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.