Fig. 1: Performance characteristics of urine biomarkers interpreted using logistic regression, neural network, neuro-fuzzy technology, random forest and support vector machine for detection of pancreatic cancer (PDAC) cases. | British Journal of Cancer

Fig. 1: Performance characteristics of urine biomarkers interpreted using logistic regression, neural network, neuro-fuzzy technology, random forest and support vector machine for detection of pancreatic cancer (PDAC) cases.

From: Development of PancRISK, a urine biomarker-based risk score for stratified screening of pancreatic cancer patients

Fig. 1

Circle points give particular values of sensitivity and specificity provided by random forest and support vector machine. LR logistic regression, NN neural network, NFT neuro-fuzzy technology, RF random forest, SVM support vector machine, AUC area under ROC curve.

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