Chapter 9 Table 9.2 Classification performance of selected Si‐sensor features TP TN Sensitivity Specificity PPV NPV Accuracy LOO CV 20/22 11/18 91 (69‐98) 61 (36‐82) 74 (53‐88) 85 (54‐97) 78 TT CV 10/10 0/5 100 (66‐100) 0 (0‐54) 67 (39‐87) ‐ 67 TP = true positive; TN = true negative numbers indicate identified tissue spots. A positive test is defined as the tissue observed being RLN; a negative test is defined as the tissue observed being adipose tissue. Sensitivity; specificity; PPV = positive predictive value; NPV = negative predictive value; accuracy numbers are percentages; numbers in parentheses indicate 95% confidence interval. LOO CV = leave‐one‐out cross– validation; TT CV = train‐test cross‐validation. Classification of spectral data in InGaAs‐sensor range From the 36 extracted features, defined in Figure 9.2, 25 were located within the spectral detection range of InGaAs. After binary logistic regression, gradient Ft12 (W1 ‐ F4) and amplitude difference Ft26 (F2 – F1) were selected as the most promising combination for differentiation of RLN from surrounding adipose tissue. Figure 9.5 shows a scatter plot for these InGaAs‐sensor based features extracted for nerve and adipose tissue. Data for thyroid and parathyroid surgery and carpal tunnel release surgery data are included. Figure 9.5 Scatter plot of two selected features within InGaAs‐range 138 Scatter plot showing two computer‐selected features (gradient Ft12 and amplitude difference Ft26). Data measured during thyroid and parathyroid surgery and carpal tunnel release surgery are included.
proefschrift_Schols_SLV
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