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Similar case recommendation method based on comprehensive feature representation and improved width-depth model

A technology that integrates features and deep models. It is applied to biological neural network models, patient-specific data, and medical data mining. It can solve problems such as failure to achieve expected results and improve recommendation efficiency.

Active Publication Date: 2019-10-01
KUNMING UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

Make traditional rule-based diagnosis and case recommendation methods less than expected

Method used

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  • Similar case recommendation method based on comprehensive feature representation and improved width-depth model
  • Similar case recommendation method based on comprehensive feature representation and improved width-depth model
  • Similar case recommendation method based on comprehensive feature representation and improved width-depth model

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Embodiment 1

[0045] Embodiment 1: as Figure 1-4 As shown, the similar case recommendation method based on comprehensive feature representation and improved wide-depth model, the specific steps of the method are as follows:

[0046] Step1. First desensitize the medical text of the text, and segment the medical text; add THULAC words to the characteristic terms of traditional Chinese medicine, the basic theoretical terms of traditional Chinese medicine, the unique names of diseases and symptoms of traditional Chinese medicine, the terms of traditional Chinese medicine treatment principles and prescriptions library, and use THULAC for word segmentation to obtain the corpus representation in units of words;

[0047] Step2, perform feature partitioning, map discrete features into real-valued vectors; segment continuous features according to the steps in Step1, and use Word2Vec to obtain the word vector representation of the corpus;

[0048] Step3. Construct a comprehensive feature representat...

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Abstract

The invention relates to a similar case recommendation method based on comprehensive feature representation and an improved width-depth model, and belongs to the technical field of computer natural language processing. According to the invention, the method comprises the steps: firstly, obtaining comprehensive features described by medical records through a comprehensive feature representation model, and performing disease screening; secondly, processing the discrete features by adopting a cross feature method, inputting the discrete features into a linear part, combining comprehensive features described by medical records with shallow model features, and inputting the combined features into a recommendation sorting part taking a gate loop unit as a core; and finally, on the basis of hundreds of candidate cases, outputting dozens of case recommendation items. According to the method, the personalized case recommendation is realized, a recommendation sorting algorithm model combining atraditional shallow linear model and a deep network model is provided, and the accuracy of similar case recommendation is improved.

Description

technical field [0001] The invention relates to a similar case recommendation method based on comprehensive feature representation and improved wide-depth model, which belongs to the technical field of computer natural language processing. Background technique [0002] With the rapid development of smart medical care, artificial intelligence technology is gradually integrated into the medical industry, and a health and medical information platform for interaction between patients, medical staff, and medical institutions has emerged as the times require. At present, research on clinical auxiliary diagnosis and treatment is mainly through the analysis and processing of massive medical and diagnostic data in the form of multimedia. Therefore, the feature extraction of massive data is essential, and how to carry out personalized diagnosis and treatment applications also has far-reaching research significance. [0003] Compared with the existing medical medical record recommenda...

Claims

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Application Information

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IPC IPC(8): G16H10/60G16H50/70G06F17/27G06F16/83G06F21/62G06N3/04
CPCG16H10/60G16H50/70G06F16/83G06F21/6245G06F40/242G06F40/289G06F40/30G06N3/045
Inventor 黄青松杨承启王艺平刘利军冯旭鹏
Owner KUNMING UNIV OF SCI & TECH
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