Depression auxiliary detection method based on open question and answer text

A technology for auxiliary detection and depression, applied in unstructured text data retrieval, text database clustering/classification, instruments, etc.

Inactive Publication Date: 2019-12-03
成都中科云集信息技术有限公司
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[0008] 3) At present, technologies in various fields have developed rapidly to varying degrees, and technology updates are needed to better mine information

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  • Depression auxiliary detection method based on open question and answer text
  • Depression auxiliary detection method based on open question and answer text
  • Depression auxiliary detection method based on open question and answer text

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[0025] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms without being limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0026] Such as figure 1 As shown, it is a work flow diagram of an auxiliary detection method for depression based on an open question and answer text of the present invention, wherein a method for auxiliary detection of depression based on an open question and answer text includes: text collection, using speech recognition technology to extract dialogue Text; text preprocessing, text preprocessing according to data characteristics and ...

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Abstract

The invention discloses a depression auxiliary detection method based on an open question and answer text, which is mainly characterized in that the depression auxiliary detection method is a text analysis method suitable for dialogue between a depression patient and a doctor, a model is retrained along with the increase of dialogue data to achieve a self-learning improvement effect, and the depression auxiliary detection method specifically comprises the following steps: text collection: extracting a dialogue text by using a voice recognition technology; text preprocessing: performing text preprocessing according to data features and model design; training a text semantic model, and performing semantic mining on the preprocessed text; predicting a text model and classifying features output by the semantic mining model. The model is self-learned, and the model can be self-iterated and updated along with the increase of the number of recognized samples.

Description

technical field [0001] The invention relates to the technical field of computer-aided medical diagnosis, in particular to an auxiliary detection method for depression based on an open question-and-answer text Background technique [0002] As the number of people living with depression has steadily increased, so has the difficulty of accurately diagnosing it. The World Health Organization (WTO) predicts that by 2020, depression will become the second leading cause of disease in the world, and the automatic detection of depression symptoms is breaking this tradition, and it can potentially improve the accuracy and effectiveness of diagnosis without clinical detection. This will lead to faster intervention and assist doctors in making accurate assessments. [0003] Severe depression can lead to neurophysiological and neurocognitive changes that affect facial expression, speech and cognitive function, and expression. The manifestations of depression will be reflected in some b...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/35G06F16/36G06F17/27
CPCG06F16/353G06F16/36
Inventor 田文洪莫中勤舒展
Owner 成都中科云集信息技术有限公司
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