Medical data classification and grading method, computer equipment and storage medium

A medical data and grading method technology, applied in the field of electronic digital data, can solve the problems of low accuracy of medical data classification results, large dimensions, and sparse data, so as to reduce interdependence, reduce the amount of calculation, and alleviate the disappearance of gradients Effect

Inactive Publication Date: 2021-10-29
成都健康医联信息产业有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to solve the above problems, the present invention proposes a medical data classification and grading method, computer equipment and storage media, which are used to solve the problem of low accuracy of medical data classification results caused by sparse data and large dimensions

Method used

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  • Medical data classification and grading method, computer equipment and storage medium
  • Medical data classification and grading method, computer equipment and storage medium
  • Medical data classification and grading method, computer equipment and storage medium

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Embodiment 1

[0046] Such as figure 1 As shown, this embodiment provides a method for classifying and grading medical data, including the following steps:

[0047] S1. Medical data preprocessing, including the following sub-steps:

[0048] S101. Using a word segmentation tool to perform word segmentation according to the medical data in the medical data set;

[0049] S102. Establish a stop word corpus according to the words and punctuation marks that need to be filtered out, and after word segmentation, filter out the stop words in the word segmentation results according to the stop word corpus;

[0050]S103. Bag the filtered medical data, count the word frequency and build a dictionary, for example:

[0051] {unknown: 0, discomfort: 1, postoperative: 2, follow-up: 3, pain: 4, follow-up: 5, cough: 6, ...}

[0052] S2. Extract word vectors:

[0053] The input of the classification model is a word vector, and a word vector corpus needs to be constructed. Word vectorization is performed o...

Embodiment 2

[0096] This embodiment is on the basis of embodiment 1:

[0097] This embodiment provides a computer device, including a memory and a processor, the memory stores a computer program, and the processor implements the steps of the method for classifying and grading medical data in Embodiment 1 when executing the computer program. Among them, the computer program may be in the form of source code, object code, executable file or some intermediate form.

Embodiment 3

[0099] This embodiment is on the basis of embodiment 1:

[0100] This embodiment provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the method for classifying and grading medical data in Embodiment 1 are implemented. Among them, the computer program may be in the form of source code, object code, executable file or some intermediate form. The storage medium includes: any entity or device capable of carrying computer program code, recording medium, computer memory, read only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, software distribution medium, etc. It should be noted that the content contained in the storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the storage ...

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Abstract

The invention discloses a medical data classification and grading method, computer equipment and a storage medium. The method comprises the steps of medical data preprocessing: performing word segmentation, filtering and word bag processing on medical data; word vector extraction: performing word vectorization on the preprocessed medical data, namely mapping the preprocessed medical data into word vectors, and constructing a word vector corpus according to the generated word vectors; constructing a classification model: inputting the word vectors in the word vector corpus to a TextCNN model for training; and classification and classification prediction: calling the trained TextCNN model to calculate the classification and classification probability of the to-be-classified medical data, and outputting a classification and classification result. According to the method, the problem of low accuracy of a medical data classification result caused by data sparsity and huge dimension can be well solved.

Description

technical field [0001] The invention relates to the technical field of electric digital data, in particular to a medical data classification and grading method, computer equipment and a storage medium. Background technique [0002] Traditional medical data classification methods are mainly divided into two categories. One is the data classification based on the dictionary, which compares the data with the established dictionary database to classify. The second is data classification based on machine learning. This method uses feature engineering such as text preprocessing, feature extraction, and text representation, such as calculating the frequency of words through the bag of words model, and calculating the weight of words in the text through the TF-IDF model. On the basis of feature engineering, classification models such as SVM, Naive Bayesian, and K nearest neighbor classification are used for classification. [0003] But there is following defective in above-mention...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/70G16H10/60G06F40/242G06F40/279G06K9/62G06N3/04G06N3/08
CPCG16H50/70G16H10/60G06F40/242G06F40/279G06N3/08G06N3/045G06F18/213
Inventor 顾勤李正赵婷吴直高李青光
Owner 成都健康医联信息产业有限公司
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