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The conventional B-mode image indicated no ability to identify the change in tissue stiffness after RFA.
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A value of 0.5 indicates no ability, beyond that of chance, of the model to discriminate between ranks of participants in terms of risk; a value of 1 indicates perfect discrimination; a value less than 0.5 would indicate discrimination in the opposite direction to that expected.
The capacity of a model to predict haemorrhage was evaluated using the area under the receiver-operating characteristic (ROC) curve (C-statistic), with values of 1.0 representing perfect ability and 0.5 indicating no better ability than chance.
AUC of 0.5 indicates no predictive ability, whereas a value of 1 represents perfect predictive ability.
An AUC less than 0.5 indicates no predictive ability, whereas an AUC greater than 0.5 represents predictive ability statistically.
The concordance statistic for survival data indicates the probability that for a randomly chosen pair of persons, the one having the higher predicted survival is the one who survives longer: 0.5 indicates no discriminative ability and 1.0 indicates no false classifications.
Similarly, RN=0 indicates no predictive ability and RN=1 indicates perfect predictions.
An index of 0.5 indicates no discrimination ability, whereas a value of 1 indicates perfect discrimination.
A C-index value of 0.5 indicates no discriminative ability, beyond that of chance, and 1 indicates perfect discrimination.
An AUC value of 0.5 indicates no discriminative ability, and a value of 1 indicates perfect discrimination.
The areas under the ROC curves were relatively low but significantly higher than 0.5, the value indicating no predictive ability.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com