Journals

Tanzim et al., “Development of a multi-fusion convolutional neural network (MF-CNN) for enhanced gastrointestinal disease diagnosis in endoscopy image analysis,” PeerJ Computer Science, 2024. [Paper]

Shamrat et al., “An advanced deep neural network for fundus image analysis and enhancing diabetic retinopathy detection,” PeerJ Computer Science , 100303 , 2024. [Paper]

Ananda et al., “An Intelligent Thyroid Diagnosis System Utilising Multiple Ensemble and Explainable Algorithms with Medical Supported Attributes,” IEEE Transactions on Artificial Intelligence, vol. 5, no. 6, pp. 2840-2855, 2023. [Paper]

Ananda et al., “BOO-ST and CBCEC: two novel hybrid machine learning methods aim to reduce the mortality of heart failure patients,” Scientific Reports, 13(1), 22847, 2023. [Paper]

F. M. J. M. Shamrat et al., “High-precision multiclass classification of lung disease through customized MobileNetV2 from chest X-ray images,” Computers in Biology and Medicine, vol. 155, 2023. [Paper]

F. M. J. M. Shamrat et al., “Sentiment analysis on twitter tweets about COVID-19 vaccines using NLP and supervised KNN classification algorithm,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 23, no. 1, pp. 463–470, 2021. [Paper]

P. Ghosh, F. M. J. M. Shamrat et al., “Efficient prediction of cardiovascular disease using machine learning algorithms with relief and LASSO feature selection techniques,” IEEE Access, vol. 9, pp. 19304–19326, 2021. [Paper]

S. Akter, F. M. J. M. Shamrat, S. Chakraborty et al., “COVID-19 Detection Using Deep Learning Algorithm on Chest X-ray Images,” Biology, vol. 10, no. 11, Art. no. 11, Nov. 2021. [Paper]

F. M. J. M. Shamrat, S. Chakraborty, M. M. Billah, M. Kabir, N. S. Shadin, and S. Sanjana, “Bangla numerical sign language recognition using convolutional neural networks,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 23, no. 1, pp. 405–413, 2021. [Paper]

F. M. J. M. Shamrat, P. Ghosh et al., “LungNet22: A Fine-Tuned Model for Multiclass Classification and Prediction of Lung Disease Using X-ray Images,” Journal of Personalized Medicine, vol. 12, no. 5, Art. no. 5, May 2022. [Paper]

S. Afrin, F. M. J. M. Shamrat et al., “Supervised machine learning based liver disease prediction approach with LASSO feature selection,” Bulletin of Electrical Engineering and Informatics, vol. 10, no. 6, pp. 3369–3376, 2021. [Paper]

F. M. J. M. Shamrat et al., “Analysing most efficient deep learning model to detect COVID-19 from computer tomography images,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 26, no. 1, pp. 462–471, 2022. [Paper]

P. Ghosh, F. M. J. M. Shamrat et al., “SkinNet-16: A deep learning approach to identify benign and malignant skin lesions,” Front Oncol, vol. 12, p. 931141, Aug. 2022. [Paper]

S. Molla, F. M. J. M. Shamrat et al., “A predictive analysis framework of heart disease using machine learning approaches,” Bulletin of Electrical Engineering and Informatics, vol. 11, no. 5, pp. 2705–2716, 2022. [Paper]

C. Mondol, Chaity, F. M. J. M. Shamrat, Md. R. Hasan, S. Alam, P. Ghosh, Z. Tasnim, K. Ahmed, M. Bui. Francis, and M. I. Sobhy, "Early Prediction of Chronic Kidney Disease: A Comprehensive Performance Analysis of Deep Learning Models" Algorithms, vol. 15, no. 9, pp. 308. 2022. [Paper]

M. M. Hossin, F. M. J. M. Shamrat, M. R. Bhuiyan, R. A. Hira, T. Khan, S. Molla, “Breast cancer detection: an effective comparison of different machine learning algorithms on the Wisconsin dataset,” Bulletin of Electrical Engineering and Informatics, vol. 12, no. 4, pp. 2446-56, 2023. [Paper]

F. M. J. M. Shamrat, P. Ghosh et al., "AlzheimerNet: An Effective Deep Learning Based Proposition for Alzheimer’s Disease Stages Classification From Functional Brain Changes in Magnetic Resonance Images," in IEEE Access, vol. 11, pp. 16376-16395, 2023. [Paper]

P. Ghosh, A. Karim, S. T. Atik, S. Afrin, and M. Saifuzzaman, “Expert cancer model using supervised algorithms with a LASSO selection approach,” International Journal of Electrical and Computer Engineering (IJECE), vol. 11, no. 3, p. 2631, 2021. [Paper]

S. Montaha, P. Ghosh et al., “BreastNet18: A High Accuracy Fine-Tuned VGG16 Model Evaluated Using Ablation Study for Diagnosing Breast Cancer from Enhanced Mammography Images,” Biology, vol. 10, no. 12, Art. no. 12, Dec. 2021. [Paper]

S. Montaha, A. R. H. Rafid, P. Ghosh et al., “A shallow deep learning approach to classify skin cancer using down-scaling method to minimize time and space complexity,” PLoS One, vol. 17, no. 8, p. e0269826, 2022. [Paper]