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. Author manuscript; available in PMC: 2022 Aug 5.
Published in final edited form as: IEEE J Biomed Health Inform. 2021 Aug 5;25(8):2906–2916. doi: 10.1109/JBHI.2020.3048901

TABLE III.

diagnostic ability of AHICNN for the ahi cutoffs= 1e/h, 5 e/h, and 10 e/h in the CHAT, UofC and BUH test databases

Estimated
AHI
CHAT test set UofC test set BUH test set

AHI = 1
e/h
AHI =5
e/h
AHI = 10
e/h
AHI = 1
e/h
AHI =5
e/h
AHI = 10
e/h
AHI = 1
e/h
AHI =5
e/h
AHI = 10
e/h
Se (%) 71.2 83.7 83.9 90.8 76.0 79.5 88.8 61.1 65.0
Sp (%) 81.8 100 99.3 36.4 88.6 95.8 53.2 93.7 96.9
PPV (%) 72.4 100 92.9 85.4 79.8 83.5 83.8 81.5 81.3
NPV (%) 81.0 97.0 98.2 49.1 86.2 94.6 63.5 84.2 93.0
LR+ 3.92 N.D 117.84 1.43 6.68 18.90 1.90 9.72 20.69
LR− 0.35 0.16 0.16 0.25 0.27 0.21 0.21 0.42 0.36
Acc (%) 77.6 97.4 97.8 80.1 83.9 92.3 79.2 83.5 91.3
kappa 0.515 0.422 0.423

CNN = Convolutional neural network, AHI = apnea-hypopnea index, Se = sensitivity, Sp = specificity, PPV = positive predictive value, NPV = negative predictive value, LR+ = positive likelihood ratio, LR- = negative likelihood ratio, Acc = accuracy, kappa = Cohen’s kappa index, N.D = not defined, CHAT = Childhood Adenotonsillectomy Trial, UofC = University of Chicago, BUH = Burgos University Hospital.