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The association of index and PML risk was initially explored using a test set of samples and then confirmed using a verification set.
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Two thirds of the training pool was used for training and the remaining third served as a verification set.
In order to achieve this aim, the known samples which are used as calibraion set are generally divided into two parts: a training set and a verification set.
The data were divided into a "calibration" and a "verification" set.
Although the verification set is used to identify the best network, actually, training algorithms do not use the verification set to adjust network weights.
In a verification setting, we use all possible combinations for matching genuine pairs and the first sample of each subject is chosen for imposter matches (5880 (210×8×7/2) genuine comparisons and 21945 (210×209/2) imposter comparisons) in order to evaluate the performance of the biometric hashing scheme.
The Nash Sutcliffe (N S) coefficient of efficiency was used to assess the quality of prediction of the verification set as a function of the length of the calibration set.
This quantity is computed both using the calibration set and a new set of input/output values, not used by the calibration procedure, called validation or verification set.
Subsequent analysis using the verification data set confirmed the association between index and PML, with a significantly higher index distribution for pre-PML samples from PML patients than for samples from non-PML patients (median = 2.3 vs 1.9; p = 0.0199; see Fig 1B).
Each architecture uses a different combination of neurons and inputs and each network has its own training and verification set.
These results indicate that our scoring system may be applied to predict severe chemotherapy-induced alopecia and might provide useful information for better understanding of the hair-loss mechanism, even though further verification using an additional independent set(s) of samples is warranted.
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CEO of Professional Science Editing for Scientists @ prosciediting.com