethical
prediction model combining pre-training with deep
th
Considerations”, 4 International Conference on
reinforcement learning. Complex & Intelligent
th
Electrical and Electronics Engineering (ICEEE),19 &
Systems, 11, 104.
th
20 August 2023, 978-981-99-8661-3, Volume 1115,
[7] Cong, X., Song, S., Li, Y., Song, K., MacLeod, C., Cheng, Y., PP. 249-262, https://doi.org/10.1007/978-981-99-
... & Li, L. (2024). Comparison of models to predict 8661-3_19
incident chronic liver disease: a systematic review [16]
and external validation in Chinese adults. BMC Usha Kosarkar, Gopal Sakarkar, Shilpa Gedam (2021),
“Deepfakes, a threat to society”, International Journal
Medicine, 22, 601.
of Scientific Research in Science and Technology
[8] Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., (IJSRST), 13 October 2021, 2395-602X, Volume 9,
th
Blau, H. M., & Thrun, S. (2017). Dermatologist-level Issue 6, PP. 1132-1140,
classification of skin cancer with deep neural https://ijsrst.com/IJSRST219682
networks. Nature, 542(7639), 115-118.
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