1naresh
Array ( [urn:ac.highwire.org:guest:identity] => Array ( [runtime-id] => urn:ac.highwire.org:guest:identity [type] => guest [service-id] => ajnr-ac.highwire.org [access-type] => Controlled [privilege] => Array ( [urn:ac.highwire.org:guest:privilege] => Array ( [runtime-id] => urn:ac.highwire.org:guest:privilege [type] => privilege-set [privilege-set] => GUEST ) ) [credentials] => Array ( [method] => guest ) ) ) 1nareshArray ( [urn:ac.highwire.org:guest:identity] => Array ( [runtime-id] => urn:ac.highwire.org:guest:identity [type] => guest [service-id] => ajnr-ac.highwire.org [access-type] => Controlled [privilege] => Array ( [urn:ac.highwire.org:guest:privilege] => Array ( [runtime-id] => urn:ac.highwire.org:guest:privilege [type] => privilege-set [privilege-set] => GUEST ) ) [credentials] => Array ( [method] => guest ) ) )Table 3:Diagnostic performances of the ADC1000 and ADCratio
Cutoff Valuea Sensitivity (%) Specificity (%) PPV (%) NPV (%) Accuracy (%) ADC1000 1.460 × 10−3 mm2/s 85.0 (17/20) 84.6 (11/13) 89.5 (17/19) 78.6 (11/14) 84.8 (28/33) ADCratio 62.6% 95.0 (19/20) 69.2 (9/13) 69.6 (16/23) 90.0 (9/10) 84.8 (28/33)
Note:—Raw data are in parentheses. NPV indicates negative predictive value; PPV, positive predictive value.
↵a Receiver operating characteristic curves were drawn to find the optimal cutoff values for the ADC1000 and ADCratio.