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Machine learning, medical diagnosis, and biomedical engineering research - commentary

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Figure

Figure 1 Apparent accuracy of classifiers (ACC) applied to synthetic training sets of equal numbersof “healthy” and “ill” subjects, with 10 attributes for each subject created using a random numbergenerator
Figure 2 Sensitivity (SEN) and specificity (SPC) of classifier applied to a validation set of 50 healthyand 50 ill subjects
Table 1 Impact of the operator and the device type on the sensitivity and specificity ofthe classifier SVM
Table 2 Results of training a classifier with SVM (quadratic kernel), using a training set of400 ultrasound images (half from healthy individuals, half from individuals with Hashimoto’sdisease) with a validation set of 100 separate individuals, half of whom had the disease

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