Published:

• M. N. Hasan, S. B. Shuvo, M. M. H. Ankon, S. M. T. U. Raju, and N. Siddique, “TransfusionNet: Framework for cervical cancer detection using deep learning with multi-level fusion", Results in Engineering, vol. 28, p. 107174, 2025, doi: 10.1016/j.rineng.2025.107174.

In Preparation:

• S. B. Shuvo, S. A. Redhila, S. Hossain,  and A. D. Roy, “NeuroSwin: A Swin Transformer-GRU Model for Parkinson's Disease Classification and Brain Region Localization from EEG Signals,” Manuscript in preparation for Expert Systems with Application.

• S. B. Shuvo, M. M. H. Ankon, M. A. Sayed, M. N. Hasan, and M. Z. Chowdhury, “CholeNet: A Recurrent-Convolutional Hybrid Ensemble Framework with Quad-Fold Parallel Transfer Learning and Spatio-Sequential Feature Fusion for Gallbladder Cancer Classification,” Manuscript in preparation for Biomedical Signal Processing and Control (Elsevier).

• M. M. H. Ankon, S. B. Shuvo, M. N. Hasan, and M. M. H. Manik, “VRX-UNet: Automated Volumetric Characterization of Intra-tumoral Structures in Gliomas using 3D Segmentation,” Manuscript in preparation for Computers in Biology and Medicine (Elsevier).

• M. N. Hasan, I. Ahmad, S. B. Shuvo, M. M. H. Ankon, S. Das, and N. Siddique, “A Critical Analysis of LLM Performance in Stomach Infection Classification through Multi-Level Prompt Benchmarking against a Proposed Hybrid CNN Framework: MobileCoAtNet,” Manuscript in preparation for IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI).

• M. A. Sayed, M. A. Rahman, S. B. Shuvo, M. J. Hossain, M. S. Alam, K. N. Hasan, and M. A. Kadir, “Advanced image analysis for liver tumor detection and visualization in CT images using automated segmentation,” Manuscript in preparation for Nature - Scientific Reports.

• M. N. Hasan,  M. M. H. Ankon, S. B. Shuvo, I. Ahmad, M. M. H. Manik, and N. Siddique, “Zero-to-Multi-Shot Benchmarking of Model-Agnostic Meta-Learning (MAML)-Based Domain Adaptation for Multi-Cancer Classification: Comparative Evaluation of LLMs, State-of-the-Art Deep Learning Models, and a Proposed Hybrid Approach,” Ongoing Research.

• M. N. Hasan, W. M. Shafin, T. Joty, Md. M. H. Ankon, S. B. Shuvo, and N. Siddique, “Unveiling Overfitting Patterns: Explainable AI-Driven Benchmarking of LLMs, Deep Learning Models, and a Hybrid Framework for Medical Image Classification,” Ongoing Research

Published:

• S. B. Shuvo and M. Z. Chowdhury, "Classification of Gallbladder Cancer Using Average Ensemble Learning," 2024 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT), Dhaka, Bangladesh, 2024, pp. 1450-1455, doi: 10.1109/ICEEICT62016.2024.10534480. [PDF]

Under Review:

• S. B. Shuvo, S. Hossain, S. A. Redhila and U. Bose, “Exploring Common Molecular Interactions across Multiple Cancer to Identify Potential Therapeutic Targets and Drug Candidates,” Submitted in 2025 7th International Conference on Electrical Information and Communication Technology (EICT), Khulna, Bangladesh, 2025.

• Md. A. Sayed, A. Rahman, S. B. Shuvo, M. A. Kadir, Md. I. A. Imran, Md. S. I. Wadud, and Md. N. Hossain, “Automated PET to Fused PET-CT Mapping Using PCGAN for Lung Cancer Diagnosis,” Submitted in 2025 7th International Conference on Electrical Information and Communication Technology (EICT), Khulna, Bangladesh, 2025.

Oral presentation at ICEEICT (2024) on “Classification of Gallbladder Cancer Using Average Ensemble Learning.” (Presentation Slide)

Event: 1st National Conference of Research, Industry and Collaboration in Biomedical Engineering

Organizer: Department of Biomedical Engineering, Jashore University of Science & Technology

Date: June 22, 2025

Format: Poster presentation

Title: Exploring Gene Network Interactions and Pathways in Three Cancers: Identifying Potential Therapeutic Targets and Drug Candidates

Poster Link: Google Drive

Certification Link: