Based on analyzing and comparatively studying the two algorithms of machine learning,namely,the artificial neural network (ANN) and support vector machine (SVM),the modeling,data classification and prediction for magnetic resonance images (MRIs) of the neuromuscular disease,(duchenne musular dystrophy,DMD),were carried out.The conclusions of the study are as follows.The outcomes of the two algorithms indicate that between the two kinds of DMD MRI images(T1 and T2),the T1 image has clearer texture feature.Therefore,patients could just need T1 scanning for MRI examination.If the model parameters are selected appropriately,the two algorithm models could produce very excellent classification prediction outcomes respectively.The sensitivity,specificity and accuracy rate might reach as high as 98.5%,97.3%,97.9% and 96.9%,97.3% and 97.1% respectively.The machine learning method could be used as a non-invasive detection technology in the treatment of DMD MRI images and it is expected to provide an objective and effective diagnostic method for clinical.