This dataset contains key characteristics about the data described in the Data Descriptor The SUSTech-SYSU dataset for automatically segmenting and classifying corneal ulcers. Contents:
We developed the deep neural network model for the automatic classification of hallux sesamoid position according to Hardy and Clapham classificaion. This dataset includes the trained neural network m
Classification results of various methods in terms of classification accuracy, sensitivity, specificity, number of selected features and support vectors, and model parameters for Parkinson’s disease d
The development of automated tools using advanced technologies like deep learning holds great promise for improving the accuracy of lung nodule classification in computed tomography (CT) imaging, ulti
