. 2026 Mar 21;26:148. doi: 10.1186/s12911-026-03451-y

Table 5.

Performance metrics of the Red Blood Cell Indices → Image Analysis pipeline for β-thalassemia screening. The MLP model was applied to Red Blood Cell parameters first, followed by VGG-16–based image analysis for Red Blood Cell indices analysis-negative cases

Step	Model	Sensitivity (%)	Specificity (%)	Classification Accuracy (%)
1	Red Blood Cell Indices Analysis (MLP) only	88.2% (63.6–98.5%)	92.9% (76.5–99.1%)	91.1% (78.8–97.5%)
2	Image Analysis (VGG-16) only	100.0% (15.8–100%)	57.7% (36.9–76.6%)	60.7% (40.6–78.5%)
Overall Pipeline	100% (80.5–100%)	60.7% (40.6–78.5%)	75.6% (60.5–87.1%)

Step

Model

Sensitivity (%)

Specificity (%)

Classification Accuracy (%)

Red Blood Cell Indices Analysis (MLP) only

88.2%

(63.6–98.5%)

92.9%

(76.5–99.1%)

91.1%

(78.8–97.5%)

Image Analysis (VGG-16) only

100.0%

(15.8–100%)

57.7%

(36.9–76.6%)

60.7%

(40.6–78.5%)

Overall Pipeline

100%

(80.5–100%)

60.7%

(40.6–78.5%)

75.6%

(60.5–87.1%)