CN117976116A - Intelligent analysis method for accelerating rehabilitation surgical data - Google Patents
Intelligent analysis method for accelerating rehabilitation surgical data Download PDFInfo
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Abstract
The invention provides an intelligent analysis method for accelerating rehabilitation surgical data, which comprises the following steps: s100, establishing a resident rehabilitation data database, and acquiring rehabilitation data analysis requirement sentences of a user; s200, carrying out SQL analysis on the rehabilitation data analysis requirement statement of the user to obtain a word assisting, an implicit query condition and a display query condition in the rehabilitation data analysis requirement statement of the user, and generating an SQL statement according to the word assisting, the implicit query condition and the display query condition; s300, executing recovery data query analysis of the user according to the SQL statement. The invention can realize convenient data filling and verification, can cover most projects which need to be filled by doctors through the basic database, and can remind the doctors through the verification of the upper limit and the lower limit. The invention can realize automatic analysis, and doctors can select items to be analyzed independently through the software page, thereby achieving the purpose of rapidness and convenience.
Description
Technical Field
The invention relates to the technical field of intelligent analysis scheme design of accelerated rehabilitation surgical data, in particular to an intelligent analysis method of accelerated rehabilitation surgical data.
Background
ERAS is regarded as the theory of surgical front, and is deeply paid attention to the world, in recent years, a plurality of hospitals in China begin to discuss ERAS, certain data are accumulated, scientific evaluation and research are carried out based on the existing data, the data are classified and compared, better conclusion can be obtained, and the development and improvement of ERAS are finally promoted.
The prior art can complete data analysis to a certain extent, but most of the prior art is limited to a single table, and cannot realize multi-dimension analysis.
Thus, the prior art is still to be further developed.
Disclosure of Invention
The invention aims to overcome the technical defects and provide an intelligent analysis method for accelerating rehabilitation surgical data so as to solve the problems in the prior art.
In order to achieve the technical aim, the invention provides an intelligent analysis method for accelerating rehabilitation surgical data, which comprises the following steps:
s100, establishing a resident rehabilitation data database, and acquiring rehabilitation data analysis requirement sentences of a user;
S200, carrying out SQL analysis on the rehabilitation data analysis requirement statement of the user to obtain a word assisting, an implicit query condition and a display query condition in the rehabilitation data analysis requirement statement of the user, and generating an SQL statement according to the word assisting, the implicit query condition and the display query condition;
S300, executing recovery data query analysis of the user according to the SQL statement.
Specifically, the establishing a recovery database of inpatients includes:
And acquiring rehabilitation data generated during inpatient hospitalization by using an information acquisition terminal arranged in the hospital, and transmitting the rehabilitation data generated during inpatient hospitalization to an inpatient rehabilitation data database.
Specifically, the manner in which the data generated during hospitalization of the resident person is injected into the standard database through each system includes at least one of the following:
a direct database butt joint mode; webService mode; restFul mode.
Specifically, the S100 further includes:
Creating a dictionary of terms and generating an erat filling template.
Specifically, the creating the entry dictionary and generating the erat filling template includes:
Creating a set of terms required for the ERAS study, wherein the terms required for the ERAS study comprise term names, data types and upper and lower data limits, and the set of terms required for the ERAS study is used for selecting according to requirements when a user generates an ERAS filling template.
Specifically, the S100 further includes:
Acquiring a set of terms selected according to analysis requirements of a user when the user generates an ERAS filling template, generating the ERAS filling template according to the set of terms selected according to analysis requirements of the user when the user generates the ERAS filling template, generating an electronic form according to the ERAS filling template, acquiring name information of required inpatients input by the user, retrieving recovery data of corresponding inpatients according to the name information of the required inpatients, and judging whether the recovery data of each term is normal according to the upper limit and the lower limit of the data corresponding to the term, and outputting a prompt signal related to whether the recovery data of the term prompting the corresponding inpatients is normal according to a judging result, building an ERAS database and storing the electronic form in the ERAS database.
Specifically, the S100 includes:
If the upper and lower limits of the data corresponding to the vocabulary entry are within the upper and lower limits of the data corresponding to the vocabulary entry, outputting a prompting signal related to prompting the normal rehabilitation data of the vocabulary entry of the corresponding resident.
Specifically, the S100 includes:
If the upper and lower limits of the data corresponding to the vocabulary entry are not within the upper and lower limits of the data corresponding to the vocabulary entry, a prompting signal related to abnormal rehabilitation data of the vocabulary entry prompting the corresponding resident is output.
Specifically, the S100 includes:
establishing a data analysis element database, and establishing an index for each ERAS data in an electronic form in the ERAS database, wherein the index contains field names and table names corresponding to each ERAS data and is used for later inquiry.
Specifically, the S100 includes:
Generating a word-assisting database, inputting verbs, word-assisting and nonsensical words in natural language into the word-assisting database and defining the verbs, the word-assisting and the nonsensical words, and performing SQL analysis on rehabilitation data analysis requirement sentences of the user.
The beneficial effects are that:
1. the invention provides a set of data collecting, screening and analyzing method, which is characterized in that data is classified, marked and screened to generate a data model, and finally a set of complete data comparison and analysis conclusion is provided for scientific researchers, and the scientific researchers can intuitively obtain an autonomous and intuitive result through a graph.
2. The invention completes data acquisition by integrating the information acquisition terminals in all hospitals, thereby reducing the filling amount of hospital staff and lightening the burden.
3. The invention provides a free template and verification: through the entry dictionary, a hospital administrator can freely set filling items and configure filling requirements, so that data filling is more flexible.
4. The invention provides a highly intelligent analysis system: the hospital staff can automatically complete analysis and research through a section of characters or select corresponding analysis items, so that the analysis speed is greatly improved.
Drawings
FIG. 1 is a flow chart of a method for intelligent analysis of accelerated rehabilitation surgical data provided in an embodiment of the present invention;
Fig. 2 is a block diagram of an intelligent analysis system for accelerated rehabilitation surgical data provided in an embodiment of the present invention.
Detailed Description
In order to make the technical solution of the present application better understood by those skilled in the art, the technical solution of the present application will be clearly and completely described in the following with reference to the accompanying drawings, and based on the embodiments of the present application, other similar embodiments obtained by those skilled in the art without making any inventive effort should be included in the scope of protection of the present application. In addition, directional words such as "upper", "lower", "left", "right", and the like, as used in the following embodiments are merely directions with reference to the drawings, and thus, the directional words used are intended to illustrate, not to limit, the application.
The invention will be further described with reference to the drawings and preferred embodiments.
Referring to fig. 1, the present invention provides an intelligent analysis method for accelerating rehabilitation surgical data, comprising:
S100, establishing a resident rehabilitation data database, and acquiring rehabilitation data analysis requirement sentences of the user.
Here, the function of S100 is to create a standard database, and inject data generated during patient hospitalization into the standard database through each system. The system is directly connected with the database or connected with the database in a webService mode or restFul mode.
S200, carrying out SQL analysis on the rehabilitation data analysis requirement statement of the user to obtain a word assisting, an implicit query condition and a display query condition in the rehabilitation data analysis requirement statement of the user, and generating an SQL statement according to the word assisting, the implicit query condition and the display query condition.
S300, executing recovery data query analysis of the user according to the SQL statement.
Specifically, the establishing a recovery database of inpatients includes:
And acquiring rehabilitation data generated during inpatient hospitalization by using an information acquisition terminal arranged in the hospital, and transmitting the rehabilitation data generated during inpatient hospitalization to an inpatient rehabilitation data database.
Specifically, the manner in which the data generated during hospitalization of the resident person is injected into the standard database through each system includes at least one of the following:
a direct database butt joint mode; webService mode; restFul mode.
Specifically, the S100 further includes:
Creating a dictionary of terms and generating an erat filling template.
Specifically, the creating the entry dictionary and generating the erat filling template includes:
Creating a set of terms required for the ERAS study, wherein the terms required for the ERAS study comprise term names, data types and upper and lower data limits, and the set of terms required for the ERAS study is used for selecting according to requirements when a user generates an ERAS filling template.
It should be noted here that the above steps are used to create a dictionary of terms, which is used by a hospital administrator to create the required terms of the erats, including name, data type, upper and lower data limits, for selection in generating the erats filling templates.
Specifically, the S100 further includes:
Acquiring a set of terms selected according to analysis requirements of a user when the user generates an ERAS filling template, generating the ERAS filling template according to the set of terms selected according to analysis requirements of the user when the user generates the ERAS filling template, generating an electronic form according to the ERAS filling template, acquiring name information of required inpatients input by the user, retrieving recovery data of corresponding inpatients according to the name information of the required inpatients, and judging whether the recovery data of each term is normal according to the upper limit and the lower limit of the data corresponding to the term, and outputting a prompt signal related to whether the recovery data of the term prompting the corresponding inpatients is normal according to a judging result, building an ERAS database and storing the electronic form in the ERAS database.
Specifically, the S100 includes:
If the upper and lower limits of the data corresponding to the vocabulary entry are within the upper and lower limits of the data corresponding to the vocabulary entry, outputting a prompting signal related to prompting the normal rehabilitation data of the vocabulary entry of the corresponding resident.
Specifically, the S100 further includes:
If the upper and lower limits of the data corresponding to the vocabulary entry are not within the upper and lower limits of the data corresponding to the vocabulary entry, a prompting signal related to abnormal rehabilitation data of the vocabulary entry prompting the corresponding resident is output.
It should be noted that, the above steps are used to create a data filling template, the hospital administrator selects the vocabulary entry required in the era study from the dictionary, and after the selection is completed, the system automatically generates the filling template and generates a form for the doctor nurse to fill in. The doctor selects the patient in the hospitalization list, enters a data filling page, can automatically introduce the data which accords with the corresponding entry in the standard database into the form by clicking and import, judges rationality through the upper limit and the lower limit of the form, reminds the doctor, and can not be imported and filled by the doctor, and the data is stored and then is put into the ERAS database.
It will be appreciated that hospital staff can perform the analysis in two ways: first kind: a section of text is entered. The hospital staff can input a section of analysis requirement, and the system automatically analyzes the analysis requirement into sql sentences. For example, doctor writes the following fields: the ratio of male and female patients of mastopathy department was analyzed for a period of time of 2020, 7 months, 3 days to 2020, 8 months, 20 days daily. First, the system will find the help words, "as" to, "daily," "and," "proportion," and "patient" in this sentence. Secondly, acquiring an explicit query condition, wherein the explicit query condition in a sentence is 'operation time', and thirdly, acquiring an implicit query condition: the first condition is "mastology", the database is analyzed by querying the data, resulting in the following search conditions [ data: RXBKHL-mastopathy department (general surgery department) (guard) [ field name: ward name [ table name: maindata, the second condition is "male", the following search conditions are obtained [ data: man [ field name: gender [ table name: maindata, the third condition is "female", similar to the second condition, and then the sql statement is obtained according to the meaning of the fluxing word and the retrieval condition. Finally, determining the retrieval conditions as follows: surgical time: 7.2020, 3.to 8.20.2020, ward name: RXBKHL-mastopathy department (general surgery department of nine disease areas) (care), sex: male and female, comparison conditions: gender, pattern: a bar graph. Meanwhile, if the hospital staff feel inaccurate, a second mode can be selected, and after the data analysis page selects the analyzed vocabulary entry, the graphic style, the search condition and the like, the system automatically generates a splicing sql and displays the splicing sql in the front-end page.
Specifically, the S100 includes:
establishing a data analysis element database, and establishing an index for each ERAS data in an electronic form in the ERAS database, wherein the index contains field names and table names corresponding to each ERAS data and is used for later inquiry.
It should be noted that, the above steps are used for creating a data analysis element database, and creating an index for the erat data, where the index includes a field name, a table name, etc. corresponding to the data, for later query.
Specifically, the S100 includes:
Generating a word-assisting database, inputting verbs, word-assisting and nonsensical words in natural language into the word-assisting database and defining the verbs, the word-assisting and the nonsensical words, and performing SQL analysis on rehabilitation data analysis requirement sentences of the user.
Here, the above steps are used to generate a word-assisting database, and the verbs, the word-assisting words, the nonsensical words, and the like in the natural language are filled, for example, words such as "to", and the like are put in a warehouse, and are defined to help understand the meaning of the words in the sentence and train.
The following illustrates the flow of the intelligent analysis method for accelerated rehabilitation surgical data according to the present invention:
1. a standard database is created into which data generated during patient hospitalization is injected through the various systems. The system can be directly docked through databases, webService, restFul and the like.
2. Creating a dictionary of terms, which is used by a hospital administrator to create the required terms of the erats, including name, data type, upper and lower data limits, for selection when generating the erats filling templates.
3. Creating a data filling template, wherein a hospital administrator selects an entry required in ERAS research in a dictionary, and after the selection is completed, the system automatically generates the filling template and generates a form for a doctor nurse to fill in.
4. The doctor selects the patient in the hospitalization list, enters a data filling page, can automatically introduce the data which accords with the corresponding entry in the standard database into the form by clicking and import, judges rationality through the upper limit and the lower limit of the form, reminds the doctor, and can not be imported and filled by the doctor, and the data is stored and then is put into the ERAS database.
5. And establishing a data analysis element database, and establishing an index for ERAS data, wherein the index comprises field names, table names and the like corresponding to the data and is used for later inquiry.
6. Generating a word-assisting database, filling verbs, word-assisting and word-nonsensical words and the like in natural language, e.g. "to", and the like, warehousing, defining, helping to understand the meaning of the word-assisting and word-nonsensical words in sentences and training.
7. Creating a data analysis template, hospital staff can complete the analysis in two ways: first kind: a section of text is entered. The hospital staff can input a section of analysis requirement, and the system automatically analyzes the analysis requirement into sql sentences. For example, doctor writes the following fields: the ratio of male and female patients of mastopathy department was analyzed for a period of time of 2020, 7 months, 3 days to 2020, 8 months, 20 days daily. First, the system will find the help words, "as" to, "daily," "and," "proportion," and "patient" in this sentence. Secondly, acquiring an explicit query condition, wherein the explicit query condition in a sentence is 'operation time', and thirdly, acquiring an implicit query condition: the first condition is "mastology", the database is analyzed by querying the data, resulting in the following search conditions [ data: RXBKHL-mastopathy department (general surgery department) (guard) [ field name: ward name [ table name: maindata, the second condition is "male", the following search conditions are obtained [ data: man [ field name: gender [ table name: maindata, the third condition is "female", similar to the second condition, and then the sql statement is obtained according to the meaning of the fluxing word and the retrieval condition. Finally, determining the retrieval conditions as follows: surgical time: 7.2020, 3.to 8.20.2020, ward name: RXBKHL-mastopathy department (general surgery department of nine disease areas) (care), sex: male and female, comparison conditions: gender, pattern: a bar graph. Meanwhile, if the hospital staff feel inaccurate, a second mode can be selected, and after the data analysis page selects the analyzed vocabulary entry, the graphic style, the search condition and the like, the system automatically generates a splicing sql and displays the splicing sql in the front-end page.
It can be understood that the invention provides a set of data collecting, screening and analyzing methods, and the data model is generated by classifying, labeling and screening the data, so that a complete set of data comparison and analysis conclusion is finally provided for scientific researchers, and the scientific researchers can intuitively obtain the result independently and intuitively through the graph.
The invention integrates the information acquisition terminals in all hospitals to complete data acquisition, thereby reducing the filling amount of hospital staff and lightening the burden.
It will be appreciated that the present invention provides a free template and verification: through the entry dictionary, a hospital administrator can freely set filling items and configure filling requirements, so that data filling is more flexible.
It should be noted here that the present invention provides a highly intelligent analysis system: the hospital staff can automatically complete analysis and research through a section of characters or select corresponding analysis items, so that the analysis speed is greatly improved.
It can be understood that the data of each system of the hospital is standardized through the standard database and stored in the basic database for calling. The invention has selectable templates, and a hospital administrator can configure and fill out templates by selecting configured vocabulary entry dictionaries. The invention can realize convenient data filling and verification, can cover most projects which need to be filled by doctors through the basic database, and can remind the doctors through the verification of the upper limit and the lower limit. The invention can realize automatic analysis, and doctors can select items to be analyzed independently through the software page, thereby achieving the purpose of rapidness and convenience.
Referring to fig. 2, another embodiment of the present invention provides an intelligent analysis system for accelerating rehabilitation surgical data, which includes:
an obtaining module 100, configured to obtain a rehabilitation data analysis requirement statement of a user;
The control module 200 is used for establishing a recovery database of inpatients; or performing SQL analysis on the rehabilitation data analysis requirement statement of the user to obtain a word assisting, an implicit query condition and a display query condition in the rehabilitation data analysis requirement statement of the user, and generating an SQL statement according to the word assisting, the implicit query condition and the display query condition; or for performing a user's recovery data query analysis from an SQL statement.
It can be understood that the invention provides a set of data collecting, screening and analyzing methods, and the data model is generated by classifying, labeling and screening the data, so that a complete set of data comparison and analysis conclusion is finally provided for scientific researchers, and the scientific researchers can intuitively obtain the result independently and intuitively through the graph.
The invention integrates the information acquisition terminals in all hospitals to complete data acquisition, thereby reducing the filling amount of hospital staff and lightening the burden.
It will be appreciated that the present invention provides a free template and verification: through the entry dictionary, a hospital administrator can freely set filling items and configure filling requirements, so that data filling is more flexible.
It should be noted here that the present invention provides a highly intelligent analysis system: the hospital staff can automatically complete analysis and research through a section of characters or select corresponding analysis items, so that the analysis speed is greatly improved.
It can be understood that the data of each system of the hospital is standardized through the standard database and stored in the basic database for calling. The invention has selectable templates, and a hospital administrator can configure and fill out templates by selecting configured vocabulary entry dictionaries. The invention can realize convenient data filling and verification, can cover most projects which need to be filled by doctors through the basic database, and can remind the doctors through the verification of the upper limit and the lower limit. The invention can realize automatic analysis, and doctors can select items to be analyzed independently through the software page, thereby achieving the purpose of rapidness and convenience.
In a preferred embodiment, the present application also provides an electronic device, including:
a memory; and the processor is used for storing computer readable instructions on the memory, and the computer readable instructions realize the intelligent analysis method of the accelerated rehabilitation surgical data when being executed by the processor. The computer device may be broadly a server, a terminal, or any other electronic device having the necessary computing and/or processing capabilities. In one embodiment, the computer device may include a processor, memory, network interface, communication interface, etc. connected by a system bus. The processor of the computer device may be used to provide the necessary computing, processing and/or control capabilities. The memory of the computer device may include a non-volatile storage medium and an internal memory. The non-volatile storage medium may have an operating system, computer programs, etc. stored therein or thereon. The internal memory may provide an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface and communication interface of the computer device may be used to connect and communicate with external devices via a network. Which when executed by a processor performs the steps of the method of the invention.
The present invention may be implemented as a computer readable storage medium having stored thereon a computer program which, when executed by a processor, causes steps of a method of an embodiment of the present invention to be performed. In one embodiment, the computer program is distributed over a plurality of computer devices or processors coupled by a network such that the computer program is stored, accessed, and executed by one or more computer devices or processors in a distributed fashion. A single method step/operation, or two or more method steps/operations, may be performed by a single computer device or processor, or by two or more computer devices or processors. One or more method steps/operations may be performed by one or more computer devices or processors, and one or more other method steps/operations may be performed by one or more other computer devices or processors. One or more computer devices or processors may perform a single method step/operation or two or more method steps/operations.
Those of ordinary skill in the art will appreciate that the method steps of the present invention may be implemented by a computer program, which may be stored on a non-transitory computer readable storage medium, to instruct related hardware such as a computer device or a processor, which when executed causes the steps of the present invention to be performed. Any reference herein to memory, storage, database, or other medium may include non-volatile and/or volatile memory, as the case may be. Examples of nonvolatile memory include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), flash memory, magnetic tape, floppy disk, magneto-optical data storage, hard disk, solid state disk, and the like. Examples of volatile memory include Random Access Memory (RAM), external cache memory, and the like.
It can be understood that the invention provides a set of data collecting, screening and analyzing methods, and the data model is generated by classifying, labeling and screening the data, so that a complete set of data comparison and analysis conclusion is finally provided for scientific researchers, and the scientific researchers can intuitively obtain the result independently and intuitively through the graph.
The invention integrates the information acquisition terminals in all hospitals to complete data acquisition, thereby reducing the filling amount of hospital staff and lightening the burden.
It will be appreciated that the present invention provides a free template and verification: through the entry dictionary, a hospital administrator can freely set filling items and configure filling requirements, so that data filling is more flexible.
It should be noted here that the present invention provides a highly intelligent analysis system: the hospital staff can automatically complete analysis and research through a section of characters or select corresponding analysis items, so that the analysis speed is greatly improved.
It can be understood that the data of each system of the hospital is standardized through the standard database and stored in the basic database for calling. The invention has selectable templates, and a hospital administrator can configure and fill out templates by selecting configured vocabulary entry dictionaries. The invention can realize convenient data filling and verification, can cover most projects which need to be filled by doctors through the basic database, and can remind the doctors through the verification of the upper limit and the lower limit. The invention can realize automatic analysis, and doctors can select items to be analyzed independently through the software page, thereby achieving the purpose of rapidness and convenience.
The technical features described above may be arbitrarily combined. Although not all possible combinations of features are described, any combination of features should be considered to be covered by the description provided that such combinations are not inconsistent.
The above-described embodiments of the present invention do not limit the scope of the present invention. Any other corresponding changes and modifications made in accordance with the technical idea of the present invention shall be included in the scope of the claims of the present invention.
Claims (10)
1. An intelligent analysis method for accelerating rehabilitation surgical data, which is characterized by comprising the following steps:
s100, establishing a resident rehabilitation data database, and acquiring rehabilitation data analysis requirement sentences of a user;
S200, carrying out SQL analysis on the rehabilitation data analysis requirement statement of the user to obtain a word assisting, an implicit query condition and a display query condition in the rehabilitation data analysis requirement statement of the user, and generating an SQL statement according to the word assisting, the implicit query condition and the display query condition;
S300, executing recovery data query analysis of the user according to the SQL statement.
2. The method for intelligent analysis of accelerated recovery surgical data of claim 1, wherein said creating a resident recovery data database comprises:
And acquiring rehabilitation data generated during inpatient hospitalization by using an information acquisition terminal arranged in the hospital, and transmitting the rehabilitation data generated during inpatient hospitalization to an inpatient rehabilitation data database.
3. The method of intelligent analysis of accelerated rehabilitation surgical data according to claim 2, wherein the means for injecting data generated during hospitalization of the resident person into the standard database through the respective systems comprises at least one of:
a direct database butt joint mode; webService mode; restFul mode.
4. The accelerated recovery surgical data intelligent analysis method of claim 1, wherein S100 further comprises:
Creating a dictionary of terms and generating an erat filling template.
5. The method of intelligent analysis of accelerated rehabilitation surgical data of claim 4 wherein creating a dictionary of terms and generating an era filling template comprises:
Creating a set of terms required for the ERAS study, wherein the terms required for the ERAS study comprise term names, data types and upper and lower data limits, and the set of terms required for the ERAS study is used for selecting according to requirements when a user generates an ERAS filling template.
6. The accelerated recovery surgical data intelligent analysis method of claim 5, wherein S100 further comprises:
Acquiring a set of terms selected according to analysis requirements of a user when the user generates an ERAS filling template, generating the ERAS filling template according to the set of terms selected according to analysis requirements of the user when the user generates the ERAS filling template, generating an electronic form according to the ERAS filling template, acquiring name information of required inpatients input by the user, retrieving recovery data of corresponding inpatients according to the name information of the required inpatients, and judging whether the recovery data of each term is normal according to the upper limit and the lower limit of the data corresponding to the term, and outputting a prompt signal related to whether the recovery data of the term prompting the corresponding inpatients is normal according to a judging result, building an ERAS database and storing the electronic form in the ERAS database.
7. The accelerated recovery surgical data intelligent analysis method of claim 6, wherein S100 comprises:
If the upper and lower limits of the data corresponding to the vocabulary entry are within the upper and lower limits of the data corresponding to the vocabulary entry, outputting a prompting signal related to prompting the normal rehabilitation data of the vocabulary entry of the corresponding resident.
8. The accelerated recovery surgical data intelligent analysis method of claim 6, wherein S100 comprises:
If the upper and lower limits of the data corresponding to the vocabulary entry are not within the upper and lower limits of the data corresponding to the vocabulary entry, a prompting signal related to abnormal rehabilitation data of the vocabulary entry prompting the corresponding resident is output.
9. The accelerated recovery surgical data intelligent analysis method of claim 6, wherein S100 comprises:
establishing a data analysis element database, and establishing an index for each ERAS data in an electronic form in the ERAS database, wherein the index contains field names and table names corresponding to each ERAS data and is used for later inquiry.
10. The accelerated rehabilitation surgical data intelligent analysis method of claim 1, wherein S100 comprises:
Generating a word-assisting database, inputting verbs, word-assisting and nonsensical words in natural language into the word-assisting database and defining the verbs, the word-assisting and the nonsensical words, and performing SQL analysis on rehabilitation data analysis requirement sentences of the user.
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