Table 2.
Predictive performance of the best ML models using NIR spectral data from first trimester serum samples.
| Range a | Pretreatment | Sp | Se | NER | |||
|---|---|---|---|---|---|---|---|
| Av | StD | Av | StD | Av | StD | ||
| Full | SM (W = 23) + N + MC | 0.6946 | 0.0456 | 0.4507 | 0.0681 | 0.5726 | 0.0410 |
| R1 | N + MC | 0.6722 | 0.0361 | 0.5920 | 0.0910 | 0.6321 | 0.0489 |
| R2 | SM (W = 3) + N + MC | 0.5678 | 0.0322 | 0.6480 | 0.1035 | 0.6079 | 0.0542 |
| R3 | SM (W = 23) + MC | 0.5931 | 0.0346 | 0.5133 | 0.0811 | 0.5532 | 0.0441 |
a Full: 10,500–4000 cm−1; R1: 10,500–7600 cm−1; R2: 7600–5100 cm−1; R3: 5100–4000 cm−1. Sp: specificity; Se: sensitivity; NER: non-error rate; Av: average; StD: standard deviation; R1: Range 1; R2: Range 2; R3: Range 3; SM: smoothing; W: width; N: normalization; MC: mean centering.