Research ArticleResearch and Reports

A Seven-Parameter Approach to White Blood Cell Identification

Audrey Memmott, Dylan Tanner and Ryan Cordner
American Society for Clinical Laboratory Science January 2024, 37 (1) 18-23; DOI: https://doi.org/10.29074/ascls.2023003225

Article Figures & Data

Figures

  • Figure 1.
    Figure 1.

    Seven-cell morphology parameters. (A) Box 1 indicates chromatin pattern (lacey). Box 2 indicates cellular shape (round). (B) Box 3 indicates granulation type (eosinophilic). Box 4 indicates granulation amount (many). Box 5 indicates nuclear shape (bilobed). (C) Box 6 indicates nucleoli presence (one). Box 7 indicates cytoplasm color (violet).

  • Figure 2.
    Figure 2.

    Variable optimization and importance. (A) Decreasing the number variables, starting with the least important variable decreased the overall AUC of the model. (B) Decreasing the number of variables used by the model also increased the overall MSE of the model. (C) The relative importance of each variable in reducing the MSE of the model’s performance is displayed. The most important variable is scaled to 100% important.

  • Figure 3.
    Figure 3.

    Variable optimization and importance without color. (A) The impact of decreasing the number of variables, starting with the least important variable on AUC. (B) The impact of decreasing the number of variables used by the model on MSE. (C) The relative importance of each variable in reducing the MSE of the model’s performance is displayed. The most important variable is scaled to 100% important.

Tables

  • Table 1.

    Cell prediction metrics

    BandBasophilBlastEosinophilLymphocyteMetamyelocyteMonocyteMyelocyteSegmented
    Neutrophil    		NRBCProlymphocytePromonocytePromyelocyteReactive
    Lymphocyte    		Smudge
    Cell
    Accuracy0.99910.97410.9600.9990.9710.9990.9980.9980.9810.9810.9820.9670.999
    Misclassification rate0.00100.02600.0390.0010.0280.0010.0020.0020.0180.0180.0170.0320.001
    Precision0.99110.78210.8730.9830.8580.988110.620.4040.9750.7370.985
    Sensitivity1.00010.76710.81710.79610.9880.9070.6890.9130.7260.8711
    Specificity0.99910.98710.9820.9990.9880.999110.9820.9820.9990.9750.999

    The model’s performance for accuracy, precision, sensitivity, and specificity for each cell type from the test data are presented.

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    A Seven-Parameter Approach to White Blood Cell Identification
    Audrey Memmott, Dylan Tanner, Ryan Cordner
    American Society for Clinical Laboratory Science Jan 2024, 37 (1) 18-23; DOI: 10.29074/ascls.2023003225
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