Ming Dao

This paper improves sickle cell disease morphology analysis by combining a YOLO detector with a DenseNet classifier for accurate detection and classification of red blood cell morphologies in full-scope microscopy images.

This paper develops a computational platform to evaluate anti-sickling agents by integrating PK/PD models with RBC sickling kinetics, demonstrating its utility in predicting therapeutic efficacy and noncompliance outcomes for existing and potential drugs.

This study uses computational models to show that deformable interendothelial slits in the spleen better predict RBC filtration compared to rigid models, improving understanding of splenic hemodynamics and filtration mechanisms.