Samrat Kumar Dey (Study Leave)

[1]   Dey, S. K., Rahman, M. M., Siddiqi, U. R., Howlader, A., Tushar, M. A., & Qazi, A. (2022). Global landscape of COVID-19 vaccination progress: insight from an exploratory data analysis. Human vaccines & immunotherapeutics, 18(1), 2025009.

[2]   Dey, S. K., Rahman, M. M., Howlader, A., Siddiqi, U. R., Uddin, K. M. M., Borhan, R., & Rahman, E. U. (2022). Prediction of dengue incidents using hospitalized patients, metrological and socio-economic data in Bangladesh: A machine learning approach. PLoS One, 17(7), e0270933.

[3]   Dey, S. K., Uddin, K. M. M., Babu, H. M. H., Rahman, M. M., Howlader, A., & Uddin, K. A. (2022). Chi2-MI: A hybrid feature selection based machine learning approach in diagnosis of chronic kidney disease. Intelligent Systems with Applications, 16, 200144.

[4]   Sultana, A., Dey, S. K., & Rahman, M. A. (2023). Facial emotion recognition based on deep transfer learning approach. Multimedia Tools and Applications, 1-15.

[5]   Mohi Uddin, K. M., Biswas, N., Rikta, S. T., Dey, S. K., & Qazi, A. (2023). XML‐LightGBMDroid: A self‐driven interactive mobile application utilizing explainable machine learning for breast cancer diagnosis. Engineering Reports, e12666.

[6]   Uddin, K. M. M., Ripa, R., Yeasmin, N., Biswas, N., & Dey, S. K. (2023). Machine learning-based approach to the diagnosis of cardiovascular vascular disease using a combined dataset. Intelligence-Based Medicine, 7, 100100.

[7]   Rikta, S. T., Uddin, K. M. M., Biswas, N., Mostafiz, R., Sharmin, F., & Dey, S. K. (2023). XML-GBM lung: An explainable machine learning-based application for the diagnosis of lung cancer. Journal of Pathology Informatics, 14, 100307.

[8]   Qazi, A., Hasan, N., Owusu-Ansah, C. M., Hardaker, G., Dey, S. K., & Haruna, K. (2023). SentiTAM: Sentiments centered integrated framework for mobile learning adaptability in higher education. Heliyon, 9(1).

[9]   Dey, S. K., Rahman, M. M., Shibly, K. H., Siddiqi, U. R., & Howlader, A. (2023). Epidemic trend analysis of SARS‐CoV‐2 in South Asian Association for Regional Cooperation countries using modified susceptible‐infected‐recovered predictive model. Engineering Reports, 5(1), e12550.

[10]Uddin, K. M. M., Dey, S. K., Babu, H. M. H., Mostafiz, R., Uddin, S., Shoombuatong, W., & Moni, M. A. (2022). Feature fusion based VGGFusionNet model to detect COVID-19 patients utilizing computed tomography scan images. Scientific Reports, 12(1), 21796.

[11]Biswas, N., Uddin, K. M. M., Rikta, S. T., & Dey, S. K. (2022). A comparative analysis of machine learning classifiers for stroke prediction: A predictive analytics approach. Healthcare Analytics, 2, 100116.

[12]Rahman, M. M., Kundu, D., Suha, S. A., Siddiqi, U. R., & Dey, S. K. (2022). Hospital patients’ length of stay prediction: A federated learning approach. Journal of King Saud University-Computer and Information Sciences, 34(10), 7874-7884.

[13]Dey, S. K., Mehrin, K., Akter, L., & Akter, M. (2022). Use of Digital Technologies in Public Health Responses to Tackle Covid-19: the Bangladesh Perspective. arXiv preprint arXiv:2203.05303.

Conference Publications

[1]   Jannat, H. E., Rahman, M. M., Dey, S. K., & Islam, A. M. (2022, December). Mutual Information on Low-rank Matrix for Effective Intrusion Detection. In 2022 4th International Conference on Sustainable Technologies for Industry 4.0 (STI) (pp. 1-5). IEEE.

[2]   Arif, M. A. I., Kabir, S., Khan, M. F. H., Dey, S. K., & Rahman, M. M. (2022, December). Machine Learning and Deep Learning Based Network Slicing Models for 5G Network. In 2022 25th International Conference on Computer and Information Technology (ICCIT) (pp. 96-101). IEEE.

[3]   Qazi, A., Qazi, J., Naseer, K., Zeeshan, M., Khan, B., & Dey, S. K. (2022, November). Sentiment analysis of nationwide lockdown amid COVID 19: evidence from Pakistan. In 2022 IEEE 7th International Conference on Information Technology and Digital Applications (ICITDA) (pp. 1-4). IEEE.

[4]   Zaman, S. B., Tasnim, N., Jahan, N., Rahman, M. M., & Dey, S. K. (2022, October). An Ensemble Machine Learning Approach for Detecting Fraudulent Banking Transactions. In Proceedings of International Conference on Fourth Industrial Revolution and Beyond 2021 (pp. 331-343). Singapore: Springer Nature Singapore.

[5]   Kabir, M. H., Rajib, M. S., Rahman, A. S. M. T., Rahman, M. M., & Dey, S. K. (2022, February). Network Intrusion Detection Using UNSW-NB15 Dataset: Stacking Machine Learning Based Approach. In 2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE) (pp. 1-6). IEEE.

[6]   Rahman, M. M., Aktar, R., & Dey, S. K. (2022, February). Design and Implementation of a Low-Cost Automated Medicine Dispenser. In 2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE) (pp. 1-6). IEEE.