Physical examination order generation method and device, equipment and storage medium

Abstract

The embodiment of the invention provides a physical examination order generation method and device, equipment and a storage medium. The method comprises the steps of obtaining a target physical examination package and target item adding package information, wherein the target item adding package information comprises item adding packages selected by a plurality of users; performing feature extraction on the target item adding package information, arranging the target item adding packages according to a preset rule, and generating a retrieval feature value corresponding to the target item adding package information; matching is conducted in an item database through the retrieval feature values, a matching result is obtained, and the item database comprises a plurality of initial physical examination packages and retrieval feature values of a plurality of optional initial item adding packages corresponding to the initial physical examination packages; and in response to the fact that the matching result is successful matching, generating a target physical examination order based on the target item adding package information and the target physical examination package. According to the invention, conflicts between the item adding combination and the physical examination package are avoided, and then the physical examination order capable of meeting the personalized requirements of the user is generated.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method for generating a physical examination order, a physical examination order generating device, a computer device, and a computer-readable storage medium. Background Art

[0002] As people's living standards continue to improve, the demand for preventive health care continues to increase. Regular physical examinations, as an important part of health care, are increasingly valued by people. In the online physical examination reservation process, the preset physical examination packages often cannot meet the needs of users, so it is necessary to provide personalized physical examination add-ons for users to choose to purchase. If users choose to add items arbitrarily, they may not be able to meet the combination of add-ons that can be provided by the supplier contract, so there may be a conflict between the add-on combination and the physical examination package.

[0003] In view of the above reasons, it is necessary to propose a method for generating physical examination orders, which can meet the personalized needs of users while avoiding conflicts between additional item combinations and physical examination packages, that is, the combination items that meet the user's selection are within the scope supported by the contract. Summary of the invention

[0004] The present application provides a physical examination order generation method, a physical examination order generation device, a computer device and a computer-readable storage medium, which aim to avoid conflicts between additional item combinations and physical examination packages, and thus generate a physical examination order that can meet the personalized needs of users.

[0005] To achieve the above objectives, the present application provides a method for generating a physical examination order, comprising:

[0006] Obtaining target physical examination packages and target additional item package information, wherein the target additional item package information includes several additional item packages selected by the user;

[0007] Extracting features from the target added item package information, arranging the target added item package according to a preset rule, and generating a search feature value corresponding to the target added item package information;

[0008] Using the search feature value to perform matching in a project database to obtain a matching result, wherein the project database includes a plurality of initial physical examination packages and search feature values ​​of a plurality of optional initial additional item packages corresponding to the initial physical examination packages;

[0009] In response to the matching result being a successful match, a target physical examination order is generated based on the target additional item package information and the target physical examination package.

[0010] To achieve the above objectives, the present application also provides a physical examination order generating device, comprising:

[0011] An acquisition module, used to acquire target physical examination packages and target additional item package information, wherein the target additional item package information includes several additional item packages selected by users;

[0012] A feature extraction module, used to extract features from the target added item package information, arrange the target added item package according to a preset rule, and generate a search feature value corresponding to the target added item package information;

[0013] A matching module, used to use the search feature value to match in a project database to obtain a matching result, wherein the project database includes a plurality of initial physical examination packages and search feature values ​​of a plurality of optional initial additional item packages corresponding to the initial physical examination packages;

[0014] A physical examination order generating module is used to generate a target physical examination order based on the target additional item package information and the target physical examination package in response to the matching result being a successful match.

[0015] In addition, to achieve the above-mentioned purpose, the present application also provides a computer device, which includes a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program and implement the steps of the physical examination order generation method provided in any one of the embodiments of the present application when executing the computer program.

[0016] In addition, to achieve the above-mentioned purpose, the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processor implements the steps of the physical examination order generation method described in any one of the embodiments of the present application.

[0017] The present application discloses a method for generating a physical examination order, a physical examination order generating device, a computer device and a computer-readable storage medium. The method includes obtaining a target physical examination package and a target additional item package information, wherein the target additional item package information includes additional item packages selected by several users. Further, the target additional item package information can be feature extracted, and the target additional item package is arranged according to a preset rule to generate a retrieval feature value corresponding to the target additional item package information. Thus, the retrieval feature value can be used to match in the project database to obtain a matching result, wherein the project database includes several initial physical examination packages and retrieval feature values ​​of several optional initial additional item packages corresponding to the initial physical examination package. Finally, in response to the matching result being a successful match, a target physical examination order can be generated based on the target additional item package information and the target physical examination package. The present application extracts features from the target additional item package information and generates retrieval feature values ​​according to preset rules, so that the organization of the target additional item package information is more standardized and efficient. By matching the retrieval feature value in the project database, the physical examination package and its additional item package combination that meet the user's needs can be quickly and accurately determined. In addition, this method not only improves matching efficiency, but also effectively reduces human errors and improves user experience. At the same time, by automatically generating target physical examination orders based on matching results, the intelligent configuration of physical examination packages is realized, which helps to meet the diverse needs of users and improve the accuracy and satisfaction of services. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 This is a scenario diagram of a method for generating a physical examination order provided in an embodiment of the present application;

[0020] Figure 2 It is a flowchart of a method for generating a physical examination order provided in an embodiment of the present application;

[0021] Figure 3 is a schematic block diagram of a physical examination order generating device provided in an embodiment of the present application;

[0022] Figure 4 It is a schematic block diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0024] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor do they have to be executed in the order described. For example, some operations / steps can also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions. In addition, although the functional modules are divided in the device schematic, in some cases, the module division can be different from that in the device schematic.

[0025] The term "and / or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0026] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0027] like Figure 1 As shown, the physical examination order generation method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. The application environment includes a terminal device 110 and a server 120, wherein the terminal device 110 can communicate with the server 120 through a network. Specifically, the server 120 can include a method for obtaining a target physical examination package and a target additional item package information, wherein the target additional item package information includes additional item packages selected by several users. Further, the target additional item package information can be feature extracted, and the target additional item package is arranged according to a preset rule to generate a retrieval feature value corresponding to the target additional item package information. Thus, the retrieval feature value can be used to match in the project database to obtain a matching result, wherein the project database includes several initial physical examination packages, and the retrieval feature values ​​of several optional initial additional item packages corresponding to the initial physical examination package. Finally, in response to the matching result being a successful match, a target physical examination order can be generated based on the target additional item package information and the target physical examination package, thereby sending the target physical examination package to the terminal device 110. Among them, the server 120 can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms. The terminal device 110 can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, etc., but is not limited to this. The terminal and the server can be directly or indirectly connected via wired or wireless communication, and this application does not limit this.

[0028] Please continue reading Figure 2 , Figure 2 Schematic diagram of a method for generating a physical examination order provided in an embodiment of the present application. Figure 2 As shown, the physical examination order generation method can be implemented through steps S11 to S14.

[0029] Step S11: Obtain target physical examination package and target additional item package information.

[0030] The target additional item package information includes several additional item packages selected by the user.

[0031] For example, the target physical examination package is used to represent the basic physical examination service set selected by the user, which usually includes a series of routine physical examination items, such as blood test, liver function test, electrocardiogram, etc. Among them, the target physical examination package can be one selected by the user from multiple physical examination packages provided by the platform or service provider, or it can be a default package recommended by the system based on the user's basic information (such as age, gender, health status), and this application does not limit this.

[0032] For example, the target additional item package is a set of physical examination item packages selected by the user in addition to the target physical examination package. The target additional item package is used to meet the personalized needs of the user, such as specific disease screening, in-depth health examination, etc.

[0033] The above implementation methods can obtain the target physical examination package and target additional item package information, lay a data foundation for accurate matching and package generation, and ensure the personalization and efficiency of the service.

[0034] Step S12: extracting features from the target added item package information, arranging the target added item packages according to preset rules, and generating search feature values ​​corresponding to the target added item package information.

[0035] Feature extraction refers to extracting key attributes from the target item package information selected by the user and converting them into structured data that can be understood and processed by computers. The retrieval feature value is the unique identifier finally generated for database matching. Its core purpose is to simplify the complex item package information into a unified and comparable form.

[0036] For example, core words can be extracted from the name and content description of the add-on package, and then the information features of the add-on package can be extracted and converted into a multi-dimensional feature vector, such as category, price and priority are mapped to corresponding numerical values. Thus, the category and attributes of the add-on package can be marked according to preset rules to facilitate subsequent arrangement and matching.

[0037] It should be noted that the present application does not limit the method of feature extraction operation, for example, natural language processing or database query and rule engine etc. are included to realize feature extraction of target item package.

[0038] For example, preset rules include but are not limited to the following methods: multi-level sorting (for example, first classify by category, then sort by priority); rule encoding (for example, use fixed logical rules to arrange the added item packages); algorithm optimization (for example, use sorting algorithms such as quick sort to achieve efficient arrangement).

[0039] The above implementation methods can standardize and structure the information of the additional item packages selected by the user, generate unique retrieval feature values, ensure that complex user needs can be quickly and accurately identified and processed by the system, and provide efficient support for subsequent matching operations.

[0040] Step S13: Use the search feature value to perform matching in the project database to obtain matching results.

[0041] The project database includes several initial physical examination packages and retrieval feature values ​​of several optional initial additional item packages corresponding to the initial physical examination packages.

[0042] For example, the search feature value (such as a coded form or a hash value) can be generated by the target physical examination package and the additional package selected by the user. Since the search feature value carries the detailed information of the user's needs, including category, priority, price, etc., the search feature value can be compared with the feature values ​​in the project database one by one to obtain a matching result.

[0043] The above implementation methods can utilize the retrieval feature values ​​for efficient matching, providing users with physical examination plans that are highly consistent with their needs, and ensuring the accuracy and efficiency of the service.

[0044] Step S14: In response to the matching result being a successful match, a target physical examination order is generated based on the target additional item package information and the target physical examination package.

[0045] It should be understood that if the matching result is a successful match, it means that there is no conflict between the target additional item package information and the target physical examination package, and they can constitute a complete solution. Therefore, a target physical examination order can be generated based on the target additional item package information and the target physical examination package.

[0046] The above implementation methods can organically combine user needs with existing resources to generate available target physical examination packages, which not only improves user satisfaction but also optimizes service efficiency.

[0047] The physical examination order generation method disclosed in the embodiment of the present application includes obtaining a target physical examination package and a target additional item package information, wherein the target additional item package information includes several additional item packages selected by users. Further, the target additional item package information can be feature extracted, and the target additional item package is arranged according to a preset rule to generate a search feature value corresponding to the target additional item package information. Thus, the search feature value can be used to match in the project database to obtain a matching result, wherein the project database includes several initial physical examination packages and the search feature values ​​of several optional initial additional item packages corresponding to the initial physical examination package. Finally, in response to the matching result being a successful match, a target physical examination order can be generated based on the target additional item package information and the target physical examination package. The present application extracts features from the target additional item package information and generates a search feature value according to a preset rule, so that the organization of the target additional item package information is more standardized and efficient. By matching the search feature value in the project database, the physical examination package and its additional item package combination that meet the user's needs can be quickly and accurately determined. In addition, the method not only improves the matching efficiency, but also effectively reduces human errors and improves the user experience. At the same time, by automatically generating target physical examination orders based on matching results, the intelligent personalized configuration of physical examination packages is realized, which helps to meet the diverse needs of users and improve the accuracy and satisfaction of services.

[0048] Optionally, feature extraction is performed on the target plus item package information, including: preprocessing the target plus item package information to obtain preprocessed target plus item package information; feature extraction is performed on the preprocessed target plus item package information to obtain a target identification code corresponding to the target plus item package information.

[0049] Specifically, at least one preprocessing operation of removing stop words, removing punctuation marks, and removing special characters can be performed on the target plus package information, and the preprocessed target plus package information can be obtained to prevent invalid data from affecting the subsequent feature extraction of the target plus package information. Further, the preprocessed target text can be encoded and other feature extraction operations can be performed to obtain the target identification code corresponding to the target plus package information.

[0050] In the above manner, by performing preprocessing operations and feature extraction operations on the target text, the target identification code corresponding to the target added item package information can be determined, thereby providing a basis for the subsequent matching process.

[0051] Optionally, the target plus item package is arranged according to preset rules to generate a retrieval feature value corresponding to the target plus item package information, including: sorting the target identification code in order of priority to obtain the sorted target identification code; dividing the sorted target identification code by a preset separator to generate a retrieval feature value corresponding to the target plus item package information.

[0052] For example, the identification codes of the target item packages can be sorted according to preset rules (such as priority) to ensure that the generated retrieval feature values ​​are unique and consistent, thereby avoiding matching failures caused by different orders. For example, the target item packages include cardiovascular screening packages (identification code `101`, priority `2`), tumor screening packages (identification code `102`, priority `1`) and diabetes screening packages (identification code `103`, priority `3`). The sorted target identification codes include: `102` (priority 1) → `101` (priority 2) → `103` (priority 3).

[0053] For example, in order to generate a standardized string that is easy to store, transmit and match, a specific symbol (such as `|`, `,`) can also be predefined as a separator between identification codes. For example, the sorted target identification codes are `102`, `101`, and `103`. After using `|` as a separator, a string is generated: `102|101|103`, and it is used as the retrieval feature value corresponding to the target added item package information.

[0054] In the above implementation, the search feature values ​​generated by sorting the target identification codes and encoding the separators ensure fast and accurate matching of user requirements with database information. The above method not only realizes automatic matching, but also improves the efficiency and flexibility of the system.

[0055] Optionally, the retrieval feature value is used to match in the project database to obtain a matching result, including: determining the similarity value between the retrieval feature value and the project database through a cosine similarity algorithm; in response to the similarity value being greater than or equal to a preset similarity value, determining the matching result to be a matching failure; and, in response to the similarity value being less than a preset similarity value, determining the matching result to be a matching success.

[0056] Among them, cosine similarity is used to measure the similarity between two eigenvalues ​​in a multidimensional vector space. The preset similarity value is used to determine whether the matching degree of two eigenvalues ​​reaches the required threshold. For example, the preset similarity value is 0.9, 0.95, etc., which is not limited in the embodiment of the present application, and the preset similarity value of 0.9 is used as an example for explanation.

[0057] For example, if the similarity value is less than 0.9, the matching result is determined to be a successful match; if the similarity value is greater than or equal to 0.9, the matching result is determined to be a failed match.

[0058] The above implementation method uses the cosine similarity algorithm for matching, which can significantly improve the matching flexibility and user experience. Through the preset similarity threshold, the matching standard can be accurately controlled to meet the different requirements of strict matching and loose matching.

[0059] Optionally, the similarity value between the retrieval feature value and the project database is determined by a cosine similarity algorithm, including: vectorizing the retrieval feature value through a bag-of-words model to obtain a target vector representation; traversing the project database and determining the initial similarity between the target vector representation and the project database; and determining the maximum value of the initial similarities as the similarity value.

[0060] Among them, the bag-of-words model is a text feature representation method used to convert a group of words or identifiers into a numerical vector.

[0061] For example, the bag-of-words model can be used to map the identifiers of the retrieval feature values ​​into the vocabulary according to their contents, and the number of occurrences of each identifier can be counted to generate a target vector representation. Furthermore, the cosine similarity algorithm can be used to calculate the similarity between the retrieval target vector representation and the database feature value vector one by one, and the maximum value can be selected as the final similarity value between the retrieval feature value and the project database.

[0062] In the above implementation, the retrieval feature value and the item database feature value are vectorized through the bag-of-words model, and the cosine similarity algorithm is used to calculate the similarity, thereby effectively achieving matching. By selecting the maximum similarity value, the system can accurately determine the closest matching result, which is suitable for the flexible selection scenario of adding item packages in the physical examination package.

[0063] Optionally, after matching in the project database using the retrieval feature value to obtain the matching result, it also includes: in response to the matching result being a matching failure, generating recommended added item package information based on the target added item package information using an intelligent recommendation algorithm; displaying the recommended added item package information through a display page; or, in response to the matching result being a matching failure, displaying the matching result through a display page.

[0064] For example, after the retrieval feature value fails to match the project database, the intelligent recommendation algorithm can be used to generate recommended additional package information based on the target additional package information and displayed on the display page to help users quickly find additional packages that are close to their needs; or the page can directly prompt the matching failure result to guide the user to adjust the selection or obtain further help.

[0065] The above implementation methods not only improve the user experience in the event of matching failure and avoid user loss due to no matching results, but also effectively improve the accuracy and convenience of the service through the intelligent recommendation algorithm, and enhance the user's trust and satisfaction with the system.

[0066] In an embodiment of the present application, the training data set and the annotation results can be input into the CRF model for supervised learning, and then trained to obtain the iterative target deep learning model.

[0067] Optionally, an intelligent recommendation algorithm is used to generate recommended added item package information based on the target added item package information, including: obtaining historical order data, and determining user behavior information based on the historical order data; analyzing the target added item package information and user behavior information through an intelligent recommendation algorithm to obtain recommended added item package information, wherein the recommended added item package information and the target added item package information have at least one identical added item package.

[0068] In an embodiment of the present application, the target deep learning model is repeatedly trained by using a stochastic gradient descent algorithm so that the loss function is continuously reduced to obtain the target deep learning model after iteration.

[0069] See also Figure 3 , Figure 3 This is a schematic block diagram of a physical examination order generation device provided in an embodiment of the present application. The physical examination order generation device can be configured in a server to execute the above-mentioned physical examination order generation method.

[0070] like Figure 3 As shown, the physical examination order generating device 200 includes: an acquisition module 201, a feature extraction module 202, a matching module 203 and a physical examination order generating module 204.

[0071] The acquisition module 201 is used to acquire target physical examination packages and target additional item package information, wherein the target additional item package information includes several additional item packages selected by the user;

[0072] A feature extraction module 202 is used to extract features from the target added item package information, and arrange the target added item package according to a preset rule to generate a search feature value corresponding to the target added item package information;

[0073] A matching module 203 is used to use the search feature value to perform matching in a project database to obtain a matching result, wherein the project database includes a plurality of initial physical examination packages and search feature values ​​of a plurality of optional initial additional item packages corresponding to the initial physical examination packages;

[0074] The physical examination order generating module 204 is used to generate a target physical examination order based on the target additional item package information and the target physical examination package in response to the matching result being a successful match.

[0075] The feature extraction module 202 is further used to perform a preprocessing operation on the target plus item package information to obtain the preprocessed target plus item package information; perform feature extraction on the preprocessed target plus item package information to obtain a target identification code corresponding to the target plus item package information.

[0076] The feature extraction module 202 is further used to sort the target identification codes according to the priority order to obtain sorted target identification codes; segment the sorted target identification codes by a preset separator to generate a retrieval feature value corresponding to the target plus item package information.

[0077] The matching module 203 is also used to determine the similarity value between the retrieval feature value and the project database through a cosine similarity algorithm; in response to the similarity value being greater than or equal to a preset similarity value, determine that the matching result is a matching failure; and, in response to the similarity value being less than the preset similarity value, determine that the matching result is a matching success.

[0078] The matching module 203 is also used to vectorize the retrieval feature value through the bag-of-words model to obtain a target vector representation; traverse the project database and determine the initial similarity between the target vector representation and the project database; and determine the maximum value of the initial similarities as the similarity value.

[0079] The matching module 203 is also used to generate recommended item package information based on the target item package information using an intelligent recommendation algorithm in response to the matching result being a matching failure; display the recommended item package information through a display page; or, in response to the matching result being a matching failure, display the matching result through the display page.

[0080] The matching module 203 is also used to obtain historical order data and determine user behavior information based on the historical order data; analyze the target additional item package information and the user behavior information through the intelligent recommendation algorithm to obtain the recommended additional item package information, wherein the recommended additional item package information and the target additional item package information have at least one identical additional item package.

[0081] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and modules and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0082] The method and apparatus of the present application can be used in many general or special computing system environments or configurations, such as personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer terminal devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices.

[0083] Exemplarily, the above method and apparatus may be implemented in the form of a computer program. The computer program may be implemented in Figure 4 Runs on the computer device shown.

[0084] See also Figure 4 , Figure 4 1 is a schematic diagram of a computer device provided in an embodiment of the present application. The computer device may be a server.

[0085] like Figure 4 As shown, the computer device includes a processor, a memory and a network interface connected through a system bus, wherein the memory may include a volatile storage medium, a non-volatile storage medium and an internal memory.

[0086] The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can execute any one of the physical examination order generation methods.

[0087] The processor is used to provide computing and control capabilities and support the operation of the entire computer equipment.

[0088] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can execute any one of the physical examination order generation methods.

[0089] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art can understand that the structure of the computer device is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0090] It should be understood that the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0091] Among them, in some embodiments, the processor is used to obtain a target physical examination package and a target additional item package information, wherein the target additional item package information includes several additional item packages selected by the user; perform feature extraction on the target additional item package information, and arrange the target additional item packages according to preset rules to generate a retrieval feature value corresponding to the target additional item package information; use the retrieval feature value to match in a project database to obtain a matching result, wherein the project database includes several initial physical examination packages and several optional initial additional item packages corresponding to the initial physical examination packages; in response to the matching result being a successful match, generate a target physical examination order based on the target additional item package information and the target physical examination package.

[0092] In some embodiments, the processor is further used to perform a preprocessing operation on the target plus item package information to obtain preprocessed target plus item package information; perform feature extraction on the preprocessed target plus item package information to obtain a target identification code corresponding to the target plus item package information.

[0093] In some embodiments, the processor is further used to sort the target identification codes in order of priority to obtain sorted target identification codes; segment the sorted target identification codes by a preset separator to generate a retrieval feature value corresponding to the target plus item package information.

[0094] In some embodiments, the processor is also used to determine the similarity value between the retrieval feature value and the project database through a cosine similarity algorithm; in response to the similarity value being greater than or equal to a preset similarity value, determine that the matching result is a matching failure; and, in response to the similarity value being less than the preset similarity value, determine that the matching result is a matching success.

[0095] In some embodiments, the processor is further used to vectorize the retrieval feature value through a bag-of-words model to obtain a target vector representation; traverse the project database and determine the initial similarity between the target vector representation and the project database; and determine the maximum value of the initial similarities as the similarity value.

[0096] In some embodiments, the processor is also used to generate recommended item package information based on the target item package information using an intelligent recommendation algorithm in response to the matching result being a matching failure; display the recommended item package information through a display page; or, in response to the matching result being a matching failure, display the matching result through the display page.

[0097] In some embodiments, the processor is also used to obtain historical order data and determine user behavior information based on the historical order data; the target additional item package information and the user behavior information are analyzed by the intelligent recommendation algorithm to obtain the recommended additional item package information, wherein the recommended additional item package information and the target additional item package information have at least one identical additional item package.

[0098] An embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. The computer program includes program instructions, and when the program instructions are executed, any one of the physical examination order generation methods provided in the embodiments of the present application is implemented.

[0099] The computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiment, such as a hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc., equipped on the computer device.

[0100] Furthermore, the computer-readable storage medium may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like.

[0101] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for generating a physical examination order, characterized in that: The method comprises: Obtaining target physical examination packages and target additional item package information, wherein the target additional item package information includes several additional item packages selected by the user; Extracting features from the target added item package information, arranging the target added item package according to a preset rule, and generating a search feature value corresponding to the target added item package information; Using the search feature value to perform matching in a project database to obtain a matching result, wherein the project database includes a plurality of initial physical examination packages and search feature values ​​of a plurality of optional initial additional item packages corresponding to the initial physical examination packages; In response to the matching result being a successful match, a target physical examination order is generated based on the target additional item package information and the target physical examination package.

2. The method according to claim 1, characterized in that The feature extraction of the target added item package information includes: Performing a preprocessing operation on the target added item package information to obtain the preprocessed target added item package information; Feature extraction is performed on the preprocessed target item package information to obtain a target identification code corresponding to the target item package information.

3. The method according to claim 2, characterized in that The step of arranging the target added item packages according to a preset rule and generating a search feature value corresponding to the target added item package information includes: Sorting the target identification codes in order of priority to obtain sorted target identification codes; The sorted target identification codes are segmented by a preset separator to generate a search feature value corresponding to the target added item package information.

4. The method according to claim 1, characterized in that The using the search feature value to match in the project database to obtain a matching result includes: Determining the similarity value between the retrieval feature value and the project database by using a cosine similarity algorithm; In response to the similarity value being greater than or equal to a preset similarity value, determining that the matching result is a matching failure; and, In response to the similarity value being less than the preset similarity value, determining the matching result as the matching success.

5. The method according to claim 4, characterized in that Determining the similarity value between the search feature value and the project database by using a cosine similarity algorithm includes: Vectorizing the retrieval feature value through a bag-of-words model to obtain a target vector representation; Traversing the item database and determining an initial similarity between the target vector representation and the item database; The maximum value among the initial similarities is determined as the similarity value.

6. The method according to claim 1, characterized in that After matching the search feature value in the project database and obtaining the matching result, the method further includes: In response to the matching result being a match failure, generating recommended additional item package information according to the target additional item package information using an intelligent recommendation algorithm; Displaying the recommended additional item package information by displaying a page; or, In response to the matching result being the matching failure, displaying the matching result through the display page.

7. The method according to claim 6, characterized in that The step of generating the recommended additional item package information according to the target additional item package information by using an intelligent recommendation algorithm includes: Acquire historical order data, and determine user behavior information based on the historical order data; The target additional item package information and the user behavior information are analyzed by the intelligent recommendation algorithm to obtain the recommended additional item package information, wherein the recommended additional item package information and the target additional item package information have at least one identical additional item package.

8. A physical examination order generating device, characterized in that: The physical examination order generating device comprises: An acquisition module, used to acquire target physical examination packages and target additional item package information, wherein the target additional item package information includes several additional item packages selected by users; A feature extraction module, used to extract features from the target added item package information, arrange the target added item package according to a preset rule, and generate a search feature value corresponding to the target added item package information; A matching module, used to use the search feature value to match in a project database to obtain a matching result, wherein the project database includes a plurality of initial physical examination packages and search feature values ​​of a plurality of optional initial additional item packages corresponding to the initial physical examination packages; A physical examination order generating module is used to generate a target physical examination order based on the target additional item package information and the target physical examination package in response to the matching result being a successful match.

9. A computer device, characterized in that: include: A memory and a processor; wherein the memory is connected to the processor and is used to store a program; the processor is used to implement the steps of the physical examination order generation method as described in any one of claims 1 to 7 by running the program stored in the memory.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements the steps of the physical examination order generation method according to any one of claims 1 to 7.

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