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Fig. 1 | BMC Medical Informatics and Decision Making

Fig. 1

From: Diagnostic support for selected neuromuscular diseases using answer-pattern recognition and data mining techniques: a proof of concept multicenter prospective trial

Fig. 1

ROC curves and AUC values indicate variable diagnostic sensitivity among different classifier systems for identifying patients with Pompe disease. The results are based on the training set of 210 questionnaires during cross validation. The best classifier results were obtained with the fusion classifier (black line, 100 % correct diagnoses), which identified all 43 Pompe patients during the 21-fold stratified cross-validation runs

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