CN114822880A - Hospital diagnosis and treatment information system based on domestic autonomous control - Google Patents
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Abstract
The invention provides a domestic-based autonomous controllable hospital diagnosis and treatment information system, which belongs to the technical field of internet diagnosis and treatment systems and specifically comprises the following steps: the system comprises a browser, a web server, a standardized management database and a network storage module; the browser requests and responds to the bidirectional connection of the web server; the web server reads data, writes the data into the standardized management database, is in bidirectional connection with the standardized management database, stores the data into the network storage module, analyzes the data in different analysis modes according to different file types of the data to obtain an analysis result, performs data interaction and fusion by taking a case as a center based on the analysis result to obtain a fusion result, and provides a suggestion for treatment of the case according to the fusion result; the network storage module adopts a domestic autonomous structure and is used for storing the data; the standardized management database comprises all database resources of the hospital, so that information interaction and fusion among different databases are better realized.
Description
Technical Field
The invention belongs to the technical field of internet diagnosis and treatment systems, and particularly relates to a domestic-made autonomous-controllable hospital diagnosis and treatment information system.
Background
In recent years, with the rapid development of scientific technology, the informatization construction of hospitals is gradually improved. But also exposes some problems in the development of hospital informatization, such as the increasing demand of the hospital business system on information sharing and business integration, and the traditional information architecture mode is difficult to meet the demand of patients and medical staff on data interaction. Under traditional hospital information-based development mode, the hospital needs to continuously carry out capital investment and then upgrade and reform original systems in order to meet the data sharing requirements of the systems, and meanwhile, system manufacturers need to continuously update own systems and need to bear the risks and burdens of other system accesses, and the defects are obvious. The stable operation of daily work of a hospital is the result of the cooperative work of a plurality of information systems, and the information systems are responsible for the work of different fields of the hospital and are mutually related by different labor division, so that the integration of the information systems becomes very important for improving the work efficiency and the information sharing degree of the information systems of the hospital.
The author xuliang in the master thesis "research and implementation of hospital information integration system based on semantic Web services" uses ontology technology to solve the semantic heterogeneous problem in medical system integration. Firstly, a medical ontology construction scheme is designed, extraction rules of semantic models of relational database ontologies are researched from multiple aspects, secondly, a medical ontology model is extracted from a relational database, and a local medical ontology is constructed, so that medical information can be circulated and fused mutually, but only the relational database is considered for extracting the ontology model, a large amount of non-relational database storage data including image data, XML files and the like exist in different detection equipment in a hospital, for each patient, if the image detection result cannot be analyzed, information fusion processing is carried out according to the detection result, the final data utilization rate is low, and the medical information cannot be well communicated and fused. Meanwhile, in order to meet the requirement of domestic substitution, a large number of domestic devices of different types are deployed in hospitals, the database storage mode and the database storage method of the domestic devices are also compatible to a certain extent, and medical information cannot be fused and communicated well due to information among different data.
The problems of the prior art are thought: the image data and the XML file are not analyzed, the compatibility of a database of domestic equipment and the existing database is poor, and medical information cannot be fused and communicated well.
Based on the technical problems, a hospital diagnosis and treatment information system based on domestic autonomous control needs to be designed.
Disclosure of Invention
The invention aims to provide a hospital diagnosis and treatment information system based on domestic autonomous control.
In order to solve the technical problems, the invention provides a home-made autonomous controllable hospital diagnosis and treatment information system, which is characterized by comprising:
the system comprises a browser, a web server, a standardized management database and a network storage module;
the browser requests and responds to connect the web server in a bidirectional mode;
the web server reads data, writes the data into the standardized management database in a bidirectional connection manner, stores the data into the network storage module, analyzes the data in different analysis manners according to different file types of the data to obtain analysis results, performs interaction and fusion on the data by taking a case as a center based on the analysis results to obtain fusion results, and provides suggestions for treatment of the case according to the fusion results;
the network storage module adopts a domestic autonomous structure and is used for storing the data;
the standardized management database includes all database resources of the hospital.
Reading and writing of data of the standardized management database is realized by adopting a web server, and storing the data in a network storage module, wherein the data in the network storage module comprises XML files, text files, picture files, sound files and video files, different parsing modes are adopted to parse according to different file types to obtain parsing results, so that parsing of image data and XML files is realized, meanwhile, the problem of poor compatibility between a database of domestic equipment and the existing database is solved, the interaction and fusion of the data are carried out by taking a case as a center based on the analysis result to obtain a fusion result, and provides suggestions for the treatment of cases according to the fusion result, realizes the interaction and fusion of data, and can realize the control of the treatment process of the case according to the fusion result, and provide suggestions for the later specific treatment.
The browser is adopted to request or correspond the web server, so that the content of the server can be conveniently inquired, the overall access and control difficulty is greatly simplified, the web server stores the data in the network storage module, the data in the network storage module comprises XML files, text files, picture files, sound files and video files, different analysis modes are adopted to analyze according to different file types to obtain analysis results, so that resources in different databases can be fully utilized, the problem that information cannot be fused and interacted with other databases due to poor compatibility of a newly added database is solved, the problem that the compatibility of a database of domestic equipment and the existing database is poor is solved, and the interaction and fusion of the data are carried out by taking a case as a center based on the analysis results to obtain fusion results, and provide the suggestion for the treatment of case according to the result of said fusion, through obtaining the result of fusion with the case center, realize the interaction between different databases, while carrying on the particular inspection or treatment, the medical personnel can be according to the results of other databases, and integral result of fusion, better grasp the key point, can judge according to the historical situation while treating too, make the integral diagnosis result become more reliable. The network storage module adopts a domestic autonomous structure, so that the domestic requirements can be met, and the storage and the keeping of user information become more reliable.
The further technical scheme is that the web server also comprises a function service subsystem, a platform subsystem and a user subsystem;
the functional service subsystem comprises an appointment module, an inquiry module, an intelligent message reminding module, a database data processing module, an auxiliary API module and a payment module;
the user subsystem is used for creating accounts for users and medical institutions, managing roles to which the users belong and distributing corresponding authorities and module functions;
the platform subsystem is used for establishing communication between the reservation module, the inquiry module, the intelligent message reminding module, the auxiliary API module, the payment module and the database data processing module and the user subsystem.
The further technical scheme is that the domestic autonomous structure adopts a domestic database system based on a distributed architecture, and a hardware circuit adopts a domestic chip.
By adopting the server based on the distributed architecture, the data is deployed in a cluster formed by a plurality of machines, so that when one or more machines are damaged, the service is ensured not to be interfered by a backup mechanism among the machines, and meanwhile, a home-made database system and a home-made chip are adopted, so that the data is stored more safely and reliably in the field of software management and in addition, the hardware part is adopted.
The further technical scheme is that the appointment module is used for appointing the inquiry time to the medical institution by the user;
the inquiry module is used for establishing communication between the user and the medical institution through the platform subsystem within the inquiry time, and performing on-line inquiry to obtain an electronic medical record and a medicine list;
the intelligent message reminding module is used for carrying out information communication among a plurality of clients and releasing system messages and notifications;
the auxiliary API module is used for realizing data interaction between the third-party equipment and the hospital diagnosis and treatment information system and function expansion of the third-party equipment; the database data processing module is used for carrying out data analysis, data storage and reading on the hospital diagnosis and treatment information in the network storage module;
and the payment module is used for acquiring the online medical insurance of the user and performing inquiry and settlement to the medical institution through the medical insurance.
The further technical scheme is that the specific steps for analyzing the XML file are as follows:
s1, realizing the query of the XML element of the XML file based on the document object model to obtain a query result;
s2, constructing a character string database according to an expert algorithm, sending the query result into the character string database for comparison, and extracting keywords;
and S3, expressing the content of the XML file by taking the keywords as an XML analysis result.
The XML elements of the XML files are inquired by adopting a document object-based model, and the character string database matching result is constructed according to the expert algorithm to obtain the final analysis result, so that the XML files in the hospital information system are not in a deep sleep state, the information of the XML files can be shared with other servers, meanwhile, due to the stability and the specialty of the medical expression character strings, the character string library is constructed by adopting the expert algorithm, the final analysis result can be more stable and reliable, the efficiency is higher, the final analysis result cannot be determined and duplicate removed for different medical expressions by adopting a method based on a machine learning algorithm, and the efficiency is lower.
The further technical scheme is that the specific steps for analyzing the picture file are as follows:
s11, extracting keywords by adopting an LDA algorithm based on the diagnosis and treatment opinion files of the cases of the picture files to obtain LDA keywords, extracting the keywords of the diagnosis and treatment opinion files according to a TF-IDF algorithm to obtain TF-IDF keywords, and fusing and de-duplicating the LDA keywords and the TF-IDF keywords to finally obtain keywords;
s12: performing dimensionality reduction processing on the basis of the keywords to obtain dimensionality reduction image keywords, and sending the dimensionality reduction image keywords into an SVM (support vector machine) prediction model improved on the basis of a bat algorithm to predict and obtain the disease type at the moment;
s13, processing the picture file to obtain the image characteristic, determining the image key word according to the image characteristic and the disease type by adopting the prediction model of the CNN algorithm, and expressing the image by taking the image key word as the image analysis result.
The method comprises the steps of extracting keywords by adopting an LDA algorithm based on a diagnosis and treatment opinion file to obtain LDA keywords, extracting the keywords of the diagnosis and treatment opinion file according to a TF-IDF algorithm to obtain TF-IDF keywords, fusing and de-duplicating the LDA keywords and the TF-IDF keywords to obtain the keywords finally, wherein the TF-IDF algorithm tends to filter common words and retain important words, the judgment result depends on the structure of the IDF, only the word frequency and the position of the keywords are considered, the rarely-used words in the medicine are mistaken for the keywords, the LDA algorithm introduces the priors of dirichlet theme distribution and word distribution, the method is a non-supervised machine learning technology, the keywords can be identified more accurately, but the sequence of the keywords is not considered, so the two algorithms are combined, the final keyword identification effect becomes more accurate, and performing dimensionality reduction on the keywords to obtain dimensionality reduction key image keywords, wherein the keywords are more and need to be further subjected to dimensionality reduction to improve the final prediction speed, the dimensionality reduction image keywords are sent to an SVM prediction model improved based on a bat algorithm, and SVM classification results are optimized through the bat algorithm to obtain more accurate classification results, so that the disease type is accurately determined.
The further technical scheme is that the concrete steps for analyzing the text file are as follows:
s11, extracting keywords of the character file by adopting an LDA algorithm to obtain LDA keywords, extracting the keywords of the diagnosis and treatment opinion file according to a TF-IDF algorithm to obtain TF-IDF keywords, and performing fusion de-duplication processing on the LDA keywords and the TF-IDF keywords to finally obtain character keywords;
s12: performing dimensionality reduction processing on the basis of the character keywords to obtain dimensionality reduction character keywords, and sending the dimensionality reduction character keywords to an SVM (support vector machine) prediction model improved on the basis of a bat algorithm to predict and obtain the disease type at the moment;
and S13, expressing the text file by taking the disease type and the text keywords as text analysis results.
The further technical scheme is that after the dimensionality reduction processing algorithm adopts a principal component analysis method based on PCA to obtain dimensionality reduction character keywords or dimensionality reduction image keywords, the de-coincidence of the dimensionality reduction character keywords or the dimensionality reduction image keywords is realized and the final dimensionality reduction character keywords or the dimensionality reduction image keywords are obtained through processing by further a character string database based on an expert algorithm.
The character string database based on the expert algorithm is used for carrying out de-duplication processing on the data subjected to the dimensionality reduction processing, and the de-duplication processing is carried out on the keywords which are different in name but consistent in meaning in certain medicine, so that the prediction efficiency can be further improved.
The further technical scheme is that information interaction is carried out on different analysis results among different standardized management databases by adopting an enterprise service bus technology, and the different analysis results are fused to form a final fusion result.
The technical scheme is that when a doctor treats the case, keywords are input through the browser according to the specific condition of the case or the keyword is matched with the fusion result of the historical case according to the analysis result, so that a suggestion is provided for the doctor to treat.
According to the analysis result or the keywords determined by the doctor, the historical case fusion result is matched, so that the historical case can be queried in a simple and effective mode, and suggestions are provided for the doctor to further treat according to the query result, so that the judgment result is more accurate, and the treatment effect is better.
Additional features and advantages will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.
Fig. 1 is a configuration diagram of a home-made autonomous controlled hospital medical information system according to embodiment 1.
Fig. 2 is a flowchart of the specific steps of XML file parsing in embodiment 1.
Fig. 3 is a flowchart of specific steps of picture file parsing in embodiment 1.
Fig. 4 is a flowchart showing the specific steps of parsing a text file in embodiment 1.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and thus their detailed description will be omitted.
The terms "a," "an," "the," "said" are used to indicate the presence of one or more elements/components/etc.; the terms "comprising" and "having" are intended to be inclusive and mean that there may be additional elements/components/etc. other than the listed elements/components/etc.
The problems of the prior art are thought: the image data and the XML file are not analyzed, the compatibility of a database of domestic equipment and the existing database is poor, and medical information cannot be fused and communicated well.
In order to solve the above technical problems, as shown in fig. 1, the present invention provides a home-made autonomous controllable hospital medical information system, which is characterized in that the hospital medical information system includes:
the system comprises a browser, a web server, a standardized management database and a network storage module;
the browser requests and responds to connect the web server in a bidirectional mode;
the web server reads data, writes the data into the standardized management database in a bidirectional connection manner, stores the data into the network storage module, analyzes the data in different analysis manners according to different file types of the data to obtain analysis results, performs interaction and fusion on the data by taking a case as a center based on the analysis results to obtain fusion results, and provides suggestions for treatment of the case according to the fusion results;
the network storage module adopts a domestic autonomous structure and is used for storing the data;
the standardized management database includes all database resources of the hospital.
Reading and writing of data of the standardized management database is realized by adopting a web server, and storing the data in a network storage module, wherein the data in the network storage module comprises XML files, text files, picture files, sound files and video files, different parsing modes are adopted to parse according to different file types to obtain parsing results, so that parsing of image data and XML files is realized, meanwhile, the problem of poor compatibility between a database of domestic equipment and the existing database is solved, the interaction and fusion of the data are carried out by taking a case as a center based on the analysis result to obtain a fusion result, and provides suggestions for the treatment of cases according to the fusion result, realizes the interaction and fusion of data, and can realize the control of the treatment process of the case according to the fusion result, and provide suggestions for the later specific treatment.
The browser is adopted to request or correspond the web server, so that the content of the server can be conveniently inquired, the overall access and control difficulty is greatly simplified, the web server stores the data in the network storage module, the data in the network storage module comprises XML files, text files, picture files, sound files and video files, different analysis modes are adopted to analyze according to different file types to obtain analysis results, so that resources in different databases can be fully utilized, the problem that information cannot be fused and interacted with other databases due to poor compatibility of a newly added database is solved, the problem that the compatibility of a database of domestic equipment and the existing database is poor is solved, and the interaction and fusion of the data are carried out by taking a case as a center based on the analysis results to obtain fusion results, and provide the suggestion for the treatment of case according to the result of said fusion, through obtaining the result of fusion with the case center, realize the interaction between different databases, while carrying on the particular inspection or treatment, the medical personnel can be according to the result of other databases, and the integral result of fusion, better grasp the key point, can judge according to the historical situation while treating, make the integral diagnosis result become more reliable. The network storage module adopts a domestic autonomous structure, so that the domestic requirements can be met, and the storage and the keeping of user information become more reliable.
In another possible embodiment, the access to the hospital clinical information system by the client or the third-party device is performed in a browser manner or an open port manner of the hospital clinical information system.
In another possible embodiment, the source of the data includes any one of: the client side entry, the hospital diagnosis and treatment information system entry and the third-party equipment entry.
In another possible embodiment, the web server further comprises a function service subsystem, a platform subsystem and a user subsystem;
the functional service subsystem comprises an appointment module, an inquiry module, an intelligent message reminding module, a database data processing module, an auxiliary API module and a payment module;
in another possible embodiment, the category of the functional service subsystem includes any one of: the medical treatment information, the medical process framework, the medical treatment guidance information and the medical treatment report of the third-party equipment.
The user subsystem is used for creating accounts for users and medical institutions, managing roles to which the users belong and distributing corresponding authorities and module functions;
the platform subsystem is used for establishing communication between the reservation module, the inquiry module, the intelligent message reminding module, the auxiliary API module, the payment module and the database data processing module and the user subsystem.
In another possible embodiment, the manner of communicating information between the plurality of clients includes any one of the following: the communication reminding is carried out in a mode of realizing direct communication through a chat window of the data communication module, in a mode of realizing indirect communication through a message leaving window of the data communication module, in a mode of sending system messages, short message reminding and the like.
In another possible embodiment, the content of the information communication between the plurality of clients includes any one of the following: text files, picture files, sound files, movie files.
In another possible embodiment, the domestic autonomous structure adopts a domestic database system based on a distributed architecture, and the hardware circuit adopts a domestic chip.
By adopting the server based on the distributed architecture, the data is deployed in a cluster formed by a plurality of machines, so that when one or more machines are damaged, the service is ensured not to be interfered by a backup mechanism among the machines, and meanwhile, a home-made database system and a home-made chip are adopted, so that the data is stored more safely and reliably in the field of software management and in addition, the hardware part is adopted.
In another possible embodiment, the appointment module is used for the user to appoint an inquiry time to the medical institution;
the inquiry module is used for establishing communication between the user and the medical institution through the platform subsystem within the inquiry time, and performing on-line inquiry to obtain an electronic medical record and a medicine list;
the intelligent message reminding module is used for carrying out information communication among a plurality of clients and releasing system messages and notifications;
the auxiliary API module is used for realizing data interaction between the third-party equipment and the hospital diagnosis and treatment information system and function expansion of the third-party equipment; the database data processing module is used for carrying out data analysis, data storage and reading on the hospital diagnosis and treatment information in the network storage module;
and the payment module is used for acquiring the online medical insurance of the user and performing inquiry and settlement to the medical institution through the medical insurance.
In another possible embodiment, the specific steps of parsing the XML file include:
s1, realizing the query of the XML element of the XML file based on the document object model to obtain a query result;
s2, constructing a character string database according to an expert algorithm, sending the query result into the character string database for comparison, and extracting keywords;
and S3, expressing the content of the XML file by taking the keywords as an XML analysis result.
The XML elements of the XML files are inquired by adopting a document object-based model, and the character string database matching result is constructed according to the expert algorithm to obtain the final analysis result, so that the XML files in the hospital information system are not in a deep sleep state, the information of the XML files can be shared with other servers, meanwhile, due to the stability and the specialty of the medical expression character strings, the character string library is constructed by adopting the expert algorithm, the final analysis result can be more stable and reliable, the efficiency is higher, the final analysis result cannot be determined and duplicate removed for different medical expressions by adopting a method based on a machine learning algorithm, and the efficiency is lower.
In another possible embodiment, the specific steps of parsing the picture file include:
s11, extracting keywords by adopting an LDA algorithm based on the diagnosis and treatment opinion files of the cases of the picture files to obtain LDA keywords, extracting the keywords of the diagnosis and treatment opinion files according to a TF-IDF algorithm to obtain TF-IDF keywords, and fusing and de-duplicating the LDA keywords and the TF-IDF keywords to finally obtain keywords;
s12: performing dimensionality reduction processing on the basis of the keywords to obtain dimensionality reduction image keywords, and sending the dimensionality reduction image keywords into an SVM (support vector machine) prediction model improved on the basis of a bat algorithm to predict and obtain the disease type at the moment;
s13, processing the picture file to obtain the image characteristic, determining the image key word according to the image characteristic and the disease type by adopting the prediction model of the CNN algorithm, and expressing the image by taking the image key word as the image analysis result.
The method comprises the steps of extracting keywords by adopting an LDA algorithm based on a diagnosis and treatment opinion file to obtain LDA keywords, extracting the keywords of the diagnosis and treatment opinion file according to a TF-IDF algorithm to obtain TF-IDF keywords, fusing and de-duplicating the LDA keywords and the TF-IDF keywords to obtain the keywords finally, wherein the TF-IDF algorithm tends to filter common words and retain important words, the judgment result depends on the structure of the IDF, only the word frequency and the position of the keywords are considered, the rarely-used words in the medicine are mistaken for the keywords, the LDA algorithm introduces the priors of dirichlet theme distribution and word distribution, the method is a non-supervised machine learning technology, the keywords can be identified more accurately, but the sequence of the keywords is not considered, so the two algorithms are combined, the final keyword identification effect becomes more accurate, and performing dimensionality reduction on the keywords to obtain dimensionality reduction key image keywords, wherein the keywords are more and need to be further subjected to dimensionality reduction to improve the final prediction speed, the dimensionality reduction image keywords are sent to an SVM prediction model improved based on a bat algorithm, and SVM classification results are optimized through the bat algorithm to obtain more accurate classification results, so that the disease type is accurately determined.
In another possible embodiment, the specific steps of parsing the text file include:
s11, extracting keywords of the character file by adopting an LDA algorithm to obtain LDA keywords, extracting the keywords of the diagnosis and treatment opinion file according to a TF-IDF algorithm to obtain TF-IDF keywords, and performing fusion de-duplication processing on the LDA keywords and the TF-IDF keywords to finally obtain character keywords;
s12: performing dimensionality reduction processing based on the character keywords to obtain dimensionality reduction character keywords, sending the dimensionality reduction character keywords to an SVM (support vector machine) prediction model improved based on a bat algorithm, and predicting to obtain the disease types at the moment
And S13, expressing the text file by taking the disease type and the text keywords as text analysis results.
In another possible embodiment, after obtaining the dimension-reduced text keywords or the dimension-reduced image keywords by using a principal component analysis based PCA, the algorithm for dimension reduction processing needs to further implement de-registration of the dimension-reduced text keywords or the dimension-reduced image keywords and process the de-registration to obtain the final dimension-reduced text keywords or the dimension-reduced image keywords through a character string database based on an expert algorithm.
The character string database based on the expert algorithm is used for carrying out de-duplication processing on the data subjected to the dimensionality reduction processing, and the de-duplication processing is carried out on the keywords which are different in name but consistent in meaning in certain medicine, so that the prediction efficiency can be further improved.
In another possible embodiment, different analysis results are exchanged among different standardized management databases by using an enterprise service bus technology, and the different analysis results are fused to form a final fusion result.
In another possible embodiment, when the doctor treats the case, the doctor can input keywords through the browser according to the specific situation of the case or match the fusion result of the historical case according to the analysis result, so as to provide suggestions for the doctor to treat.
According to the analysis result or the keywords determined by the doctor, the historical case fusion result is matched, so that the historical case can be queried in a simple and effective mode, and suggestions are provided for the doctor to further treat according to the query result, so that the judgment result is more accurate, and the treatment effect is better.
In embodiments of the present invention, the term "plurality" means two or more unless explicitly defined otherwise. The terms "mounted," "connected," "fixed," and the like are to be construed broadly and include, for example, fixed connections, removable connections, or integral connections. Specific meanings of the above terms in the embodiments of the present invention can be understood by those of ordinary skill in the art according to specific situations.
In the description of the embodiments of the present invention, it should be understood that the terms "upper", "lower", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience in describing the embodiments of the present invention and simplifying the description, but do not indicate or imply that the referred devices or units must have a specific direction, be configured in a specific orientation, and operate, and thus, should not be construed as limiting the embodiments of the present invention.
In the description herein, the appearances of the phrase "one embodiment," "a preferred embodiment," or the like, are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the embodiments of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The present invention can be configured as follows:
1. the utility model provides an information system is diagnose in hospital based on domestic autonomic controllable, this information system is diagnose in hospital includes:
the system comprises a browser, a web server, a standardized management database and a network storage module;
the browser requests and responds to the bidirectional connection web server;
the web server reads data, writes the data into a data bidirectional connection standardized management database, stores the data into a network storage module, analyzes the data by adopting different analysis modes according to different file types of the data to obtain an analysis result, performs interaction and fusion of the data by taking a case as a center based on the analysis result to obtain a fusion result, and provides a suggestion for treatment of the case according to the fusion result;
the network storage module adopts a domestic autonomous structure and is used for storing data;
the standardized administration database includes all database resources of the hospital.
2. According to the home-made autonomous controllable hospital diagnosis and treatment information system in the invention 1, the web server further comprises a function service subsystem, a platform subsystem and a user subsystem;
the function service subsystem comprises an appointment module, an inquiry module, an intelligent message reminding module, a database data processing module, an auxiliary API module and a payment module;
the user subsystem is used for creating accounts for users and medical institutions, managing roles to which the users belong and distributing corresponding authorities and module functions;
and the platform subsystem is used for establishing communication between the reservation module, the inquiry module, the intelligent message reminding module, the auxiliary API module, the payment module and the database data processing module and the user subsystem.
3. According to the home-made autonomous controllable hospital medical information system of 1 or 2,
the domestic autonomous structure adopts a domestic database system based on a distributed architecture, and a hardware circuit adopts a domestic chip.
4. According to the domestic-based autonomous controllable hospital diagnosis and treatment information system of 3,
the appointment module is used for appointing inquiry time to the medical institution by a user;
the inquiry module is used for establishing communication between the user and the medical institution through the platform subsystem in the inquiry time, and performing online inquiry to obtain an electronic medical record and a medicine list;
the intelligent message reminding module is used for carrying out information communication among a plurality of clients and releasing system messages and notifications;
the auxiliary API module is used for realizing data interaction between third-party equipment and a hospital diagnosis and treatment information system and function expansion of the third-party equipment; the database data processing module is used for carrying out data analysis, data storage and reading on the hospital diagnosis and treatment information in the network storage module;
and the payment module is used for acquiring the online medical insurance of the user and performing inquiry and settlement to the medical institution through the medical insurance.
5. According to the domestic autonomous controllable hospital diagnosis and treatment information system, the specific steps of analyzing the XML file are as follows:
s1, realizing the query of XML elements of the XML file based on the document object model to obtain a query result;
s2, constructing a character string database according to an expert algorithm, sending the query result into the character string database for comparison, and extracting keywords;
s3, the content of the XML file is expressed by using the keywords as the result of XML analysis.
6. According to the domestic autonomous controllable hospital diagnosis and treatment information system, the specific steps of analyzing the picture file are as follows:
s11, extracting keywords from the diagnosis and treatment opinion file based on the case of the picture file by adopting an LDA algorithm to obtain LDA keywords, extracting the keywords from the diagnosis and treatment opinion file according to a TF-IDF algorithm to obtain TF-IDF keywords, and fusing the LDA keywords and the TF-IDF keywords for de-duplication treatment to finally obtain the keywords;
s12: performing dimensionality reduction processing based on the keywords to obtain dimensionality reduction image keywords, and sending the dimensionality reduction image keywords into an SVM (support vector machine) prediction model improved based on a bat algorithm to predict and obtain the disease type at the moment;
s13, image processing is carried out on the picture file to obtain image characteristics, the image keywords at the moment are determined according to the image characteristics and the disease types by adopting a prediction model of a CNN algorithm, and the image keywords are used as image analysis results to realize the expression of the image.
7. According to the domestic autonomous controllable hospital diagnosis and treatment information system, the concrete steps of analyzing the text file are as follows:
s11, extracting keywords of the character file by adopting an LDA algorithm to obtain LDA keywords, extracting the keywords of the diagnosis and treatment opinion file according to a TF-IDF algorithm to obtain TF-IDF keywords, and fusing the LDA keywords and the TF-IDF keywords for de-duplication treatment to finally obtain character keywords;
s12: performing dimensionality reduction processing based on the character keywords to obtain dimensionality reduction character keywords, sending the dimensionality reduction character keywords to an SVM (support vector machine) prediction model improved based on a bat algorithm, and predicting to obtain the disease types at the moment
And S13, expressing the text file by taking the disease type and the text keywords as text analysis results.
8. According to the domestic autonomous controllable hospital diagnosis and treatment information system, the algorithm of the dimensionality reduction processing adopts a principal component analysis method based on PCA to obtain the dimensionality reduction character keywords or the dimensionality reduction image keywords, and then the de-coincidence of the dimensionality reduction character keywords or the dimensionality reduction image keywords is realized and the final dimensionality reduction character keywords or the dimensionality reduction image keywords are obtained through processing by further a character string database based on an expert algorithm.
9. According to the domestic-based autonomous controllable hospital diagnosis and treatment information system, information interaction between different standardized management databases is realized by adopting an enterprise service bus technology for different analysis results, and the different analysis results are fused, so that a final fusion result is formed.
10. According to the domestic-autonomous-controllable-based hospital diagnosis and treatment information system of any one of 1 to 9, when a doctor treats a case, keywords are input through a browser according to the specific situation of the case or the case is matched with the fusion result of historical cases according to the analysis result, so that a suggestion is provided for the doctor to treat.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes may be made to the present embodiment by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the embodiments of the present invention should be included in the protection scope of the embodiments of the present invention.
Claims (10)
1. The utility model provides an information system is diagnose in hospital based on homemade is independently controllable which characterized in that, information system is diagnose in hospital includes:
the system comprises a browser, a web server, a standardized management database and a network storage module;
the browser requests and responds to the bidirectional connection of the web server;
the web server reads data, writes the data into the standardized management database in a bidirectional connection manner, stores the data into the network storage module, analyzes the data in different analysis manners according to different file types of the data to obtain analysis results, performs interaction and fusion on the data by taking a case as a center based on the analysis results to obtain fusion results, and provides suggestions for treatment of the case according to the fusion results;
the network storage module adopts a domestic autonomous structure and is used for storing the data;
the standardized management database includes all database resources of the hospital.
2. The home-made autonomous controllable based hospital clinical information system according to claim 1,
the web server also comprises a function service subsystem, a platform subsystem and a user subsystem;
the functional service subsystem comprises an appointment module, an inquiry module, an intelligent message reminding module, a database data processing module, an auxiliary API module and a payment module;
the user subsystem is used for creating accounts for users and medical institutions, managing roles to which the users belong and distributing corresponding authorities and module functions;
the platform subsystem is used for establishing communication between the reservation module, the inquiry module, the intelligent message reminding module, the auxiliary API module, the payment module and the database data processing module and the user subsystem.
3. The home-made autonomous controllable based hospital clinical information system according to claim 1,
the domestic autonomous structure adopts a domestic database system based on a distributed architecture, and a hardware circuit adopts a domestic chip.
4. The home-made autonomous controllable based hospital clinical information system according to claim 1,
the appointment module is used for appointing inquiry time to the medical institution by the user;
the inquiry module is used for establishing communication between the user and a medical institution through the platform subsystem within the inquiry time, and performing on-line inquiry to obtain an electronic medical record and a medicine list;
the intelligent message reminding module is used for carrying out information communication among a plurality of clients and releasing system messages and notifications;
the auxiliary API module is used for realizing data interaction between the third-party equipment and the hospital diagnosis and treatment information system and function expansion of the third-party equipment; the database data processing module is used for carrying out data analysis, data storage and reading on the hospital diagnosis and treatment information in the network storage module;
and the payment module is used for acquiring the online medical insurance of the user and performing inquiry and settlement to the medical institution through the medical insurance.
5. The domestic-autonomous-controllable-based hospital diagnosis and treatment information system according to claim 1, wherein the specific steps of parsing said XML file are:
s1, realizing the query of the XML element of the XML file based on the document object model to obtain a query result;
s2, constructing a character string database according to an expert algorithm, sending the query result into the character string database for comparison, and extracting keywords;
and S3, expressing the content of the XML file by taking the keywords as an XML analysis result.
6. The domestic-autonomous-controllable-based hospital diagnosis and treatment information system according to claim 1, wherein the specific steps of parsing said picture file are as follows:
s11, extracting keywords by adopting an LDA algorithm based on the diagnosis and treatment opinion files of the cases of the picture files to obtain LDA keywords, extracting the keywords of the diagnosis and treatment opinion files according to a TF-IDF algorithm to obtain TF-IDF keywords, and fusing and de-duplicating the LDA keywords and the TF-IDF keywords to finally obtain keywords;
s12: performing dimensionality reduction processing on the basis of the keywords to obtain dimensionality reduction image keywords, and sending the dimensionality reduction image keywords into an SVM (support vector machine) prediction model improved on the basis of a bat algorithm to predict and obtain the disease type at the moment;
s13, processing the picture file to obtain the image characteristic, determining the image key word according to the image characteristic and the disease type by adopting the prediction model of the CNN algorithm, and expressing the image by taking the image key word as the image analysis result.
7. The domestic-autonomous-controllable-based hospital clinical information system according to claim 1, wherein the specific steps of parsing said text file are as follows:
s11, extracting keywords of the character file by adopting an LDA algorithm to obtain LDA keywords, extracting the keywords of the diagnosis and treatment opinion file according to a TF-IDF algorithm to obtain TF-IDF keywords, and performing fusion de-duplication processing on the LDA keywords and the TF-IDF keywords to finally obtain character keywords;
s12: performing dimension reduction processing based on the character keywords to obtain dimension reduction character keywords, sending the dimension reduction character keywords to an SVM (support vector machine) prediction model improved based on a bat algorithm, and predicting to obtain the disease type at the moment
And S13, expressing the text file by taking the disease type and the text keywords as text analysis results.
8. The domestic-autonomous-controllable-based hospital diagnosis and treatment information system according to claim 1, wherein after the dimensionality reduction processing algorithm adopts a principal component analysis based PCA to obtain the dimensionality reduction text keywords or the dimensionality reduction image keywords, the dimensionality reduction text keywords or the dimensionality reduction image keywords are further subjected to de-registration and processed to obtain the final dimensionality reduction text keywords or the dimensionality reduction image keywords through a character string database based on an expert algorithm.
9. The domestic-autonomous-controllable-based hospital diagnosis and treatment information system according to claim 1, wherein different parsing results are exchanged between different standardized management databases by using an enterprise service bus technology, and the different parsing results are fused to form a final fused result.
10. The home-made autonomous controlled hospital clinical information system according to claim 1, wherein when a doctor treats the case, the doctor provides a suggestion for the doctor to treat the case by inputting keywords through the browser according to the specific condition of the case or matching the fused result of the historical case according to the parsed result.
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