Identifying Facial Features and Predicting Patients of Acromegaly Using Three-Dimensional Imaging Techniques and Machine Learning.

We further applied a permutation procedure to establish the statistical significance of such prediction accuracies against the chance level, and both turned out to be highly significant ( p < 0.0001 for females and p < 0.001 for males).

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