CN112328551A

CN112328551A - Medical data analysis method, device, medium, and electronic device

Info

Publication number: CN112328551A
Application number: CN202011240916.6A
Authority: CN
Inventors: 周于丰
Original assignee: Yidu Cloud Beijing Technology Co Ltd
Current assignee: NANJING YIJI CLOUD MEDICAL DATA RESEARCH INSTITUTE Co.,Ltd.
Priority date: 2020-11-09
Filing date: 2020-11-09
Publication date: 2021-02-05

Abstract

The invention provides a medical data analysis method, which comprises the following steps: acquiring all files to be analyzed under an input path according to the input path of the files to be analyzed; classifying all files to be analyzed according to preset medical service types to obtain a file set to be analyzed of multiple medical service types; determining the analysis logic of each file to be analyzed according to the file type of each file to be analyzed in each file set to be analyzed; the medical data is analyzed by the analyzing logic of each file to be analyzed and the corresponding file to be analyzed, and the analyzing result of each file to be analyzed in each file set to be analyzed is obtained. The invention also provides a medical data analysis device, a medium and electronic equipment.

Description

Medical data analysis method, device, medium, and electronic device

Technical Field

The invention relates to the technical field of data analysis, in particular to a medical data analysis method, a medical data analysis device, a medical data analysis medium and electronic equipment.

Background

The medical big data plays an important role in improving the efficiency of a medical system, optimizing a clinical decision path and realizing personalized medical services. Big medical data are developed in a digital resource way for a thousand miles every day, all systems of a hospital, such as HIS, EMR, LIS, RIS, PACS, operative anesthesia management and the like, generate huge data information every day, and in order to create a deeper medical data value, the hospital needs to collect the data to form a medical big data platform for improving medical efficiency, optimizing clinical decision, disease queue research and new drug research. However, since the medical system and the business process of each hospital are different, the collected data are different. At present, the requirement for analyzing medical data is not high, firstly, an analyst needs to deeply understand the hospital business process and the system architecture, and secondly, the complexity and the variability of the medical data also pose a small challenge to the analyst, so that an analysis method with high efficiency, low cost and strong reusability is urgently needed to stably, accurately and quickly analyze the medical data.

At present, medical data is analyzed, different analysis functions are compiled aiming at each medical service type of each hospital on the premise that hospitals are not changed, however, as a plurality of medical service types exist in each hospital and medical service types defined by each hospital possibly have differences, a large number of analysis functions need to be compiled, the time cost of compiling is increased, when medical data is analyzed, a plurality of analysis functions need to be invoked aiming at different medical service types to analyze the medical data, so that the analysis efficiency is reduced, and the reusability of the analysis mode is low.

It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present invention and therefore may include information that does not constitute prior art known to a person of ordinary skill in the art.

Disclosure of Invention

An object of the embodiments of the present invention is to provide a method, an apparatus, a medium, and an electronic device for analyzing medical data, so as to improve the analysis efficiency at least to a certain extent, and in this way, the reusability of analyzing medical data is high.

Additional features and advantages of the invention will be set forth in the detailed description which follows, or may be learned by practice of the invention.

According to a first aspect of embodiments of the present invention, there is provided a medical data parsing method, including: acquiring all files to be analyzed under an input path according to the input path of the files to be analyzed; classifying all files to be analyzed according to preset medical service types to obtain a file set to be analyzed of multiple medical service types; determining the analysis logic of each file to be analyzed according to the file type of each file to be analyzed in each file set to be analyzed; and analyzing the file to be analyzed corresponding to the analysis logic of each file to be analyzed by utilizing the analysis logic of each file to be analyzed, and acquiring an analysis result of each file to be analyzed in each file set to be analyzed.

In some embodiments of the invention, the method further comprises: generating an analyzed file based on the analysis result of each file to be analyzed in each file set to be analyzed; and storing the analyzed file into a folder named by the name of the medical service according to the output path of the analyzed file, wherein the output path is determined according to the input path.

In some embodiments of the invention, the method further comprises: judging whether the number of the categories of the various medical service types is smaller than the number of the categories of the preset medical service types; and if the number of the categories of the multiple medical service types is less than the number of the categories of the preset medical service types, displaying first prompt information, wherein the first prompt information is used for prompting that the preset medical service types are lacked in the multiple medical service types.

In some embodiments of the invention, the method further comprises: traversing each file to be analyzed in each file set to be analyzed, and determining whether each file to be analyzed contains medical data; and if the file to be analyzed does not contain the medical data, displaying second prompt information, wherein the second prompt information is used for prompting that the file to be analyzed which does not contain the medical data exists in the file set to be analyzed.

In some embodiments of the present invention, when the file type of the file to be parsed is XML, parsing the file to be parsed corresponding to the file to be parsed by using the parsing logic of each file to be parsed, and acquiring the parsing result of each file to be parsed in each set of files to be parsed includes: traversing each root node in the file to be analyzed with the file type of XML in each file set to be analyzed by utilizing the analysis logic of the file to be analyzed with the file type of XML, and acquiring the sub-elements in each root node and the corresponding values of the sub-elements; and storing the sub-elements and the corresponding values of the sub-elements into a set JSONS in a key-value mode.

In some embodiments of the present invention, when the file type of the file to be parsed is JSON, parsing the file to be parsed corresponding to the file to be parsed by using the parsing logic of each file to be parsed, and acquiring the parsing result of each file to be parsed in each set of files to be parsed includes: traversing JSON arrays of files to be analyzed with file types of JSON in each file set to be analyzed by utilizing the analysis logic of the files to be analyzed with the file types of JSON, and acquiring sub-elements in each JSON array and corresponding values of the sub-elements; and storing the sub-elements and the corresponding values of the sub-elements into a set JSONS in a key-value mode.

In some embodiments of the present invention, when the file type of the file to be parsed is "execute", parsing the file to be parsed corresponding to the file to be parsed by using the parsing logic of each file to be parsed, and acquiring the parsing result of each file to be parsed in each set of files to be parsed includes: traversing each tab of the file to be analyzed with the file type of EXCLE in each file set to be analyzed by utilizing the analysis logic of the file to be analyzed with the file type of EXCLE, and acquiring sub-elements in each tab and corresponding values of the sub-elements; and storing the sub-elements and the corresponding values of the sub-elements into a set JSONS in a key-value mode.

According to a second aspect of embodiments of the present invention, there is provided a medical data analysis apparatus, including: the acquisition module is used for acquiring all files to be analyzed under an input path according to the input path of the files to be analyzed; the classification module is used for classifying all files to be analyzed according to preset medical service types to obtain a file set to be analyzed of multiple medical service types; the first determining module is used for determining the analysis logic of each file to be analyzed according to the file type of each file to be analyzed in each file set to be analyzed; and the analysis module is used for analyzing the file to be analyzed corresponding to the analysis logic of each file to be analyzed and acquiring the analysis result of each file to be analyzed in each file set to be analyzed.

In some embodiments of the invention, the apparatus further comprises: the generating module is used for generating an analyzed file based on the analysis result of each file to be analyzed in each file set to be analyzed; the first storage module is used for storing the analyzed file into a folder named by a medical service name according to an output path of the analyzed file, and the output path is determined according to the input path.

In some embodiments of the invention, the apparatus further comprises: the judging module is used for judging whether the number of the categories of the various medical service types is less than the number of the categories of the preset medical service types; and the first display module displays first prompt information if the number of the categories of the multiple medical service types is less than the number of the categories of the preset medical service types, wherein the first prompt information is used for prompting that the preset medical service types are lacked in the multiple medical service types.

In some embodiments of the invention, the apparatus further comprises: the second determining module is used for traversing each file to be analyzed in each file set to be analyzed and determining whether each file to be analyzed contains medical data; and the second display module displays second prompt information if the file to be analyzed does not contain the medical data, wherein the second prompt information is used for prompting that the file to be analyzed which does not contain the medical data exists in the file set to be analyzed.

In some embodiments of the present invention, when the file type of the file to be parsed is XML, the parsing module includes: the first analysis module is used for traversing each root node in the file to be analyzed with the file type of XML in each file set to be analyzed by utilizing the analysis logic of the file to be analyzed with the file type of XML, and acquiring the sub-elements in each root node and the corresponding values of the sub-elements; and the second storage module is used for storing the sub-elements and the corresponding values of the sub-elements into the set JSONS in a key-value mode.

In some embodiments of the present invention, when the file type of the file to be parsed is JSON, the parsing module further includes: the second parsing module is used for traversing the JSON array of the file to be parsed, of which the file type is JSON, in each set of files to be parsed by using the parsing logic of the file to be parsed, of which the file type is JSON, and acquiring the sub-elements in each JSON array and the corresponding values of the sub-elements; and the third storage module is used for storing the sub-elements and the corresponding values of the sub-elements into a set JSONS in a key-value mode.

In some embodiments of the present invention, when the file type of the file to be parsed is an execute, the parsing module further includes: the third analysis module is used for traversing each tab of the file to be analyzed with the file type of EXCLE in each file set to be analyzed by utilizing the analysis logic of the file to be analyzed with the file type of EXCLE, and acquiring the sub-elements in each tab and the corresponding values of the sub-elements; and the fourth storage module is used for storing the sub-elements and the corresponding values of the sub-elements into a set JSONS in a key-value mode.

According to a third aspect of embodiments of the present invention, there is provided an electronic apparatus, including: one or more processors; a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method of medical data parsing as described in the first aspect of the embodiments above.

According to a fourth aspect of embodiments of the present invention, there is provided a computer-readable medium, on which a computer program is stored, which when executed by a processor, implements the medical data parsing method according to the first aspect of the embodiments.

The technical scheme provided by the embodiment of the invention has the following beneficial effects:

in the technical solutions provided by some embodiments of the present invention, all files to be parsed under an input path are obtained according to the input path of the file to be parsed, all files to be parsed are classified according to a preset medical service type, a set of files to be parsed of multiple medical service types is obtained, parsing logic of each file to be parsed is determined according to a file type of each file to be parsed in each set of files to be parsed, the file to be parsed corresponding to each file to be parsed is parsed by using the parsing logic of each file to be parsed, and parsing results of each file to be parsed in each set of files to be parsed are obtained.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort. In the drawings:

fig. 1 shows a schematic diagram of an exemplary system architecture to which a medical data parsing method or medical data parsing apparatus of an embodiment of the present invention may be applied;

fig. 2 schematically shows a flow chart of a medical data parsing method according to an embodiment of the invention;

FIG. 3 schematically shows a flow chart of a medical data parsing method according to another embodiment of the invention;

FIG. 4 schematically shows a flow chart of a medical data parsing method according to another embodiment of the invention;

FIG. 5 schematically shows a flow chart of a medical data parsing method according to another embodiment of the invention;

FIG. 6 schematically shows a flow chart of a medical data parsing method according to another embodiment of the invention;

FIG. 7 schematically shows a flow chart of a medical data parsing method according to another embodiment of the invention;

FIG. 8 schematically shows a flow chart of a medical data parsing method according to another embodiment of the invention;

FIGS. 9A-9D schematically illustrate input and output path diagrams of the present invention;

fig. 10 schematically shows a block diagram of a medical data interpretation apparatus according to an embodiment of the invention;

fig. 11 schematically shows a block diagram of a medical data interpretation apparatus according to another embodiment of the invention;

fig. 12 schematically shows a block diagram of a medical data interpretation apparatus according to another embodiment of the invention;

fig. 13 schematically shows a block diagram of a medical data interpretation apparatus according to another embodiment of the invention;

fig. 14 schematically shows a block diagram of a medical data interpretation apparatus according to another embodiment of the invention;

fig. 15 schematically shows a block diagram of a medical data interpretation apparatus according to another embodiment of the invention;

fig. 16 schematically shows a block diagram of a medical data interpretation apparatus according to another embodiment of the invention;

FIG. 17 illustrates a schematic structural diagram of a computer system suitable for use with the electronic device to implement an embodiment of the invention.

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 examples 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.

Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to provide a thorough understanding of embodiments of the invention. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations or operations have not been shown or described in detail to avoid obscuring aspects of the invention.

The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.

The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.

Fig. 1 is a schematic diagram showing an exemplary system architecture to which a medical data analysis method or a medical data analysis apparatus according to an embodiment of the present invention can be applied.

As shown in fig. 1, the system architecture 100 may include one or more of

terminal devices

101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the

terminal devices

101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.

It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation. For example, server 105 may be a server cluster comprised of multiple servers, or the like.

The user may use the

terminal devices

101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The

terminal devices

101, 102, 103 may be various electronic devices having a display screen, including but not limited to smart phones, tablet computers, portable computers, desktop computers, and the like.

The server 105 may be a server that provides various services. For example the server 105 may obtain medical data of various hospitals to the terminal device 103 (which may also be the terminal device 101 or 102), and stores it as a file to be parsed in the server 105, the server 105 can obtain all files to be parsed under the input path according to the input path of the file to be parsed, classifying all files to be analyzed according to preset medical service types to obtain a file set to be analyzed of a plurality of medical service types, determining the parsing logic of each file to be parsed according to the file type of each file to be parsed in each file set to be parsed, parsing the file to be parsed corresponding to each file to be parsed by using the parsing logic of each file to be parsed, obtaining the parsing result of each file to be parsed in each file set to be parsed, analyzing the medical data in this way can improve the analysis efficiency and also can improve the reusability of the analysis method.

In some embodiments, the medical data parsing method provided by the embodiments of the present invention is generally performed by the server 105, and accordingly, the medical data parsing apparatus is generally disposed in the server 105. In other embodiments, some terminals may have similar functionality as the server to perform the method. Therefore, the medical data analysis method provided by the embodiment of the invention is not limited to be executed at the server side.

Fig. 2 schematically shows a flow chart of a medical data parsing method according to an embodiment of the invention.

As shown in fig. 2, the medical data analysis method may include steps S210 to S240.

In step S210, all the files to be parsed under the input path are obtained according to the input path of the files to be parsed.

In step S220, all the files to be analyzed are classified according to the preset medical service type, so as to obtain a set of files to be analyzed of multiple medical service types.

In step S230, a parsing logic of each file to be parsed is determined according to a file type of each file to be parsed in each file set to be parsed.

In step S240, the file to be parsed corresponding to each file to be parsed is parsed by using the parsing logic of each file to be parsed, and a parsing result of each file to be parsed in each file set to be parsed is obtained.

The method can acquire all files to be analyzed under an input path according to the input path of the files to be analyzed, classify all the files to be analyzed according to preset medical service types to obtain file sets to be analyzed of multiple medical service types, determine the analysis logic of each file to be analyzed according to the file type of each file to be analyzed in each file set to be analyzed, analyze the file to be analyzed corresponding to the analysis logic of each file to be analyzed, and acquire the analysis result of each file to be analyzed in each file set to be analyzed.

In one embodiment of the invention, the medical data can be acquired from each hospital according to the actual application requirements, and the medical data of each hospital is stored by taking the patient as a dimension. In this embodiment, the medical data of each hospital is used as a file to be analyzed, that is, the file to be analyzed includes the medical data.

In an embodiment of the present invention, the input path of the file to be parsed may be a storage path of the file to be parsed. Referring to fig. 9C, the input path of the file to be parsed may be a computer/local disk E/project/a hospital/patient 1/outpatient order. The item can be defined according to actual requirements, hospital a can refer to a hospital in a certain area, patient 1 can refer to a patient who is in a visit of hospital a, and the outpatient medical order can refer to the medical service type set by hospital a. In this embodiment, all the files to be parsed under the input path may be obtained according to the input path, that is, all the files to be parsed in the outpatient medical order of the patient 1, such as four files to be parsed whose file types are XML shown in fig. 9C.

Based on the foregoing embodiments, the input path in fig. 9C may be composed of a plurality of input sub-paths. Referring to fig. 9A and 9B, the input sub-path may be a computer/local disk E/project/a hospital, and the input sub-path may also be a computer/local disk E/project/a hospital/patient 1. In this embodiment, the "item", "hospital a", "patient 1", and "outpatient medical order" in the input path may be replaced according to actual requirements, so that all the files to be analyzed under each medical service type of each patient in each hospital may be obtained according to the input path. For example, all path information sets under the input path are obtained according to the input path, the path information sets may include the input sub-path, folder information under the input sub-path, and file information under the input sub-path, and each folder under the input sub-path is traversed circularly to obtain a file to be parsed under each medical service type of each patient.

In an embodiment of the present invention, the preset medical service type may be set according to actual needs in each hospital. For example, the type of medical service that is preset may include, but is not limited to, an outpatient fee, an outpatient visit, an outpatient order, an inpatient fee, an inpatient visit, an inpatient order, an inpatient diagnosis, and the like.

In one embodiment of the invention, all files to be parsed for each patient are stored in the patient dimension into each patient's healthcare business type. Referring to fig. 9B, all files to be parsed for patient 1 in hospital a are stored in a plurality of medical service types for that patient 1. In this embodiment, before analyzing the files to be analyzed of the patients, the files to be analyzed of each medical service type of each patient in each hospital may be obtained according to the input path, and then all the files to be analyzed are classified according to the preset medical service type, so as to obtain a set of files to be analyzed of multiple medical service types. For example, files to be analyzed of all patients in each hospital can be classified according to medical service types preset in each hospital to obtain a set of files to be analyzed of multiple medical types, and each set of files to be analyzed contains all files to be analyzed of a certain medical service type of all patients, so that the files to be analyzed can be analyzed in a subsequent centralized manner, and the files to be analyzed of the multiple medical service types of each patient do not need to be analyzed by taking the patient as a dimension.

In the related art, when medical data is analyzed, an analysis function is compiled according to medical service types, and then the medical data of each patient under each medical service type is analyzed by using the analysis function, but because various hospitals have differences when defining the medical service types, before the medical data is analyzed, corresponding analysis functions need to be compiled according to a large number of medical service types, so that the time cost is increased, when the medical data is analyzed, the analysis functions of multiple medical service types need to be called circularly to analyze the medical data of each medical service type of each patient, so that the analysis efficiency is greatly reduced, and the reusability of the analysis method is low. According to the method and the device, the corresponding analysis logic can be set according to the file type of the file to be analyzed, and the file type of the file to be analyzed is fixed and unchanged and has fewer types, so that the analysis efficiency can be improved to a certain extent by analyzing the file to be analyzed based on the analysis logic, and the analysis mode is high in reusability. For example, the file type of the file to be parsed may be XML, JSON, EXCEL. In this embodiment, the parsing logic of each file to be parsed may be determined according to the file type of each file to be parsed in each file set to be parsed, and then the parsing logic of each file to be parsed is utilized to parse the file to be parsed corresponding to the parsing logic of each file to be parsed, so as to obtain the parsing result of each file to be parsed in each file set to be parsed.

Fig. 3 schematically shows a flow chart of a medical data parsing method according to another embodiment of the invention.

As shown in fig. 3, the method further includes step S310 and step S320.

In step S310, a parsed file is generated based on the parsing result of each to-be-parsed file in each to-be-parsed file set.

In step S320, the parsed file is stored in a folder named by a name of a medical service according to an output path of the parsed file, wherein the output path is determined according to the input path.

The method can generate an analyzed file based on the analysis result of each file to be analyzed in each file set to be analyzed, so that the efficiency of generating the analyzed file can be improved, the analyzed file is convenient to manage, the analyzed file is stored into the folder named by the name of the medical service according to the output path of the analyzed file, the storage efficiency can be improved, and the space occupied by the disk of the analyzed file is reduced.

In the related technology, the analyzed file is generated and stored based on the analysis result of the file to be analyzed under each medical service type of each patient, and the analyzed file is generated and stored in the mode because the number of the patients and the medical service types in the hospital is large, so that the efficiency of generating and storing the analyzed file is greatly reduced, and the occupied space of a disk is increased. According to the embodiment of the invention, each file set to be analyzed comprises files to be analyzed under one medical service type of all patients in one hospital, and in this case, one file after analysis can be generated based on the analysis result of each file to be analyzed in each file set to be analyzed, so that the efficiency of generating the file after analysis can be improved, and the file after analysis can be managed conveniently. And then storing the analyzed file into a folder named by the name of the medical service according to the output path of the analyzed file, so that the storage efficiency can be improved, and the space of a magnetic disk occupied by the analyzed file is reduced.

In an embodiment of the present invention, a parsed file is generated based on a parsing result of each file to be parsed in each set of files to be parsed. For example, a file to be parsed corresponding to each parsed file in each set of files to be parsed is parsed according to the parsing logic of the file to be parsed, and a parsing result of the file to be parsed is obtained, the parsing result of the file to be parsed may be temporarily stored in the set JSON, when the set JSON includes parsing results of all files to be parsed in the set JSON, an parsed file is generated based on parsing results of all files to be parsed in the set JSON, and the file is a parsed file of a set of files to be parsed of a medical service type.

In an embodiment of the present invention, the output path may be a storage path for storing the parsed file. For example, for storing parsed files for each set of files to be parsed.

In an embodiment of the present invention, the output path may be determined according to an input path of the file to be parsed, and specifically, the output path may be determined according to an input sub-path of the input path of the file to be parsed. For example, a folder for storing folders named by medical service names is created under an input sub-path of an input path of a file to be parsed. For example, the input path is computer/local disk E/project/a hospital/patient 1/outpatient order, the result ts is created under the hospital layer (input sub-path), the result ts is used for storing the folder named by the name of the medical service, referring to fig. 9D, and the output path is computer/local disk E/project/a hospital/result.

Referring to FIG. 9D, the folders named by the name of the medical service may be a tbl _ mz _ menzhen folder, a tbl _ mzfymx _ menzhenyingmingxi folder, a tbl _ mzyz _ menzhenyizhu folder, a tbl _ zy _ zhuyuan folder, and the like. The folder shown in fig. 9D is used to store the parsed files of the medical-type to-be-parsed file set corresponding thereto. For example, the folder named tbl _ mz _ menzhen is used to store parsed files of a set of files to be parsed with a medical service type of "outpatient service".

As another example, the folder named tbl _ mzfymx _ menzhenfeiyongmixi is used to store parsed files of the set of files to be parsed with the type of medical service "outpatient cost detail".

As another example, the folder named tbl _ mzyz _ menzhenyizhu is used to store parsed files of a set of files to be parsed with a medical service type of "outpatient order".

As another example, the folder named tbl _ zy _ zhuyuan is used to store the parsed files of the set of files to be parsed with the type of medical service "hospitalized".

Fig. 4 schematically shows a flow chart of a medical data parsing method according to another embodiment of the invention.

As shown in fig. 4, the method further includes step S410 and step S420.

In step S410, it is determined whether the number of categories of the plurality of medical service types is less than the number of categories of the preset medical service type.

In step S420, if the number of categories of the multiple medical service types is less than the number of categories of the preset medical service type, a first prompt message is displayed, where the first prompt message is used to prompt that the preset medical service type is absent from the multiple medical service types.

The method can find whether certain medical service type in the preset medical service types is missing in the multiple medical service types in time by judging whether the number of the categories of the multiple medical service types is smaller than the number of the categories of the preset medical service types, and if the number of the categories of the multiple medical service types is smaller than the number of the categories of the preset medical service types, the method indicates that certain medical service type in the preset medical service types is missing in the multiple medical service types.

In one embodiment of the present invention, the plurality of medical service types may include outpatient service cost, outpatient service visit, outpatient service orders, hospitalization cost, and hospitalization visit, and the number of categories of the plurality of medical service types is 5. The preset medical service types can include clinic cost, clinic visit, clinic advice, hospitalization cost, hospitalization visit, hospitalization advice and hospitalization visit, and the number of the types of the preset medical service types is 7. In this case, the category number of the multiple medical service types is smaller than the category number of the preset medical service types, and the first prompt information is displayed, for example, the first prompt information may be "in-patient advice, in-patient visit" in the preset medical service types that are missing in the multiple medical service types, so that the relevant personnel can be timely notified that "in-patient advice, in-patient visit" in the preset medical service types are missing in the multiple medical service types, and the relevant personnel can check whether data are lost in the data acquisition process according to the situation.

Fig. 5 schematically shows a flow chart of a medical data parsing method according to another embodiment of the invention.

As shown in fig. 5, the method further includes step S510 and step S520.

In step S510, each file to be parsed in each file set to be parsed is traversed, and it is determined whether each file to be parsed includes medical data.

In step S520, if the file to be parsed does not include medical data, a second prompt message is displayed, where the second prompt message is used to prompt that the file to be parsed does not include medical data in the file set to be parsed.

The method can determine whether each file to be analyzed contains medical data or not by traversing each file to be analyzed in each file set to be analyzed, and if the file to be analyzed does not contain the medical data, second prompt information is displayed, so that related personnel can be timely reminded that the file to be analyzed is an empty file, and the related personnel can timely inquire reasons according to the situation.

In an embodiment of the present invention, the files to be parsed included in each set of files to be parsed belong to files to be parsed of the same medical service type. And circularly traversing each file to be analyzed in each file set to be analyzed to timely determine whether each file to be analyzed contains medical data, and if the file to be analyzed does not contain the medical data, displaying second prompt information. In this embodiment, the second prompting message may be used to prompt that there is a to-be-analyzed file that does not include medical data in the to-be-analyzed file set, for example, the to-be-analyzed file of "patient 1" in the to-be-analyzed set whose second prompting message is "out-patient cost" is empty, that is, there is no medical data in the to-be-analyzed file.

Fig. 6 schematically shows a flow chart of a medical data parsing method according to another embodiment of the invention.

When the file type of the file to be parsed is XML, the step S240 may specifically include a step S610 and a step S620, as shown in fig. 6.

In step S610, each root node in the file to be parsed having the file type of XML in each set of files to be parsed is traversed by using the parsing logic of the file to be parsed having the file type of XML, and a sub-element in each root node and a corresponding value of the sub-element are obtained.

In step S620, the child element and the corresponding value of the child element are stored in the set JSONS in the form of a key-value.

The method can traverse each root node in the file to be analyzed with the file type of XML in each file set to be analyzed by utilizing the analysis logic of the file to be analyzed with the file type of XML, and obtains the sub-elements in each root node and the corresponding values of the sub-elements.

In an embodiment of the present invention, each root node in the file to be parsed with the file type of XML in each set of files to be parsed is traversed by using the parsing logic of the file to be parsed with the file type of XML, and a child element in each root node and a corresponding value of the child element are obtained. For example, the number of the file sets to be parsed is 5, that is, the file sets to be parsed of 5 medical service types, and the parsing logic of the file to be parsed having the file type of XML can cycle through each root node in the file set to be parsed having the file type of XML in each medical service type, so as to obtain the sub-elements in each root node and the corresponding values of the sub-elements.

In an embodiment of the present invention, the child elements and the corresponding values of the child elements parsed from the root node of the file to be parsed having the file type of XML are temporarily stored in a key-value manner in the set JSONS, if the file types of the files to be parsed in the set of files to be parsed are all XML, each file to be parsed in the set of files to be parsed is parsed by using the parsing logic of the file to be parsed having the file type of XML, in this case, the set JSONS includes the parsing results of all files to be parsed having the file type of XML in the set of files to be parsed, generates a parsed file based on the parsing results of all files to be parsed having the file type of XML in the set of files to be parsed, and stores the parsed file to the folder named by the medical service name according to the output path.

Fig. 7 schematically shows a flow chart of a medical data parsing method according to another embodiment of the invention.

When the file type of the file to be parsed is JSON, the step S240 may specifically include a step S710 and a step S720, as shown in fig. 7.

In step S710, traversing the JSON array of the to-be-parsed file having the file type JSON in each to-be-parsed file set by using the parsing logic of the to-be-parsed file having the file type JSON, and acquiring the child elements in each JSON array and the corresponding values of the child elements.

In step S720, the child element and the corresponding value of the child element are stored in the set JSONS in the form of a key-value.

The method can traverse the JSON array of the file to be analyzed with the file type of JSONS in each set of files to be analyzed by utilizing the analysis logic of the file to be analyzed with the file type of JSONS, and obtain the sub-elements in each JSON array and the corresponding values of the sub-elements.

In an embodiment of the invention, a JSON array of the file to be analyzed with the file type JSON in each file set to be analyzed is traversed by utilizing the analysis logic of the file to be analyzed with the file type JSON, and the sub-elements in each JSON array and the corresponding values of the sub-elements are obtained. For example, the number of the file sets to be parsed is 5, that is, the file sets to be parsed of 5 medical service types, and the JSON arrays of the files to be parsed having the file type JSON in the file sets to be parsed having each medical service type can be circularly traversed by using the parsing logic of the files to be parsed having the file type JSON, so as to obtain the child elements in each JSON array and the corresponding values of the child elements.

In an embodiment of the present invention, the child elements and the corresponding values of the child elements parsed from the JSON array of the to-be-parsed file with the file type JSON are temporarily stored in a key-value manner in the set JSONs, if the file types of the to-be-parsed files in the to-be-parsed file set are all JSON, each to-be-parsed file in the to-be-parsed file set is parsed by using the parsing logic of the to-be-parsed file with the file type JSON, in this case, the set JSONs contains the parsing results of all to-be-parsed files with the file type JSON in the to-be-parsed file set, and generates a parsed file based on the parsing results of all to-be-parsed files with the file types JSON in the to-parsed file set, and stores the parsed file into the folder named by the medical service name according to the output path.

Fig. 8 schematically shows a flow chart of a medical data parsing method according to another embodiment of the invention.

When the file type of the file to be parsed is "execute", the step S240 may specifically include a step S810 and a step S820, as shown in fig. 8.

In step S810, traversing each tab of the file to be parsed having a file type of EXCLE in each set of files to be parsed by using parsing logic of the file to be parsed having a file type of EXCLE, and acquiring a sub-element in each tab and a corresponding value of the sub-element.

In step S820, the child element and the corresponding value of the child element are stored in the set JSONS in the form of a key-value.

The method can traverse each tab of the file to be analyzed with the file type of EXCLE in each file set to be analyzed by utilizing the analysis logic of the file to be analyzed with the file type of EXCLE, and obtain the sub-elements in each tab and the corresponding values of the sub-elements.

In an embodiment of the invention, each tab of the file to be analyzed with the file type of EXCLE in each file set to be analyzed is traversed by utilizing the analysis logic of the file to be analyzed with the file type of EXCLE, and the sub-elements in each tab and the corresponding values of the sub-elements are obtained. For example, the number of the file sets to be analyzed is 5, that is, the file sets to be analyzed of 5 medical service types, and each tab of the file to be analyzed of the file type EXCLE in the file set to be analyzed of each medical service type can be circularly traversed by using the analysis logic of the file to be analyzed of the file type EXCLE, so as to obtain the sub-elements in each tab and the corresponding values of the sub-elements.

In an embodiment of the present invention, the child elements and the corresponding values of the child elements parsed from each tab of the file to be parsed whose file type is EXCLE are temporarily stored in a key-value form in a set JSONS, if the file types of the files to be parsed in the set of files to be parsed are all EXCLE, each file to be parsed in the set of files to be parsed is parsed by using the parsing logic of the file to be parsed whose file type is EXCLE, in this case, the set JSONS contains the parsing results of all files to be parsed whose file types are EXCLE in the set of files to be parsed, and generates a parsed file based on the parsing results of all files to be parsed whose file types are EXCLE in the set of files to be parsed, and stores the parsed file to a folder named by a medical service name according to an output path.

Based on the embodiment, if the set of files to be analyzed contains files to be analyzed of different file types, different analysis logics are determined according to the different file types, the files to be analyzed of the corresponding file types are analyzed according to the different analysis logics, and analysis results are obtained and stored in the set JSONS in a key-value mode.

For example, the set of files to be parsed includes three files to be parsed, which are a file to be parsed 1, a file to be parsed 2, and a file to be parsed 3. And determining the file type of the file 1 to be analyzed, the file type of the file 2 to be analyzed and the file type of the file 3 to be analyzed according to the file name of the file 1 to be analyzed, the file name of the file 2 to be analyzed and the file name of the file 3 to be analyzed. For example, the file type of the file to be parsed 1 is XML, the file type of the file to be parsed 2 is JSON, and the file type of the file to be parsed 3 is EXCLE.

Determining an analysis logic corresponding to the file type XML according to the file type XML, analyzing the file 1 to be analyzed by using the analysis logic, obtaining an analysis result of the file 1 to be analyzed, and temporarily storing the analysis result of the file 1 to be analyzed to the set JSONS in a key-value mode. In addition, when the file to be analyzed with the file type of XML is analyzed, if Chinese exists according to the point and the sub-element, the Chinese needs to be converted into the first spelling, and if the first spelling is repeated, one can be recursively added at the tail of the first spelling according to the occurrence times.

Determining an analysis logic corresponding to the file type JSONS according to the file type JSONS, analyzing the file 2 to be analyzed by using the analysis logic, obtaining an analysis result of the file 2 to be analyzed, and then temporarily storing the analysis result of the file 2 to be analyzed to the set JSONS in a key-value mode. In addition, when the file to be analyzed with the file type being JSON is analyzed, if the key value in the JSON data group has Chinese characters, the Chinese characters need to be converted into initial spelling, and if the initial spelling is repeated, one can be recursively added at the tail of the initial spelling according to the occurrence times.

Determining an analysis logic corresponding to the file type EXCLE according to the file type EXCLE, analyzing the file 3 to be analyzed by using the analysis logic, obtaining an analysis result of the file 3 to be analyzed, and then temporarily storing the analysis result of the file 3 to be analyzed to the set JSONS in a key-value mode. For example, traversing the tab in the file to be analyzed with the file type of EXCLE, taking the first line of the tab as a key value, starting from the second line as a corresponding value of the key, circularly traversing the tab, and finally storing the tab-value into the set JSONS in a key-value form.

The file 1 to be analyzed, the file 2 to be analyzed and the file 3 to be analyzed are analyzed respectively through the three modes, the analysis result of the file 1 to be analyzed, the analysis result of the file 2 to be analyzed and the analysis result of the file 3 to be analyzed are stored in the set JSONS, then an analyzed file is generated based on the analysis result of the file 1 to be analyzed, the analysis result of the file 2 to be analyzed and the analysis result of the file 3 to be analyzed, and the analyzed file is stored in a folder named by the medical service type according to an output path. And finally, emptying the set JSONS, continuously analyzing the files to be analyzed of the file sets to be analyzed of other medical service types, and temporarily storing the analysis result to the set JSONS. In this embodiment, the file type of the parsing result is JSON.

Fig. 10 schematically shows a block diagram of a medical data interpretation apparatus according to an embodiment of the invention.

As shown in fig. 10, the medical data parsing apparatus 200 includes an acquisition module 201, a classification module 202, a first determination module 203, and a parsing module 204.

Specifically, the obtaining module 201 is configured to obtain all files to be analyzed under an input path according to the input path of the files to be analyzed.

The classification module 202 is configured to classify all the files to be analyzed according to a preset medical service type, so as to obtain a set of files to be analyzed of multiple medical service types.

The first determining module 203 is configured to determine an parsing logic of each file to be parsed according to a file type of each file to be parsed in each file set to be parsed.

The parsing module 204 parses the file to be parsed corresponding to each file to be parsed by using the parsing logic of each file to be parsed, and obtains a parsing result of each file to be parsed in each file set to be parsed.

The medical data analysis device 200 can acquire all files to be analyzed under an input path according to the input path of the files to be analyzed, classify all the files to be analyzed according to preset medical service types to obtain file sets to be analyzed of multiple medical service types, determine analysis logic of each file to be analyzed according to the file type of each file to be analyzed in each file set to be analyzed, analyze the file to be analyzed corresponding to the analysis logic of each file to be analyzed, and acquire an analysis result of each file to be analyzed in each file set to be analyzed.

According to an embodiment of the present invention, the medical data parsing apparatus 200 can be used for implementing the medical data parsing method described in the embodiment of fig. 2.

Fig. 11 schematically shows a block diagram of a medical data interpretation apparatus according to another embodiment of the invention.

As shown in fig. 11, the medical data analysis device 200 further includes a generation module 205 and a first storage module 206.

Specifically, the generating module 205 generates an analyzed file based on an analysis result of each file to be analyzed in each file set to be analyzed.

A first storage module 206, configured to store the parsed file into a folder named by a medical service name according to an output path of the parsed file, where the output path is determined according to the input path.

The medical data analysis device 200 can generate an analyzed file based on the analysis result of each file to be analyzed in each file set to be analyzed, so that the efficiency of generating the analyzed file can be improved, the analyzed file can be managed conveniently, the analyzed file is stored in the folder named by the name of the medical service according to the output path of the analyzed file, the storage efficiency can be improved, and the space occupied by a magnetic disk by the analyzed file is reduced.

According to an embodiment of the present invention, the medical data parsing apparatus 200 may be used for implementing the medical data parsing method described in the embodiment of fig. 3.

Fig. 12 schematically shows a block diagram of a medical data interpretation apparatus according to another embodiment of the invention.

As shown in fig. 12, the medical data analysis device 200 further includes a determination module 207 and a first display module 208.

Specifically, the determining module 207 is configured to determine whether the number of the categories of the multiple medical service types is smaller than the number of the categories of the preset medical service types.

The first display module 208 displays a first prompt message if the number of the categories of the multiple medical service types is less than the number of the categories of the preset medical service types, where the first prompt message is used to prompt that the preset medical service types are missing from the multiple medical service types.

The medical data analysis device 200 may find whether a certain medical service type of the preset medical service types is missing in the multiple medical service types in time by determining whether the number of the categories of the multiple medical service types is smaller than the number of the categories of the preset medical service types, and if the number of the categories of the multiple medical service types is smaller than the number of the categories of the preset medical service types, it indicates that the certain medical service type of the preset medical service types is missing in the multiple medical service types, and in this case, a relevant person may be prompted to miss the certain medical service type of the preset medical service types by displaying the first prompt information.

According to an embodiment of the present invention, the medical data parsing apparatus 200 may be used for implementing the medical data parsing method described in the embodiment of fig. 4.

Fig. 13 schematically shows a block diagram of a medical data interpretation apparatus according to another embodiment of the invention.

As shown in fig. 13, the medical data analysis device 200 further includes a second determination module 209 and a second display module 210.

Specifically, the second determining module 209 is configured to traverse each to-be-parsed file in each to-be-parsed file set, and determine whether each to-be-parsed file contains medical data.

The second display module 210 displays second prompt information if the file to be analyzed does not contain the medical data, where the second prompt information is used to prompt that the file to be analyzed does not contain the medical data in the file set to be analyzed.

The medical data analysis device 200 can determine whether each file to be analyzed contains medical data by traversing each file to be analyzed in each file set to be analyzed, and if the file to be analyzed does not contain medical data, second prompt information is displayed, so that relevant personnel can be timely reminded that the file to be analyzed is an empty file, and the relevant personnel can timely inquire reasons according to the situation.

According to an embodiment of the present invention, the medical data parsing apparatus 200 may be used for implementing the medical data parsing method described in the embodiment of fig. 5.

Fig. 14 schematically shows a block diagram of a medical data interpretation apparatus according to another embodiment of the invention.

As shown in fig. 14, the parsing module 204 may specifically include a first parsing module 204-1 and a second storage module 204-2.

Specifically, the first parsing module 204-1 traverses each root node in the file to be parsed having the file type of XML in each set of files to be parsed by using parsing logic of the file to be parsed having the file type of XML, and obtains a child element in each root node and a corresponding value of the child element.

A second storing module 204-2, configured to store the sub-element and the corresponding value of the sub-element into the set JSONS in the form of a key-value.

The parsing module 204 may traverse each root node in the file to be parsed having the file type of XML in each set of files to be parsed by using parsing logic of the file to be parsed having the file type of XML, and obtain sub-elements in each root node and corresponding values of the sub-elements.

According to an embodiment of the present invention, the parsing module 204 may be used to implement the medical data parsing method described in the embodiment of fig. 6.

Fig. 15 schematically shows a block diagram of a medical data interpretation apparatus according to another embodiment of the invention.

As shown in fig. 15, the parsing module 204 may specifically include a second parsing module 204-3 and a third storage module 204-4.

Specifically, the second parsing module 204-3 traverses the JSON array of the to-be-parsed file with the file type JSON in each to-be-parsed file set by using the parsing logic of the to-be-parsed file with the file type JSON, and obtains the child elements in each JSON array and the corresponding values of the child elements.

A third storing module 204-4, configured to store the sub-element and the corresponding value of the sub-element into the set JSONS in the form of a key-value.

The parsing module 204 can traverse the JSON array of the to-be-parsed file with the file type JSONS in each set of to-be-parsed files by using the parsing logic of the to-be-parsed file with the file type JSONS, and obtain the sub-elements in each JSON array and the corresponding values of the sub-elements.

According to an embodiment of the invention, the parsing module 204 may be used to implement the medical data parsing method described in the embodiment of fig. 7.

Fig. 16 schematically shows a block diagram of a medical data interpretation apparatus according to another embodiment of the invention.

As shown in fig. 16, the parsing module 204 may specifically include a third parsing module 204-5 and a fourth storage module 204-6.

Specifically, the third parsing module 204-5 traverses each tab of the file to be parsed, which has a file type of EXCLE, in each set of files to be parsed by using parsing logic of the file to be parsed, which has a file type of EXCLE, and obtains a sub-element in each tab and a corresponding value of the sub-element.

A fourth storing module 204-6, configured to store the sub-element and the corresponding value of the sub-element into the set JSONS in the form of a key-value.

The parsing module 204 may traverse each tab of the file to be parsed having the file type of EXCLE in each set of files to be parsed by using a parsing logic of the file to be parsed having the file type of EXCLE, and obtain sub-elements in each tab and corresponding values of the sub-elements.

According to an embodiment of the invention, the parsing module 204 may be used to implement the medical data parsing method described in the embodiment of fig. 8.

For details that are not disclosed in the embodiments of the apparatus of the present invention, reference is made to the embodiments of the medical data parsing method of the present invention described above for details that are not disclosed in the embodiments of the apparatus of the present invention, since the respective modules of the medical data parsing apparatus 200 of the exemplary embodiment of the present invention can be used to implement the steps of the exemplary embodiments of the medical data parsing method described above in fig. 2 to 8.

It is understood that the obtaining module 201, the classifying module 202, the first determining module 203, the parsing module 204, the first parsing module 204-1, the second storage module 204-2, the second parsing module 204-3, the third storage module 204-4, the third parsing module 204-5, the fourth storage module 204-6, the generating module 205, the first storage module 206, the determining module 207, the first presenting module 208, the second determining module 209, and the second presenting module 210 may be combined to be implemented in one module, or any one of them may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. According to an embodiment of the present invention, at least one of the obtaining module 201, the classifying module 202, the first determining module 203, the parsing module 204, the first parsing module 204-1, the second storing module 204-2, the second parsing module 204-3, the third storing module 204-4, the third parsing module 204-5, the fourth storing module 204-6, the generating module 205, the first storing module 206, the judging module 207, the first presenting module 208, the second determining module 209, and the second presenting module 210 may be at least partially implemented as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or in a suitable combination of software, hardware and firmware implementations. Alternatively, at least one of the obtaining module 201, the classifying module 202, the first determining module 203, the parsing module 204, the first parsing module 204-1, the second storage module 204-2, the second parsing module 204-3, the third storage module 204-4, the third parsing module 204-5, the fourth storage module 204-6, the generating module 205, the first storage module 206, the judging module 207, the first presenting module 208, the second determining module 209, and the second presenting module 210 may be at least partially implemented as a computer program module, and when the program is executed by a computer, the function of the corresponding module may be executed.

Referring now to FIG. 17, shown is a block diagram of a computer system 300 suitable for use with the electronic device implementing an embodiment of the present invention. The computer system 300 of the electronic device shown in fig. 17 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.

As shown in fig. 17, the computer system 300 includes a Central Processing Unit (CPU)301 that can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)302 or a program loaded from a storage section 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data necessary for system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.

The following components are connected to the I/O interface 305: an input portion 306 including a keyboard, a mouse, and the like; an output section 307 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 308 including a hard disk and the like; and a communication section 309 including a network interface card such as a LAN card, a modem, or the like. The communication section 309 performs communication processing via a network such as the internet. A drive 310 is also connected to the I/O interface 305 as needed. A removable medium 311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 310 as necessary, so that a computer program read out therefrom is mounted into the storage section 308 as necessary.

In particular, according to an embodiment of the present invention, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the invention include a computer program product comprising a computer program embodied on a computer-readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 309, and/or installed from the removable medium 311. The above-described functions defined in the system of the present application are executed when the computer program is executed by the Central Processing Unit (CPU) 301.

It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in the embodiments of the present invention may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves.

As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to implement the medical data parsing method as described in the above embodiments.

For example, the electronic device may implement the following as shown in fig. 2: in step S210, all the files to be parsed under the input path are obtained according to the input path of the files to be parsed. In step S220, all the files to be analyzed are classified according to the preset medical service type, so as to obtain a set of files to be analyzed of multiple medical service types. In step S230, a parsing logic of each file to be parsed is determined according to a file type of each file to be parsed in each file set to be parsed. In step S240, the file to be parsed corresponding to each file to be parsed is parsed by using the parsing logic of each file to be parsed, and a parsing result of each file to be parsed in each file set to be parsed is obtained.

It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the invention. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiment of the present invention.

Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.

It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.

Claims

1. A method for medical data analysis, the method comprising:

acquiring all files to be analyzed under an input path according to the input path of the files to be analyzed;

classifying all files to be analyzed according to preset medical service types to obtain a file set to be analyzed of multiple medical service types;

determining the analysis logic of each file to be analyzed according to the file type of each file to be analyzed in each file set to be analyzed;

and analyzing the file to be analyzed corresponding to the analysis logic of each file to be analyzed by utilizing the analysis logic of each file to be analyzed, and acquiring an analysis result of each file to be analyzed in each file set to be analyzed.

2. The method of claim 1, further comprising:

generating an analyzed file based on the analysis result of each file to be analyzed in each file set to be analyzed;

and storing the analyzed file into a folder named by the name of the medical service according to the output path of the analyzed file, wherein the output path is determined according to the input path.

3. The method of claim 1, further comprising:

judging whether the number of the categories of the various medical service types is smaller than the number of the categories of the preset medical service types;

and if the number of the categories of the multiple medical service types is less than the number of the categories of the preset medical service types, displaying first prompt information, wherein the first prompt information is used for prompting that the preset medical service types are lacked in the multiple medical service types.

4. The method of claim 1, further comprising:

traversing each file to be analyzed in each file set to be analyzed, and determining whether each file to be analyzed contains medical data;

and if the file to be analyzed does not contain the medical data, displaying second prompt information, wherein the second prompt information is used for prompting that the file to be analyzed which does not contain the medical data exists in the file set to be analyzed.

5. The method according to claim 1, wherein when the file type of the file to be parsed is XML, parsing the file to be parsed corresponding to each file to be parsed by using the parsing logic of each file to be parsed, and obtaining the parsing result of each file to be parsed in each set of files to be parsed comprises:

traversing each root node in the file to be analyzed with the file type of XML in each file set to be analyzed by utilizing the analysis logic of the file to be analyzed with the file type of XML, and acquiring the sub-elements in each root node and the corresponding values of the sub-elements;

and storing the sub-elements and the corresponding values of the sub-elements into a set JSONS in a key-value mode.

6. The method according to claim 1, wherein when the file type of the file to be parsed is JSON, parsing the file to be parsed corresponding to the parsing logic of each file to be parsed, and obtaining the parsing result of each file to be parsed in each set of files to be parsed comprises:

traversing JSON arrays of files to be analyzed with file types of JSON in each file set to be analyzed by utilizing the analysis logic of the files to be analyzed with the file types of JSON, and acquiring sub-elements in each JSON array and corresponding values of the sub-elements;

7. The method according to claim 1, wherein when the file type of the file to be parsed is "EXCLE", parsing the file to be parsed corresponding to the file to be parsed by using the parsing logic of each file to be parsed, and obtaining the parsing result of each file to be parsed in each set of files to be parsed comprises:

traversing each tab of the file to be analyzed with the file type of EXCLE in each file set to be analyzed by utilizing the analysis logic of the file to be analyzed with the file type of EXCLE, and acquiring sub-elements in each tab and corresponding values of the sub-elements;

8. A medical data analysis apparatus, comprising:

the acquisition module is used for acquiring all files to be analyzed under an input path according to the input path of the files to be analyzed;

the classification module is used for classifying all files to be analyzed according to preset medical service types to obtain a file set to be analyzed of multiple medical service types;

the first determining module is used for determining the analysis logic of each file to be analyzed according to the file type of each file to be analyzed in each file set to be analyzed;

and the analysis module is used for analyzing the file to be analyzed corresponding to the analysis logic of each file to be analyzed and acquiring the analysis result of each file to be analyzed in each file set to be analyzed.

9. An electronic device, comprising:

one or more processors; and

storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out a method according to any one of claims 1 to 7.

10. A computer-readable medium, on which a computer program is stored, which program, when being executed by a processor, is adapted to carry out the method according to any one of claims 1 to 7.