Computing Sickle Erythrocyte Health Index Based on Quantitative Phase Imaging and Machine Learning
This study developed an in-vitro assessment, the Sickle Erythrocyte Health Index, using quantitative phase imaging (QPI) and machine learning to model the health of RBCs in people with SCD. The Health Index combines assessment of cell deformation, sickle-shaped classification, and membrane flexibility to evaluate erythrocyte health.
Source: Experimental Hematology - Category: Hematology Authors: Yaw O.N. Ansong-Ansongton, Timothy D. Adamson Tags: Article Source Type: research
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