7 papers
Histo-MExNet: A Unified Framework for Real-World, Cross-Magnification, and Trustworthy Breast Cancer Histopathology
Enam Ahmed Taufika, Md Ahasanul Arafatha, Abhijit Kumar Ghoshb +2
Accurate and reliable histopathological image classification is essential for breast cancer diagnosis. However, many deep learning models remain sensitive to magnification variabil…
Colorectal Cancer Histopathological Grading using Multi-Scale Federated Learning
Md Ahasanul Arafath, Abhijit Kumar Ghosh, Md Rony Ahmed +5
Colorectal cancer (CRC) grading is a critical prognostic factor but remains hampered by inter-observer variability and the privacy constraints of multi-institutional data sharing.…
Identification of Shared Genetic Biomarkers to Discover Candidate Drugs for Cervical and Endometrial Cancer by Using the Integrated Bioinformatics Approaches
Md. Selim Reza, Mst. Ayesha Siddika, Md. Tofazzal Hossain +2
Cervical (CC) and endometrial cancers (EC) are two common types of gynecological tumors that threaten the health of females worldwide. Since their underlying mechanisms and associa…
Transforming Multi-Omics Integration with GANs: Applications in Alzheimer's and Cancer
Md Selim Reza, Sabrin Afroz, Mostafizer Rahman +1
Multi-omics data integration is crucial for understanding complex diseases, yet limited sample sizes, noise, and heterogeneity often reduce predictive power. To address these chall…
Artificial Intelligence Powered Identification of Potential Antidiabetic Compounds in Ficus religiosa
Md Ashad Alam, Md Amanullah
Diabetes mellitus is a chronic metabolic disorder that necessitates novel therapeutic innovations due to its gradual progression and the onset of various metabolic complications. R…
Identifying multi-omics interactions for lung cancer drug targets discovery using Kernel Machine Regression
Md. Imtyaz Ahmed, Md. Delwar Hossain, Md Mostafizer Rahman +4
Cancer exhibits diverse and complex phenotypes driven by multifaceted molecular interactions. Recent biomedical research has emphasized the comprehensive study of such diseases by…