Deep learning based intelligent skin disease auxiliary diagnosis system

A technology for auxiliary diagnosis and skin diseases. It is applied in the fields of medical automation diagnosis, computer-aided medical procedures, informatics, etc. It can solve the problem of not being able to do one-time identification, and achieve the effect of accurate analysis, reducing interference and improving accuracy.

Active Publication Date: 2018-06-22
洛阳飞来石软件开发有限公司
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AI Technical Summary

Problems solved by technology

At present, most artificial intelligence models on the market cannot achieve one-time recognition.

Method used

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  • Deep learning based intelligent skin disease auxiliary diagnosis system
  • Deep learning based intelligent skin disease auxiliary diagnosis system

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Embodiment Construction

[0019] The technical solutions of the present invention will be further described below in conjunction with specific embodiments.

[0020] As shown in the figure: an intelligent auxiliary diagnosis system for skin diseases based on deep learning: including a classifier training unit, a language model unit and an intelligent auxiliary diagnosis unit;

[0021] The intelligent auxiliary diagnosis unit includes an image acquisition module, a voice consultation module, a speech recognition and keyword extraction module, a probability classification model, an RNN disease analysis module, and a fusion classifier. The image acquisition module (including a polarized light contact dermatoscope) is used for The image of the affected part of the skin patient is collected and input into the probability classification model, collected by the dermatoscope, the polarized light removes impurities and reflections on the skin surface, and directly penetrates into the dermis layer, so that the pat...

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Abstract

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.

Description

technical field [0001] The invention relates to the technical field of skin disease diagnosis equipment, in particular to an intelligent auxiliary diagnosis system for skin diseases based on deep learning. Background technique [0002] There are many kinds of skin diseases, and the pathogenic factors are intricate, and there are more than 2,000 kinds only recorded in the book. In addition, there are various forms of skin lesions, and the appearance of some skin lesions is very similar, which hinders the diagnosis and treatment of skin diseases. Under such circumstances, young dermatologists need to study for many years before they can maturely master the skills, which brings great challenges to the clinical diagnosis of dermatologists, especially grassroots dermatologists. For patients, unlike a cold and fever, skin diseases can be searched for information on the Internet according to symptoms, but rashes are difficult to describe in words. [0003] With the help of artifi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/20G16H80/00G16H30/20G16H50/70G06K9/00G06K9/62
CPCG06V20/69G06F18/24
Inventor 董岩周煜张乐毅
Owner 洛阳飞来石软件开发有限公司
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