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 2:Performance of radiomic features
No. of Folds No. of Trees AUC (SD) (95% CI) Mean Sensitivity (95% CI) Mean Specificity (95% CI) Mean PPV (95% CI) Mean NPV (95% CI) Top 10 Predictive Features on the External Dataset 4 25 0.75 (SD, 0.12) (0.62–0.89) 0.72 (0.60–0.84) 0.86 (0.76–0.95) 0.73 (0.60–0.87) 0.85 (0.80–0.91) (585, 374, 761, 22, 17, 560, 344, 258, 148, 108)
Note:—SD indicates Standard Deviation; PPV, Positive Predictive Value; NPV; Negative Predictive Value.