Khanday, A. M. U. D., Wani, M. A., Rabani, S. T., Khan, Q. R., & Abd El-Latif, A. A. (2024). HAPI: An efficient Hybrid Feature Engineering-based Approach for Propaganda Identification in social media. PloS one, 19(7), e0302583.
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0302583
Hajam, M. A., Arif, T., Khanday, A. M. U. D., & Neshat, M. (2023). An Effective Ensemble Convolutional Learning Model with Fine-tuning for Medicinal Plant Leaf Identification. Information, 14(11), 618.https://www.mdpi.com/2078-2489/14/11/618
Tripathi, K., Khan, F.A., Khanday, A.M.U.D. et al. The classification of medical and botanical data through majority voting using artificial neural network. Int. j. inf. tecnol. 15, 3271–3283 (2023). https://doi.org/10.1007/s41870-023-01361-0 . https://link.springer.com/article/10.1007/s41870-023-01361-0
Rabani, S. T., Khanday, A. M. U. D., Khan, Q. R., Hajam, U. A., Imran, A. S., & Kastrati, Z. (2023). Detecting suicidality on social media: Machine learning at rescue. Egyptian Informatics Journal, 24(2), 291-302. . https://www.sciencedirect.com/science/article/pii/S1110866523000233
Khanday AMUD, Wani MA, Rabani ST, Khan QR. Hybrid Approach for Detecting Propagandistic Community and Core Node on Social Networks. Sustainability. 2023; 15(2):1249. https://doi.org/10.3390/su15021249 https://www.mdpi.com/2071-1050/15/2/1249
Khanday, A. M. U. D., Rabani, S. T., Khan, Q. R., & Malik, S. H. (2022). Detecting twitter hate speech in COVID-19 era using machine learning and ensemble learning techniques. International Journal of Information Management Data Insights, 2(2), 100120 . https://www.sciencedirect.com/science/article/pii/S2667096822000635
Khanday, A. M. U. D., Khan, Q. R., & Rabani, S. T. (2022). Ensemble Approach for Detecting COVID-19 Propaganda on Online Social Networks. Iraqi Journal of Science, 4488-4498. https://www.ijs.uobaghdad.edu.iq/index.php/eijs/article/view/3454
Khanday, A. M. U. D., Bhushan, B., Jhaveri, R. H., Khan, Q. R., Raut, R., & Rabani, S. T. (2022). Nnpcov19: Artificial neural network-based propaganda identification on social media in covid-19 era. Mobile Information Systems, 2022, 1-10. https://www.hindawi.com/journals/misy/2022/3412992/
Rabani, S. T., Khan, Q. R., & Khanday, A. M. U. D. (2021). Quantifying suicidal ideation on social media using machine learning: A critical review. Iraqi Journal of Science, 4092-4100 . https://ijs.uobaghdad.edu.iq/index.php/eijs/article/view/2877
Khanday, A. M. U. D., Khan, Q. R., & Rabani, S. T. (2021). Detecting textual propaganda using machine learning techniques. Baghdad Science Journal, 18(1), 0199-0199. . https://www.bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/5251
Khanday, A. M. U. D., Khan, Q. R., & Rabani, S. T. (2021). Identifying propaganda from online social networks during COVID-19 using machine learning techniques. International Journal of Information Technology, 13, 115-122. https://link.springer.com/article/10.1007/s41870-020-00550-5
Rabani, S. T., Khan, Q. R., & Ud din Khanday, A. M. (2021). A NOVEL APPROACH TO PREDICT THE LEVEL OF SUICIDAL IDEATION ON SOCIAL NETWORKS USING MACHINE AND ENSEMBLE LEARNING. ICTACT Journal on Soft Computing, 11(2). https://ictactjournals.in/paper/IJSC_Vol_11_Iss_2_Paper_7_2288_2293.pdf
Rabani, S. T., Khan, Q. R., & Khanday, A. M. U. D. (2020). Detection of suicidal ideation on Twitter using machine learning & ensemble approaches. Baghdad science journal, 17(4), 1328-1328. https://www.bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/5245
Khanday, A. M. U. D., Rabani, S. T., Khan, Q. R., Rouf, N., & Mohi Ud Din, M. (2020). Machine learning based approaches for detecting COVID-19 using clinical text data. International Journal of Information Technology, 12, 731-739. https://link.springer.com/article/10.1007/s41870-020-00495-9
Verma, P., Khanday, A. M. U. D., Rabani, S. T., Mir, M. H., & Jamwal, S. (2019). Twitter sentiment analysis on Indian government project using R. Int J Recent Technol Eng, 8(3), 8338-41. https://d1wqtxts1xzle7.cloudfront.net/61585865/paper_sentiment20191222-58074-1tchba0-libre.pdf?1577081821=&response-content-disposition=inline%3B+filename%3DPaper_sentiment.pdf&Expires=1694698484&Signature=bI83bn1-J2YzjAXXtrFJIN9eBbawWlsbrTu8wvgS2neATyjMCeybSun-rFuT3vyilgNqd-gpqTf84JpBOpdxnu2XnlDIHK7NMJL52t4-1tLrd~lIQv1YZU~kX3jDzTmbjIkjUzmISu9WlB07VihXk9~Ilwbs7ONf7VQEA5MOKRuW2~KC38EZm-PSzlnQder0zXibv2RPSjSJuz2Vt4NIJrRk-XGeIdXwk~pIkCQuHuTmBqukW-~r7kDi4yWz8n-od2xPjzfZ0C~BXmmPqwHZzoYMvSA4kCKYyFyU8cn2n1UdIuM02WgFxKBK~gQKUY55Q96ugsvHbCrHdGweKpJ7~w__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA
Khanday, A. M. U. D., Amin, A., Manzoor, I., & Bashir, R. (2018). Face recognition techniques: a critical review. STM Journals [Internet], 5(2), 24-30. https://www.researchgate.net/profile/Akib-Khanday/publication/330872439_Face_Recognition_Techniques_A_Critical_Review/links/5c5917be458515a4c7591595/Face-Recognition-Techniques-A-Critical-Review.pdf
Bouktif, S., Khanday, A. M. U. D., & Ouni, A. (2024, May). CoML: Machine Learning based approach for COVID-19 related Suicidal Ideation detection. In 2024 International Conference on Intelligent Systems and Computer Vision (ISCV) (pp. 1-5). IEEE.
Khanday, A., Bouktif, S., & Ouni, A. (2023, October). RNN-based model for an optimal COVID-19 cases detection using clinical reports. In 2023 9th International Conference on Optimization and Applications (ICOA) (pp. 1-6). IEEE.
Khanday, A. M. U. D., Khan, Q. R., Rabani, S. T., Wani, M. A., & ELAffendi, M. (2022, May). Propaganda Identification on Twitter Platform During COVID-19 Pandemic Using LSTM. In International Conference on Cybersecurity, Cybercrimes, and Smart Emerging Technologies (pp. 303-314). Cham: Springer International Publishing. https://link.springer.com/chapter/10.1007/978-3-031-21101-0_24
Khanday, A. M. U. D., Khan, Q. R., & Rabani, S. T. (2020, December). Analysing and predicting propaganda on social media using machine learning techniques. In 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN) (pp. 122-127). IEEE. https://ieeexplore.ieee.org/abstract/document/9362838
Rabani, S. T., Khan, Q. R., & Khanday, A. M. U. D. (2020, December). Multi-Class Suicide Risk Prediction on Twitter Using Machine Learning Techniques. In 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN) (pp. 128-134). IEEE. https://ieeexplore.ieee.org/abstract/document/9362979
Adil, A., Asger, M., Gul, M., Khanday, A. M. U. D., & Magray, R. A. (2024). Stem cell therapy in the era of machine learning. In Computational Biology for Stem Cell Research (pp. 77-84). Academic Press.
https://www.sciencedirect.com/science/article/abs/pii/B9780443132223000046
Wajid, M. A., Zafar, A., Bhushan, B., Khanday, A. M. U. D., & Wajid, M. S. (2023). Artificial Intelligence (AI) and Internet of Things (IoT): Application in Detecting and Containing the Spread of COVID-19. In AI Models for Blockchain-Based Intelligent Networks in IoT Systems: Concepts, Methodologies, Tools, and Applications (pp. 373-392). Cham: Springer International Publishing. https://link.springer.com/chapter/10.1007/978-3-031-31952-5_16
Khanday, A. M. U. D., Rabani, S. T., Khan, Q. R., & Khan, F. A. (2023). Community Detection Algorithms: A Critical Review. Advanced Applications of NLP and Deep Learning in Social Media Data, 75-91. https://www.igi-global.com/chapter/community-detection-algorithms/324563
Mir, T. A., Lawaye, A. A., & Khanday, A. M. U. D. (2023). NLP Techniques and Challenges to Process Social Media Data. In Advanced Applications of NLP and Deep Learning in Social Media Data (pp. 171-218). IGI Global. https://www.igi-global.com/chapter/nlp-techniques-and-challenges-to-process-social-media-data/324568
Khanday, A. M. U. D., Khan, Q. R., Rabani, S. T., Wani, M. A., & ELAffendi, M. (2022, May). Propaganda Identification on Twitter Platform During COVID-19 Pandemic Using LSTM. In International Conference on Cybersecurity, Cybercrimes, and Smart Emerging Technologies (pp. 303-314). Cham: Springer International Publishing. https://link.springer.com/chapter/10.1007/978-3-031-21101-0_24
Rouf, N., Kaisar Khan, A., Malik, M. B., Ud Din Khanday, A. M., & Gul, N. (2021). Unfolding the potential of impactful emerging technologies amid COVID‐19. Enabling Healthcare 4.0 for Pandemics: A Roadmap Using AI, Machine Learning, IoT and Cognitive Technologies, 117-141.https://onlinelibrary.wiley.com/doi/abs/10.1002/9781119769088.ch7
Khanday, A. M. U. D., Khan, Q. R., & Rabani, S. T. (2021). SVMBPI: support vector machine-based propaganda identification. In Cognitive Informatics and Soft Computing: Proceeding of CISC 2020 (pp. 445-455). Springer Singapore. https://link.springer.com/chapter/10.1007/978-981-16-1056-1_35