The invention relates to a deep learning based intelligent skin disease auxiliary diagnosis system, which comprises a classifier training unit, a language model unit and an intelligent auxiliary diagnosis unit. The intelligent auxiliary diagnosis unit comprises an image acquisition module, a voice interrogation module, a voice recognition and keyword extraction module, a probability classificationmodel, a RNN condition analysis module and a fusion classifier. The classifier training unit comprises a state diagram training set under a dermatoscope, a state standard database under skin lesion and dermatoscope, a CNN network convolution module and a sampling and classifying module. The language model unit comprises a medical term standard library, a RNN questioning management module, a RNN chief complaint management module and a skin disease medical knowledge base. The auxiliary diagnosis system has advantages that by deep learning for classifying skin lesion images, probable results areinferred, then a pre-installed dermatoscope image and histodiagnosis tag database is retrieved for doctors' reference, and accordingly accuracy in skin disease diagnosis can be greatly improved.