Fig. 3.

General framework of our method to automatically detect acromegaly from Facial Photographs using Machine Learning Methods: the most left part showed the training processing, which included face detection and normalization from original input images, facial feature extraction and landmark localization, and face frontalization to improve the accuracy of acromegaly diagnosis; the middle left part showed the model training processing, which included Generalized Linear Models(LM), K-nearest neighbors (KNN), Support Vector Machines (SVM), Forests of randomized trees (RT), Convolutional Neural Network (CNN), and Ensemble Method (EM); the middle right part showed the testing processing with the trained models; the most right part showed the evaluation between the ground truth, computers and doctors.