Human body constitution recognition method and system based on neural network classifier

A neural network and neural network model technology, applied in the field of artificial intelligence machine learning, can solve problems such as poor experience, insufficient objectivity, and subjective components in answering questions, so as to achieve good experience, improve objectivity and accuracy

Inactive Publication Date: 2019-05-21
上海铀米机器人科技有限公司
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Problems solved by technology

In "Traditional Chinese Medicine Physique Classification, Judgment Method and Judgment Standard", constitution identification is based on the scale method, which has the following deficiencies: 1. When judging const

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  • Human body constitution recognition method and system based on neural network classifier
  • Human body constitution recognition method and system based on neural network classifier

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[0051] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0052] In the first embodiment of the present invention, a human body physique identification method based on a neural network classifier is described, which solves the problem of physique analysis and classification based on multi-modal human vital signs such as consultation, tongue examination, facial examination, and pulse diagnosis. It mainly includes the following steps:

[0053] Step 101: Train a neural network model, construct a cla...

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Abstract

The invention discloses a human body constitution recognition method based on a neural network classifier. The human body constitution recognition method comprises the steps that a neural network model is trained, a human body constitution classifier is constructed, and the human body constitution neural network classifier is arranged on a server; multi-modality human body vital sign data is collected; the multi-modality human body vital sign data is preprocessed, and the processed data is uploaded to the server; the neural network classifier on the server outputs human body constitution information according to the obtained data and transmits the human body constitution information to a constitution recognition instrument. The invention further discloses a human body constitution recognition system based on the neural network classifier. Multi-modality human body vital signs integrating interrogation, tongue diagnosis, face diagnosis, pulse diagnosis and the like are achieved, and byusing the neural network classifier, the human body constitution is more objectively and accurately recognized.

Description

technical field [0001] The invention relates to the technology of artificial intelligence machine learning, in particular to the technology of the application of artificial intelligence in the field of traditional Chinese medicine. Background technique [0002] TCM constitution theory has a wide range of applications. By studying the relationship between different constitution types and diseases, it emphasizes the adjustability of constitution, starting from improving constitution, and providing conditions for improving the pathological state of sick individuals; realizing individualized diagnosis and treatment, and clinically treating diseases. In the diagnosis and treatment activities, the prevention and treatment measures and treatment methods for diseases are based on the identification of physical constitution, fully consider the physical characteristics of the person, and take corresponding treatment measures according to their physical characteristics; Academic thinki...

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Application Information

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IPC IPC(8): A61B5/02A61B5/00
Inventor 徐兆红杨华元秦晶张奎张文秋韵
Owner 上海铀米机器人科技有限公司
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