Biological data analysis is an important approach which utilizes genomic, transcriptomics, proteomic, metabolomics, or clinical data for disease detection process. Diabetes and Leukemia are two distinct medical conditions, but research has shown type 2 diabetes patients have a 20% greater risk of being affected by blood cancers, like acute leukemia, indicating the relationship between the two diseases. Early detection of these diseases by analyzing the biological datasets is essential for providing prognostic support. However, the class imbalance and high dimensionality problems in Machine Learning (ML)-based techniques have often degraded effective analysis of clinical and genomic datasets for disease detection