CN110517787A - A kind of clinical data group classification method based on Chinese medical main suit's analysis - Google Patents
A kind of clinical data group classification method based on Chinese medical main suit's analysis Download PDFInfo
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Abstract
The present invention is more particularly directed to a kind of clinical data group classification methods based on Chinese medical main suit's analysis.The clinical data group classification method based on Chinese medical main suit's analysis carries out analysis mining using data group of the machine learning algorithm to the main suit composition of various clinical examinations inspection data and doctor's typing, obtains information and knowledge that data group implies；It is analyzed and processed according to the data source that hospital information system provides, obtains the data classification of data group；By the corresponding data category in data group deposit clinical data center relevant knowledge library.The clinical data group classification method based on Chinese medical main suit's analysis, data model is established by using machine learning related algorithm, the data group of the main suit composition of data and doctor's typing, which carries out analysis mining, to be checked to various clinical examinations, realize the exact classification to data group, the working efficiency of doctor can not only be greatly improved, is also of great significance to small-sized, miniature clinical data center in building institute.
Description
Technical field
It is the present invention relates to machine learning algorithm and data mining technology field, in particular to a kind of based on the medical main suit of Chinese
The clinical data group classification method of analysis.
Background technique
The different brackets of different hospital, hospital, the level of informatization is irregular in institute, in the not high doctor of the level of informatization
Inside institute, each operation system is there are data silo, in institute between each system, between Hospitals in Region and hospital, and hospital and society
Can there be different degrees of data barrier between the public.
With the continuous development of big data technology, under the dual promotion of policy and technology, hospital has strong wish to disappear
Except internal data barrier, miniature, small hospital's clinical data center is established, to the interconnecting of data, the scientific research of doctor needs
It asks, the Diseases diagnosis in institute, reduce doctor's misdiagnosis rate etc. and will have important meaning.
Doctor needs the auxiliary of many relevant informations in diagnosis and treatment process, and most important information source is the various of patient
Clinical examination checks the data group of data composition.These examine detection datas composition data group, be imported into disease database it
Afterwards, it is capable of forming the support of disease aid decision, guidance is further formed to the work of doctor, so that accurate judgement disease, provides
Diagnosis and treatment scheme reduces technical fault.Therefore, if data model can be established, data composition is checked to various clinical examinations
Data group carries out analysis mining, realizes the exact classification to data group, it will the working efficiency for greatly improving doctor, to building institute
Interior small-sized, miniature clinical data center is of great significance.
Based on the above situation, the invention proposes a kind of clinical data group classification sides based on Chinese medical main suit's analysis
Method.
Summary of the invention
In order to compensate for the shortcomings of the prior art, the present invention provides it is a kind of be simple and efficient analyzed based on Chinese medical main suit
Clinical data group classification method.
The present invention is achieved through the following technical solutions:
A kind of clinical data group classification method based on Chinese medical main suit's analysis, it is characterised in that: the following steps are included:
The first step is formed using main suit of the machine learning algorithm to various clinical examinations inspection data and doctor's typing
Data group carries out analysis mining, obtains information and knowledge that data group implies；
Second step, the data source provided according to hospital information system carry out at analysis the main suit content of doctor's typing
Reason obtains the data classification of data group in conjunction with information and knowledge that the data group got implies；
Third step, by the corresponding data category in data group deposit clinical data center relevant knowledge library.
In the first step, it is described using machine learning algorithm to various clinical examinations check data composition data group into
Row analysis mining, including Chinese text pretreatment, feature extraction, data modeling and Knowledge Discovery.
The Chinese text pretreatment includes text data cleaning, word segmentation and data mapping.
The data cleansing refers to processing missing data and exceptional value, and weeds out unrelated with data modeling in initial data
Data.
The word segmentation, which refers to, checks that data and doctor are recorded for various clinical examinations using the customized dictionary for word segmentation of user
The main suit entered segments respectively；The customized dictionary for word segmentation of user uses main suit's relevant medical dictionary, and cuts in word
Timesharing load uses.
The data mapping refers to building inspection and data classification Standard Map table, and using Standard Map table respectively to each
Kind clinical examination checks that the main suit of data and doctor's typing is standardized.Example: hypertension three-level (XXX) is mapped as height
Blood pressure three-level.
The feature extraction includes following two parts:
First, load user's Custom Dictionaries segment the main suit content of doctor's typing, after being converted to term vector
After extracting main suit's Feature Words, code conversion is carried out to main suit's Feature Words；
Second, data, which carry out cutting, to be checked to various clinical examinations using additional character, filters out the character without Chinese
, and data, which are standardized, to be checked to various clinical examinations respectively using Standard Map table；Then load user makes by oneself
Various clinical examinations after standardization are checked that data segment by adopted dictionary, extract clinical examination after being converted to term vector
It checks data characteristics word, data characteristics word, which carries out code conversion, then to be checked to clinical examination.
The data modeling refer to the main suit's content and various clinical examinations that have carried out code conversion check data into
Row modeling；After data modeling, it is original set that the result of data model output, which is carried out code conversion again, to construct main suit
Content, various clinical examinations check the regulation engine between data and data classification.
In the third step, the corresponding data category in the clinical data center relevant knowledge library includes disease category and inspection
Look into classification.
The beneficial effects of the present invention are: should be based on the clinical data group classification method of Chinese medical main suit's analysis, by making
Data model is established with machine learning related algorithm, the main suit composition of data and doctor's typing is checked to various clinical examinations
Data group carries out analysis mining, realizes the exact classification to data group, can not only greatly improve the working efficiency of doctor, also
It is of great significance to small-sized, miniature clinical data center in building institute.
Specific embodiment
In order to which technical problems, technical solutions and advantages to be solved are more clearly understood, tie below
Embodiment is closed, the present invention will be described in detail.It should be noted that specific embodiment described herein is only to explain
The present invention is not intended to limit the present invention.
The clinical data group classification method based on Chinese medical main suit's analysis, comprising the following steps:
The first step is formed using main suit of the machine learning algorithm to various clinical examinations inspection data and doctor's typing
Data group carries out analysis mining, obtains information and knowledge that data group implies；
Second step, the data source provided according to hospital information system carry out at analysis the main suit content of doctor's typing
Reason obtains the data classification of data group in conjunction with information and knowledge that the data group got implies；
Third step, by the corresponding data category in data group deposit clinical data center relevant knowledge library.
The data source that the hospital information system provides comes from hospital HIS (Hospital Information System)
System.HIS is the information management system for covering hospital all business and business overall process, is a kind of living in hospital management and medical treatment
The computer application system of information management and on-line operation, english abbreviation HIS are carried out in dynamic.
Hospital HIS system includes following components:
(1) clinic diagnosis part: doctor workstation, nursing station, clinic information system (Clinical
Information System, CIS), radiological information system (Radiology Information System, RIS), experiment
Room information system (Laboratory Information System, LIS) medical image information system PACS (Picture
Archiving and Communication Systems), blood transfusion and blood bank management system, surgery anesthesia management system；
(2) drug control part: data preparation and drug dictionary, drug store management function, outpatients pharmacy manage function
Energy, dispensary for inpatients management function, drug calculate function, Drug price control, preparation management subsystem, rational use of medicines consulting function
Energy；
(3) economic management part: Emergency call hospital registration system, pricing and fees for outpatients and ER department system, inpatient enters, goes out, tube
Reason system, patient's cost of hospitalization system, material Management System, the equipment management subsystem, financial management and business accounting management system
System；
(4) integrated management and statistical analysis part: health record management system, Medical Statistical System, president's inquiry are with analysis
System, patient's consultative service system；
(5) external interface part: medical insurance interface, urban community health services interface, remote medical consultation system interface.
In the first step, it is described using machine learning algorithm to various clinical examinations check data composition data group into
Row analysis mining, including Chinese text pretreatment, feature extraction, data modeling and Knowledge Discovery.
The Chinese text pretreatment includes text data cleaning, word segmentation and data mapping.
The data cleansing refers to processing missing data and exceptional value, and weeds out unrelated with data modeling in initial data
Data.
The word segmentation, which refers to, checks that data and doctor are recorded for various clinical examinations using the customized dictionary for word segmentation of user
The main suit entered segments respectively；The customized dictionary for word segmentation of user uses main suit's relevant medical dictionary, and cuts in word
Timesharing load uses.
The data mapping refers to building inspection and data classification Standard Map table, and using Standard Map table respectively to each
Kind clinical examination checks that the main suit of data and doctor's typing is standardized.Example: hypertension three-level (XXX) is mapped as height
Blood pressure three-level.
The feature extraction includes following two parts:
First, load user's Custom Dictionaries segment the main suit content of doctor's typing, after being converted to term vector
After extracting main suit's Feature Words, code conversion is carried out to main suit's Feature Words；
Second, data, which carry out cutting, to be checked to various clinical examinations using additional character, filters out the character without Chinese
, and data, which are standardized, to be checked to various clinical examinations respectively using Standard Map table；Then load user makes by oneself
Various clinical examinations after standardization are checked that data segment by adopted dictionary, extract clinical examination after being converted to term vector
It checks data characteristics word, data characteristics word, which carries out code conversion, then to be checked to clinical examination.
The data modeling refer to the main suit's content and various clinical examinations that have carried out code conversion check data into
Row modeling；After data modeling, it is original set that the result of data model output, which is carried out code conversion again, to construct main suit
Content, various clinical examinations check the regulation engine between data and data classification.
In the third step, the corresponding data category in the clinical data center relevant knowledge library includes disease category and inspection
Look into classification.
Compared with prior art, there should be following spy based on the clinical data group classification method of Chinese medical main suit's analysis
Point:
1, using dependency rules engines such as machine learning related algorithm building diagnosis.
2, by checking that data carry out mining analysis to the various clinical examinations in hospital information system, the data institute is obtained
Implicit information and knowledge, and main suit's content of doctor's typing can be analyzed and processed obtain corresponding disease category and
It checks classification, and is automatically credited corresponding classification, to build small-sized, miniature clinical data center in institute.
Embodiment described above, only one kind of the specific embodiment of the invention, those skilled in the art is in this hair
The usual variations and alternatives carried out in bright technical proposal scope should be all included within the scope of the present invention.
Claims (9)
1. a kind of clinical data group classification method based on Chinese medical main suit's analysis, which comprises the following steps:
The first step checks various clinical examinations the data of the main suit composition of data and doctor's typing using machine learning algorithm
Group carries out analysis mining, obtains information and knowledge that data group implies；
Second step, the data source provided according to hospital information system are analyzed and processed the main suit content of doctor's typing, tie
The data group got implicit information and knowledge are closed, the data classification of data group is obtained；
Third step, by the corresponding data category in data group deposit clinical data center relevant knowledge library.
2. the clinical data group classification method according to claim 1 based on Chinese medical main suit's analysis, it is characterised in that:
It is described that the data group of data composition, which carries out analysis digging, to be checked to various clinical examinations using machine learning algorithm in the first step
Pick, including Chinese text pretreatment, feature extraction, data modeling and Knowledge Discovery.
3. the clinical data group classification method according to claim 2 based on Chinese medical main suit's analysis, it is characterised in that:
The Chinese text pretreatment includes text data cleaning, word segmentation and data mapping.
4. the clinical data group classification method according to claim 3 based on Chinese medical main suit's analysis, it is characterised in that:
The data cleansing refers to processing missing data and exceptional value, and weeds out data unrelated with data modeling in initial data.
5. the clinical data group classification method according to claim 3 based on Chinese medical main suit's analysis, it is characterised in that:
The word segmentation refers to the main suit that various clinical examinations are checked to data and doctor's typing using the customized dictionary for word segmentation of user
Item is segmented respectively；The customized dictionary for word segmentation of user uses main suit's relevant medical dictionary, and loads in word segmentation
It uses.
6. the clinical data group classification method according to claim 3 based on Chinese medical main suit's analysis, it is characterised in that:
The data mapping refers to building inspection and data classification Standard Map table, and is examined respectively to various clinics using Standard Map table
It tests and checks that the main suit of data and doctor's typing is standardized.
7. the clinical data group classification method according to claim 2 based on Chinese medical main suit's analysis, it is characterised in that:
The feature extraction includes following two parts:
First, load user's Custom Dictionaries segment the main suit content of doctor's typing, extract after being converted to term vector
After main suit's Feature Words, code conversion is carried out to main suit's Feature Words；
Second, second, data, which carry out cutting, to be checked to various clinical examinations using additional character, filters out the character without Chinese
, and data, which are standardized, to be checked to various clinical examinations respectively using Standard Map table；Then load user makes by oneself
Various clinical examinations after standardization are checked that data segment by adopted dictionary, extract clinical examination after being converted to term vector
It checks data characteristics word, data characteristics word, which carries out code conversion, then to be checked to clinical examination.
8. the clinical data group classification method according to claim 2 based on Chinese medical main suit's analysis, it is characterised in that:
The data modeling, which refers to, checks that data model to the main suit content and various clinical examinations that have carried out code conversion；Number
After modeling, it is original set that the result of data model output, which is carried out code conversion again, to construct main suit's content, various
Clinical examination checks the regulation engine between data and data classification.
9. the clinical data group classification method according to claim 1 based on Chinese medical main suit's analysis, it is characterised in that:
In the third step, the corresponding data category in the clinical data center relevant knowledge library includes disease category and checks classification.
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