CN112712863A - Method and system for calculating clinical data of accurate drug administration for liver metastasis of colon cancer - Google Patents
Method and system for calculating clinical data of accurate drug administration for liver metastasis of colon cancer Download PDFInfo
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- 206010009944 Colon cancer Diseases 0.000 title claims abstract description 81
- 206010027476 Metastases Diseases 0.000 title claims abstract description 81
- 208000029742 colonic neoplasm Diseases 0.000 title claims abstract description 81
- 210000004185 liver Anatomy 0.000 title claims abstract description 81
- 230000009401 metastasis Effects 0.000 title claims abstract description 81
- 238000000034 method Methods 0.000 title claims abstract description 48
- 238000001647 drug administration Methods 0.000 title abstract description 6
- 229940079593 drug Drugs 0.000 claims abstract description 59
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- 238000012937 correction Methods 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 abstract description 7
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Abstract
The invention provides a method and a system for calculating clinical data of accurate drug administration of liver metastasis of colon cancer, and relates to the technical field of medical data processing. The invention provides a method for calculating accurate medication clinical data of colon cancer liver metastasis, which comprises the steps of obtaining original data of an accurate medication clinical test of colon cancer liver metastasis and preprocessing the original data; inputting the original data into a pre-trained natural language processing model to obtain a result data set; and obtaining the directional demand data according to the result data set. The customized colon cancer liver metastasis accurate medication clinical data calculation has strong pertinence; the data output is structured, and the applicability is strong.
Description
Technical Field
The invention relates to the technical field of medical data processing, in particular to a method and a system for calculating clinical data of accurate medication of liver metastasis of colon cancer.
Background
Data generated in the process of diagnosis and treatment of a patient by a doctor, including basic data of the patient, an electronic medical record, diagnosis and treatment data, medical image data, medical management, economic data, medical equipment, instrument data and the like, is a main source of medical data by taking the patient as a center.
At present, aiming at multi-dimensional clinical test data related to colon cancer liver metastasis, the existing processing model relates to grammar development, grammar results and actual application data need to be combined to be subjected to specific semantic representation and association, but the search space is huge due to the fact that massive grammar structures exist in the current natural language, and the problem of avoiding generating ambiguous output is a great challenge for the existing products. In addition, there is sensitivity to medical data, requiring a secondary desensitization process; the medical structured data is special in demand, and the non-customized processing model cannot meet the requirement of multiple mechanisms.
However, medical big data contains abundant useful information. How to effectively mine and refine multi-dimensional clinical test data related to colon cancer liver metastasis so as to monitor the illness state of a patient user in a targeted manner, so that subsequent further information recommendation is facilitated, and the problem becomes a current hotspot.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a method and a system for calculating accurate medication clinical data of colon cancer liver metastasis, and solves the technical problem that multidimensional clinical test data related to colon cancer liver metastasis cannot be deeply utilized in the prior art.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme:
a method for calculating accurate medication clinical data of liver metastasis of colon cancer comprises the following steps:
s1, acquiring and preprocessing the original data of the colon cancer liver metastasis accurate medication clinical test;
s2, inputting the original data into a pre-trained natural language processing model to obtain a result data set;
and S3, obtaining the directional demand data according to the result data set.
Preferably, the raw data includes a data header and source data of the clinical test medical record, and a data identification field is set in the raw data for data duplication checking, data splicing or data capacity expansion.
Preferably, the preprocessing includes data cleaning and data vectorization.
Preferably, the building process of the natural language processing model in step S2 includes:
obtaining a plurality of pieces of original data of colon cancer liver metastasis accurate medication clinical tests, determining a result data set corresponding to the original data of the colon cancer liver metastasis accurate medication clinical tests,
taking the original data of the multiple colon cancer liver metastasis accurate medication clinical tests as training samples, taking corresponding result data sets as output labels, and constructing a training database;
and performing model training by adopting a deep learning algorithm based on the training database to obtain the natural language processing model.
Preferably, the model training using the deep learning algorithm includes:
and carrying out entity recognition and naming on the original data, analyzing, semantically analyzing, marking and recombining by combining grammar to form a first result data set after recombination.
Preferably, the step S3 specifically includes: and obtaining the directional demand data of the structured colon cancer liver metastasis accurate medication clinical test after matching with artificial correction according to the result data set.
A colon cancer liver metastasis accurate medication clinical data calculation system comprises:
the acquisition module is used for acquiring and preprocessing original data of a colon cancer liver metastasis accurate medication clinical test;
the processing module is used for inputting the original data into a pre-trained natural language processing model to obtain a result data set;
and the output module is used for obtaining the directional demand data according to the result data set.
Preferably, the raw data includes a data header and source data of the clinical test medical record, and a data identification field is set in the raw data for data duplication checking, data splicing or data capacity expansion.
Preferably, the preprocessing includes data cleaning and data vectorization.
Preferably, the process of constructing the natural language processing model in the processing module includes:
obtaining a plurality of pieces of original data of colon cancer liver metastasis accurate medication clinical tests, determining a result data set corresponding to the original data of the colon cancer liver metastasis accurate medication clinical tests,
taking the original data of the multiple colon cancer liver metastasis accurate medication clinical tests as training samples, taking corresponding result data sets as output labels, and constructing a training database;
and performing model training by adopting a deep learning algorithm based on the training database to obtain the natural language processing model.
(III) advantageous effects
The invention provides a method and a system for calculating clinical data of accurate drug administration of liver metastasis of colon cancer. Compared with the prior art, the method has the following beneficial effects:
the invention provides a method for calculating accurate medication clinical data of colon cancer liver metastasis, which comprises the steps of obtaining original data of an accurate medication clinical test of colon cancer liver metastasis and preprocessing the original data; inputting the original data into a pre-trained natural language processing model to obtain a result data set; and obtaining the directional demand data according to the result data set. The customized colon cancer liver metastasis accurate medication clinical data calculation has strong pertinence; the data output is structured, and the applicability is strong.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for calculating data of colon cancer liver metastasis accurate drug administration according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating an example of natural language processing of multi-dimensional clinical trial data related to liver metastasis of colon cancer according to an embodiment of the present invention;
fig. 3 is a block diagram of a system for calculating data of accurate drug administration clinical data of liver metastasis of colon cancer according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the application provides a method for calculating the accurate medication clinical data of the liver metastasis of the colon cancer, solves the technical problem that the prior art cannot deeply utilize multidimensional clinical test data related to the liver metastasis of the colon cancer, realizes calculation of customized accurate medication clinical data of the liver metastasis of the colon cancer, and has the advantage of strong pertinence.
In order to solve the technical problems, the general idea of the embodiment of the application is as follows:
the embodiment of the invention provides a method for calculating accurate medication clinical data of colon cancer liver metastasis, which comprises the steps of obtaining original data of an accurate medication clinical test of colon cancer liver metastasis and preprocessing the original data; inputting the original data into a pre-trained natural language processing model to obtain a result data set; and obtaining the directional demand data according to the result data set. The customized colon cancer liver metastasis accurate medication clinical data calculation has strong pertinence; the data output is structured, and the applicability is strong.
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
As shown in fig. 1, an embodiment of the present invention provides a method for calculating clinical data of colon cancer liver metastasis accurate medication, including:
s1, acquiring and preprocessing the original data of the colon cancer liver metastasis accurate medication clinical test;
s2, inputting the original data into a pre-trained natural language processing model to obtain a result data set;
and S3, obtaining the directional demand data according to the result data set.
The customized colon cancer liver metastasis accurate medication clinical data calculation has strong pertinence; the data output is structured, and the applicability is strong.
Example 1:
in a first aspect, as shown in fig. 1, an embodiment of the present invention provides a method for calculating clinical data of colon cancer liver metastasis accurate medication, specifically including:
s1, acquiring and preprocessing the primary data of the colon cancer liver metastasis accurate medication clinical test.
The original data comprises a clinical test case history data table header and source data, and a data identification field is set in the original data and is used for data duplication checking, data splicing or data capacity expansion.
The preprocessing comprises data cleaning and data vectorization.
And S2, inputting the original data into a pre-trained natural language processing model to obtain a result data set.
The construction process of the natural language processing model comprises the following steps:
obtaining a plurality of pieces of original data of colon cancer liver metastasis accurate medication clinical tests, determining a result data set corresponding to the original data of the colon cancer liver metastasis accurate medication clinical tests,
taking the original data of the multiple colon cancer liver metastasis accurate medication clinical tests as training samples, taking corresponding result data sets as output labels, and constructing a training database;
and performing model training by adopting a deep learning algorithm based on the training database to obtain the natural language processing model.
The model training by adopting the deep learning algorithm comprises the following steps:
and carrying out entity recognition and naming on the original data, analyzing, semantically analyzing, marking and recombining by combining grammar to form a first result data set after recombination.
As shown in FIG. 2, the statement entities are identified and named: the temporal words are named NT (temporal modifier), the nouns are named NN (nominal subject or direct object), the punctuation is named PU, the adjectives are named VV (connectionless modifier), and the verbs are named VA (verb modifier). After the naming is finished, the analysis, semantic analysis, marking and recombination are carried out by combining grammar. As in the first half of comma in fig. 2, the post-resolution-mark sentence is configured as: "this day" is NT time modifier, "patient" is NN noun subject, disease condition is NN noun subject, and "stable" is current sentence end phrase VA. After decomposition and recombination, a result data set is formed: "stable today", "stable patient" and "stable disease".
And S3, obtaining the directional demand data according to the result data set. The method specifically comprises the following steps:
and obtaining the directional demand data of the structured colon cancer liver metastasis accurate medication clinical test after matching with artificial correction according to the result data set.
The embodiment of the invention combines an algorithm model to search keywords/words of multidimensional clinical test data of colon cancer liver metastasis, the search process strictly conforms to a statement model, natural language is combined with actual data cleaning requirements through named entity recognition, syntactic analysis, semantic analysis and labeling and directional extraction by NLP technology, and effective high-quality data is generated. In addition, the system customizes algorithm, analyzes and processes the multi-dimensional clinical trial data of the existing colon cancer liver metastasis such as natural language data of disease courses and ward visits, extracts key words by combining semantic context, for example: diseases, disorders, etc.
The embodiment of the invention provides a method for calculating accurate medication clinical data for liver metastasis of colon cancer, which can be combined with a web application system and can be operated in a server or a cloud server. One skilled in the art can also run the method of the present invention on other application platforms as needed, which is not particularly limited in this exemplary embodiment.
Example 2:
in a second aspect, as shown in fig. 3, an embodiment of the present invention provides a system for calculating clinical data of colon cancer liver metastasis accurate medication, specifically including:
and the acquisition module is used for acquiring and preprocessing the original data of the colon cancer liver metastasis accurate medication clinical test.
The original data comprises a clinical test case history data table header and source data, and a data identification field is set in the original data and is used for data duplication checking, data splicing or data capacity expansion.
The preprocessing comprises data cleaning and data vectorization.
And the processing module is used for inputting the original data into a pre-trained natural language processing model to obtain a result data set.
The construction process of the natural language processing model in the processing module comprises the following steps:
obtaining a plurality of pieces of original data of colon cancer liver metastasis accurate medication clinical tests, determining a result data set corresponding to the original data of the colon cancer liver metastasis accurate medication clinical tests,
taking the original data of the multiple colon cancer liver metastasis accurate medication clinical tests as training samples, taking corresponding result data sets as output labels, and constructing a training database;
and performing model training by adopting a deep learning algorithm based on the training database to obtain the natural language processing model.
And the output module is used for obtaining the directional demand data according to the result data set.
It can be understood that the system for calculating the accurate medication clinical data of colon cancer liver metastasis provided by the present invention corresponds to the method for calculating the accurate medication clinical data of colon cancer liver metastasis provided by the present invention, and the explanation, examples, beneficial effects and other parts of the relevant contents thereof can refer to the corresponding parts in the method for calculating the accurate medication clinical data of colon cancer liver metastasis, and are not described herein again.
The embodiment of the invention combines an algorithm model to search keywords/words of multidimensional clinical test data of colon cancer liver metastasis, the search process strictly conforms to a statement model, natural language is combined with actual data cleaning requirements through named entity recognition, syntactic analysis, semantic analysis and labeling and directional extraction by NLP technology, and effective high-quality data is generated. In addition, the system customizes algorithm, analyzes and processes the multi-dimensional clinical trial data of the existing colon cancer liver metastasis such as natural language data of disease courses and ward visits, extracts key words by combining semantic context, for example: diseases, disorders, etc.
In summary, compared with the prior art, the method has the following beneficial effects:
1. the embodiment of the invention provides a method for calculating accurate medication clinical data of colon cancer liver metastasis, which comprises the steps of obtaining original data of an accurate medication clinical test of colon cancer liver metastasis and preprocessing the original data; inputting the original data into a pre-trained natural language processing model to obtain a result data set; and obtaining the directional demand data according to the result data set. The customized colon cancer liver metastasis accurate medication clinical data calculation has strong pertinence; the data output is structured, and the applicability is strong.
2. The embodiment of the invention combines an algorithm model to search keywords/words of multidimensional clinical test data of colon cancer liver metastasis, the search process strictly conforms to a statement model, natural language is combined with actual data cleaning requirements through named entity recognition, syntactic analysis, semantic analysis and labeling and directional extraction by NLP technology, and effective high-quality data is generated. In addition, the system customizes algorithm, analyzes and processes the multi-dimensional clinical trial data of the existing colon cancer liver metastasis such as natural language data of disease courses and ward visits, extracts key words by combining semantic context, for example: diseases, disorders, etc.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for calculating accurate medication clinical data of colon cancer liver metastasis is characterized by comprising the following steps:
s1, acquiring and preprocessing the original data of the colon cancer liver metastasis accurate medication clinical test;
s2, inputting the original data into a pre-trained natural language processing model to obtain a result data set;
and S3, obtaining the directional demand data according to the result data set.
2. The method for calculating the clinical data of the colon cancer liver metastasis accurately dosed according to claim 1, wherein the raw data comprises a data header and source data of clinical trial medical records, and a data identification field is set in the raw data for data duplication checking, data splicing or data volume expansion.
3. The method for accurately calculating clinical data of liver metastasis of colon cancer according to claim 1, wherein the preprocessing comprises data cleaning and data vectorization.
4. The method for estimating clinical data of colon cancer liver metastasis accurately dosed according to claim 1, wherein the constructing process of the natural language processing model in step S2 includes:
obtaining a plurality of pieces of original data of colon cancer liver metastasis accurate medication clinical tests, determining a result data set corresponding to the original data of the colon cancer liver metastasis accurate medication clinical tests,
taking the original data of the multiple colon cancer liver metastasis accurate medication clinical tests as training samples, taking corresponding result data sets as output labels, and constructing a training database;
and performing model training by adopting a deep learning algorithm based on the training database to obtain the natural language processing model.
5. The method for calculating the clinical data of the colon cancer liver metastasis accurate medication according to claim 4, wherein the model training using the deep learning algorithm comprises:
and carrying out entity recognition and naming on the original data, analyzing, semantically analyzing, marking and recombining by combining grammar to form a first result data set after recombination.
6. The method for calculating clinical data of colon cancer liver metastasis accurate medication according to claim 1, wherein the step S3 specifically comprises: and obtaining the directional demand data of the structured colon cancer liver metastasis accurate medication clinical test after matching with artificial correction according to the result data set.
7. A system for calculating accurate medication clinical data of liver metastasis of colon cancer comprises:
the acquisition module is used for acquiring and preprocessing original data of a colon cancer liver metastasis accurate medication clinical test;
the processing module is used for inputting the original data into a pre-trained natural language processing model to obtain a result data set;
and the output module is used for obtaining the directional demand data according to the result data set.
8. The system for calculating clinical data of colon cancer liver metastasis accurate medication as claimed in claim 7, wherein the raw data includes a data header and source data of clinical trial medical record, and a data identification field is set in the raw data for data duplication checking, data splicing or data volume expansion.
9. The system for accurately projecting clinical data on liver metastasis of colon cancer according to claim 7, wherein said preprocessing comprises data cleansing and data vectorization.
10. The system for accurately calculating clinical data of colon cancer liver metastasis as claimed in claim 7, wherein the process of constructing the natural language processing model in the processing module comprises:
obtaining a plurality of pieces of original data of colon cancer liver metastasis accurate medication clinical tests, determining a result data set corresponding to the original data of the colon cancer liver metastasis accurate medication clinical tests,
taking the original data of the multiple colon cancer liver metastasis accurate medication clinical tests as training samples, taking corresponding result data sets as output labels, and constructing a training database;
and performing model training by adopting a deep learning algorithm based on the training database to obtain the natural language processing model.
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| CN107145511A (en) * | 2017-03-31 | 2017-09-08 | 上海森亿医疗科技有限公司 | Structured medical data library generating method and system based on medical science text message |
| US20200251188A1 (en) * | 2019-02-05 | 2020-08-06 | International Business Machines Corporation | Identifying implied criteria in clinical trials using machine learning techniques |
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Application publication date: 20210427 |