Physical examination information recommendation method, device and system and storage medium

Abstract

The invention provides a physical examination information recommendation method, device and system and a storage medium, relates to the technical field of medical data processing, and aims to at least solve the problem that in the related technology, a physical examination package is added and cannot accurately reflect the needs of a physical examination user. The method comprises the following steps: extracting physical examination associated information of a physical examination user according to information extraction processes corresponding to various preset recommendation modes to obtain a plurality of physical examination information extraction results; obtaining a plurality of candidate physical examination recommendation items according to the plurality of physical examination information extraction results; and selecting a target physical examination item different from the existing physical examination items in the target physical examination package of the physical examination user from the plurality of candidate physical examination recommendation items, so as to take the target physical examination item as a physical examination item package and recommend the physical examination item package to a user terminal of the physical examination user.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of medical data processing, and particularly relates to a physical examination information recommendation method and device, a system and a storage medium. BACKGROUND

[0002] With the continuous improvement of living standards, people pay more and more attention to their own health. Regular physical examination has become the most effective way of health management. At present, in order to facilitate the screening of physical examination items by physical examination users, physical examination items with an association relationship are summarized and classified to set different physical examination packages. However, the physical examination items of the physical examination package cannot meet the arbitrary examination needs of all users, so further, a physical examination add-on package is set for physical examination users to make personalized selection, but the physical examination items of the physical examination add-on package are usually selected by searching after the physical examination users input relevant demand information, and only according to the information dimension of the information recognized by the user itself, the information dimension of the physical examination items of the physical examination add-on package is relatively single, so that the add-on physical examination package cannot accurately reflect the needs of the physical examination users. SUMMARY

[0003] The present disclosure provides a physical examination information recommendation method, device and storage medium to at least solve the problem that the add-on physical examination package cannot accurately reflect the needs of the physical examination users in the related art. The technical solution of the present disclosure is as follows:

[0004] According to a first aspect of an embodiment of the present disclosure, a physical examination information recommendation method is provided, which includes: extracting physical examination association information of a physical examination user according to information extraction processes corresponding to a plurality of preset recommendation modes respectively, to obtain a plurality of physical examination information extraction results; obtaining a plurality of candidate physical examination recommendation items according to the plurality of physical examination information extraction results; selecting target physical examination items different from existing physical examination items in a target physical examination package of the physical examination user from the plurality of candidate physical examination recommendation items, to recommend the target physical examination items as a physical examination add-on package to a user terminal of the physical examination user.

[0005] In an implementation manner, before the extracting the physical examination association information of the physical examination user according to the information extraction processes corresponding to the plurality of preset recommendation modes respectively, to obtain the plurality of physical examination information extraction results, the method further includes: determining a target recommendation priority of the plurality of preset recommendation modes according to a user type and user information of the physical examination user; the target priority represents an order of recommending the plurality of preset recommendation modes to the user.

[0006] In another implementation manner, the health examination associated information of the health examination user is extracted according to information extraction processes corresponding to the plurality of preset recommendation manners respectively, and a plurality of health examination information extraction results are obtained, including: determining a total online quantity of the health examination user; in a case where the total online quantity is greater than a preset quantity, a plurality of preset recommendation manners are sequentially called according to a target recommendation priority, and the health examination associated information corresponding to the health examination user is sequentially extracted in sequence, and one health examination information extraction result in the plurality of health examination information extraction results is sequentially obtained.

[0007] In another implementation manner, the method further includes: generating at least one candidate health examination recommendation item according to one health examination information extraction result extracted each time; comparing the at least one candidate health examination recommendation item with existing health examination items of the target health examination package each time when the at least one candidate health examination recommendation item is generated each time; taking a candidate health examination item different from the existing health examination items in the at least one candidate health examination recommendation item generated each time as a sub-add-on package of the health examination add-on package, and recommending the sub-add-on package to a user terminal of the health examination user.

[0008] In another implementation manner, the plurality of preset recommendation manners include a report recommendation manner, an abnormal index recommendation manner, a questionnaire recommendation manner, a family doctor recommendation manner, and an artificial intelligence model recommendation manner; the artificial intelligence model recommendation manner includes a preset model; the preset model represents an association relationship between multi-dimensional health examination index information and abnormal health examination items, and the preset model is trained based on sample data, and the sample data includes user physiological feature information, historical health examination report information, user basic attribute information, user this-time selected this-time health examination package information, and abnormal index health examination items.

[0009] In another implementation, according to the user type and the user information of the physical examination user, a target recommendation priority of a plurality of preset recommendation modes is determined, including: determining that the user type is a first preset type and the user information includes historical physical examination report information, arranging the priority sequence of the following preset recommendation modes, sequentially reducing the priority parameters of each preset recommendation mode, and setting the target recommendation priority: family doctor recommendation mode, abnormal index recommendation mode, questionnaire recommendation mode, report recommendation mode, and artificial intelligence model recommendation mode; the priority parameter is positively correlated with the priority; determining that the user type is the first preset type and the user information does not include the historical physical examination report information, arranging the priority sequence of the following preset recommendation modes, and setting the target recommendation priority with the priority parameters sequentially reduced: family doctor recommendation mode, abnormal index recommendation mode, questionnaire recommendation mode, report recommendation mode, and artificial intelligence model recommendation mode, and setting the priority parameters of the report recommendation mode and the artificial intelligence model recommendation mode to 0; the priority parameter of 0 represents that the corresponding preset recommendation mode is not called; determining that the user type is a second preset type, arranging the priority sequence of the following preset recommendation modes, and setting the target recommendation priority with the priority parameters sequentially reduced: artificial intelligence model recommendation mode, report recommendation mode, abnormal index recommendation mode, family doctor recommendation mode, and questionnaire recommendation mode.

[0010] In another implementation, before the physical examination associated information of the physical examination user is extracted according to the information extraction process corresponding to each of the plurality of preset recommendation modes to obtain a plurality of physical examination information extraction results, the method further includes: screening a target recommendation mode from the plurality of preset recommendation modes, which interacts with the physical examination user; associating preset interactive question and answer information related to the physical examination index with the target recommendation mode, and sending the preset interactive question and answer information to the user terminal of the physical examination user; and accepting the target input information of the preset interactive question and answer information returned by the user terminal of the physical examination user, to extract the physical examination associated information from the target input information.

[0011] According to a second aspect of the embodiment of the present application, a physical examination information recommendation device is provided, which includes: an extraction unit configured to extract physical examination associated information of a physical examination user according to an information extraction process corresponding to each of a plurality of preset recommendation modes, to obtain a plurality of physical examination information extraction results; a determination unit configured to obtain a plurality of candidate physical examination recommendation items according to the plurality of physical examination information extraction results; and a screening unit configured to select a target physical examination item different from an existing physical examination item in a target physical examination package of the physical examination user from the plurality of candidate physical examination recommendation items, to recommend the target physical examination item as a physical examination add-on package to a user terminal of the physical examination user.

[0012] According to a third aspect of the embodiment of the present application, a physical examination information recommendation device is provided, which has a photographing function and is configured to perform the physical examination information recommendation method according to the first aspect and any possible implementation thereof.

[0013] According to a fourth aspect of the embodiments of the present application, a computer readable storage medium is provided, and the computer readable storage medium has instructions stored thereon, and when the instructions in the computer readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the physical examination information recommendation method according to the first aspect and any possible implementation manner thereof.

[0014] According to a fifth aspect of the embodiments of the present application, a computer program product is provided, and the computer program product includes computer instructions, and when the computer instructions are run on an electronic device, the electronic device performs the physical examination information recommendation method according to the first aspect and any possible implementation manner thereof.

[0015] The embodiments of the present application provide at least the following beneficial effects: different recommendation modes are respectively set for different dimensions of user information obtained through different channels, and different dimensions of physical examination related information according to which different recommendation modes are extracted are unified, so as to generate different candidate physical examination items according to the physical examination related information, so as to select target physical examination items other than physical examination packages, and recommend to physical examination users. Based on this, the recommended target physical examination items are generated based on multi-dimensional physical examination index information of different information channels, can more comprehensively reflect physical examination needs of physical examination users from different dimensions, improve the accuracy of physical examination add-on packages, so that physical examination users adopt physical examination add-on packages and physical examination packages for physical examination, and obtain more accurate physical examination results.

[0016] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0017] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the present disclosure and, together with the specification, serve to explain the principles of the present disclosure, and do not constitute an undue limitation on the present disclosure.

[0018] Figure 1 is a schematic diagram of a physical examination information recommendation system according to an exemplary embodiment;

[0019] Figure 2 is a flowchart of a physical examination information recommendation method according to an exemplary embodiment;

[0020] Figure 3 is a block diagram of a physical examination information recommendation device according to an exemplary embodiment;

[0021] Figure 4 is a schematic diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0022] In order for those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be described clearly and completely below in conjunction with the drawings.

[0023] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Rather, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0024] Before the physical examination information recommendation method provided by the embodiments of the present application is described in detail, the application scenarios and implementation environments involved in the embodiments of the present application are briefly introduced.

[0025] First, the application scenarios involved in the present application are briefly introduced.

[0026] With the continuous improvement of living standards, people pay more and more attention to their own health. Regular physical examination has become the most effective way of health management. Currently, in order to facilitate the selection of physical examination items by physical examination users, physical examination items with associated relationships are summarized and classified to set different physical examination packages. However, the physical examination items of the physical examination package cannot meet the arbitrary examination needs of all users, so further, physical examination add-on packages are set for physical examination users to make personalized selection, but the physical examination items of the physical examination add-on package are usually selected by searching after the physical examination users input the relevant demand information, and are generated only according to the information dimension of the information recognized by the users themselves. The information dimension of the physical examination items of the physical examination add-on package is relatively single, so that the add-on physical examination package cannot accurately reflect the physical examination needs of the physical examination users.

[0027] In view of the above problems, the present application provides a physical examination information recommendation method, which sets different recommendation modes for different dimensions of user information obtained from different channels, and uniformly extracts different dimensions of physical examination associated information according to different recommendation modes, to generate different candidate physical examination items according to the physical examination associated information, so as to select target physical examination items other than physical examination packages for recommendation to physical examination users. Based on this, the recommended target physical examination items are generated based on multi-dimensional physical examination index information from different information channels, which can more comprehensively reflect the physical examination needs of the physical examination users from different dimensions, improve the accuracy of the physical examination add-on package, so that the physical examination users can use the physical examination add-on package and the physical examination package for physical examination, and obtain more accurate physical examination results.

[0028] Next, the implementation architecture involved in this application is briefly introduced below.

[0029] Figure 1 Schematic diagram of a physical examination information recommendation system 10 provided by the present disclosure. Figure 1 As shown, the physical examination information recommendation system 10 includes a server 101 and a user terminal 102. The server 101 and the user terminal 102 can be connected via a wired network or a wireless network.

[0030] In some embodiments, the user end 102 may be a terminal device.

[0031] The user undergoing a physical examination selects a physical examination package through the user terminal 102. The server 101 determines the first priority of multiple preset recommendation methods based on the user type of the physical examination user, and pushes the interactive interface and interactive question and answer information associated with the multiple preset recommendation methods to the user terminal 102 in the order of the first priority, so that the physical examination user returns the physical examination-related information through the user terminal 102. The server 101 receives the physical examination-related information returned by the user terminal 102, and determines the second priority of the multiple preset recommendation methods based on the physical examination-related information and the user type. According to the second priority, the server 101 sequentially calls the physical examination-related information corresponding to the multiple preset recommendation methods, sequentially generates the corresponding sub-physical examination and package items, and sends them to the user terminal 102 in order.

[0032] In some embodiments, the server 101 includes a database or is connected to a database, and the medical examination information and medical examination packages can be stored in the database. The user terminal 102 can access the corresponding medical examination packages and medical examination information through the server 101.

[0033] In other embodiments, the server 101 may be a single server, or a server cluster consisting of multiple servers. In some implementations, the server cluster may also be a distributed cluster. This application does not limit the specific implementation of the server 101.

[0034] The terminal device can be a mobile phone, a tablet computer, a desktop computer, a laptop computer, a handheld computer, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, a cellular phone, a personal digital assistant (PDA), an augmented reality (AR) \ virtual reality (VR) device, or the like, which can install and use a content community application (such as Kuaishou), and the specific form of the terminal device is not specially limited in the present disclosure. It can interact with the user through one or more ways such as a keyboard, a touchpad, a touch screen, a remote controller, voice interaction, or a handwriting device.

[0035] The server 101 can be connected with at least one mobile device. Moreover, the number and type of the terminal device are not limited in the present application.

[0036] The health examination information recommendation method provided by the embodiments of the present application can be applied to the health examination information recommendation system in the implementation architecture shown in the foregoing Figure 1 To facilitate understanding, the health examination information recommendation method provided by the present application is specifically introduced below in combination with the accompanying drawings.

[0037] Figure 2 is a flowchart of a health examination information recommendation method according to an exemplary embodiment. As shown in Figure 2 The health examination information recommendation method includes the following steps.

[0038] S21, extracting health examination associated information of the health examination user according to an information extraction process corresponding to each of a plurality of preset recommendation modes, to obtain a plurality of health examination information extraction results.

[0039] The plurality of preset recommendation modes include a report recommendation mode, an abnormal index recommendation mode, a questionnaire recommendation mode, a family doctor recommendation mode, and an artificial intelligence model recommendation mode.

[0040] In some embodiments, the health examination add-on package is referred to as an add-on package.

[0041] The report recommendation mode includes extracting health examination associated information associated with the health examination item from the historical health examination report of the health examination user.

[0042] For example, if the user has a medical examination record and has authorized a report, the report will be marked according to the report, such as obesity, lumbar disc herniation and other health abnormalities. The examination package will also be marked with the corresponding health abnormality mark when configuring. When the abnormality mark in the user's report matches any abnormality mark on the add-on package list, the add-on package will be recommended and placed at the top, and the user will be informed that according to your historical medical examination report, the following add-on package examination is recommended.

[0043] The abnormal index recommendation method includes extracting the medical examination associated information associated with the medical examination item from the abnormal index information input by the medical examination user.

[0044] For example, when the user feels that he or she has some discomfort or needs some symptom corresponding examination, the user can select the abnormal mark, and after selecting, the add-on package matching the abnormal mark is queried according to the abnormal mark selected by the user, and the add-on package is recommended and placed at the top, and the user is informed that according to the abnormal mark selected by you, the following add-on package examination is recommended.

[0045] The questionnaire recommendation method includes extracting the medical examination associated information associated with the medical examination item from the pre-set questionnaire information of the medical examination user.

[0046] For example, the user can also choose to fill in the prepared questionnaire survey. The answers to the questions in the questionnaire survey will correspond to some abnormal marks. For example, the questionnaire will ask the user: Do you have any bad living habits? When the user chooses to smoke, it is equivalent to selecting the abnormal mark of lung abnormality. After the user answers, the corresponding add-on package is matched according to the answer, and the add-on package is recommended and placed at the top, and the user is informed that according to the questionnaire answered by you, the following add-on package examination is recommended.

[0047] The family doctor recommendation method includes extracting the medical examination associated information associated with the medical examination item from the online consultation information of the medical examination user with the online doctor.

[0048] For example, when the user needs some professional doctors to recommend, the user clicks on the family doctor recommendation, then pulls up the im chat box to let the user directly communicate with the family doctor team online, and the family doctor team can also see the information of the user and the add-on package that can be purchased in the background. After the family doctor communicates with the user and confirms, the family doctor can check the add-on package that wants to recommend to the user in the background, and then recommend it to the user in the form of a card message. After the user clicks on the card message in the im chat box, it will directly return to the add-on package purchase page, and then the add-on package recommended by the doctor is recommended and placed at the top, and the user is informed that according to the recommendation of the doctor, the following add-on package examination is recommended.

[0049] The artificial intelligence model recommendation manner includes a preset model; the preset model represents an association relationship between multi-dimensional physical examination index information and an abnormal physical examination item, the preset model is trained based on sample data, and the sample data includes user physiological characteristic information, historical physical examination report information, user basic attribute information, user selected this time physical examination package information, and an abnormal index physical examination item.

[0050] The user basic attribute information includes age, height, weight, and other physical condition characteristic information.

[0051] For example, a DeepSeek recommendation attempt is performed for a small part of internal physical examination users. When the physical examination user clicks the DeepSeek recommendation, the physiological characteristics, package information, age, and existing physical examination report abnormality of the physical examination user are informed to the DeepSeek, and the DeepSeek is enabled to recommend the physical examination user to perform which physical examination additional item examination according to the information. After the DeepSeek reasoning, the additional item package recommended by the DeepSeek is recommended to be placed at the top, and the physical examination user is informed to perform the following additional item package examination according to the DeepSeek recommendation.

[0052] S22, obtaining a plurality of candidate physical examination recommendation items according to the plurality of physical examination information extraction results.

[0053] S23, selecting a target physical examination item different from the existing physical examination item in the target physical examination package of the physical examination user from the plurality of candidate physical examination recommendation items, and recommending the target physical examination item to the user terminal of the physical examination user as a physical examination additional item package.

[0054] In the above embodiment, the unified physical examination additional item package is generated based on the physical examination information extraction results extracted by the plurality of preset recommendation manners, and the physical examination additional item package is recommended to the physical examination user at one time.

[0055] Based on this, in one embodiment, the total number of online users of the physical examination user is determined, and if the total number of online users is less than or equal to a preset number, the above-mentioned integrated generation of the physical examination additional item package is adopted for the case that the total number of online users of the physical examination user is small, so as to recommend the physical examination additional item package to the user at one time.

[0056] Through the above-mentioned embodiment, different recommendation manners are respectively set for different dimension user information obtained through different channels, and different dimension physical examination association information according to which different recommendation manners are extracted is unified, so as to generate different candidate physical examination items according to the physical examination association information, and select the target physical examination item outside the physical examination package to recommend to the physical examination user. Based on this, the target physical examination item recommended is generated based on the multi-dimensional physical examination index information of different information channels, can more comprehensively reflect the physical examination demand of the physical examination user from different dimensions, improves the accuracy of the physical examination additional item package, so that the physical examination user performs physical examination by using the physical examination additional item package and the physical examination package, and the physical examination result obtained is more accurate.

[0057] As an implementation, before S21 is performed, the following step can also be performed: determining a target recommendation priority of a plurality of preset recommendation manners according to the user type and the user information of the physical examination user; the target priority represents the order of recommending the plurality of preset recommendation manners to the user.

[0058] Further, as an implementation, based on the target recommendation priority, the following step is further implemented on S21 to obtain a plurality of physical examination information extraction results.

[0059] Firstly, the total number of online is determined.

[0060] Secondly, in the case that the total number of online is greater than a preset number, the plurality of preset recommendation manners are sequentially called according to the target recommendation priority, and the physical examination associated information corresponding to the physical examination user is sequentially extracted in order to obtain one of the plurality of physical examination information extraction results.

[0061] Further, at least one candidate physical examination recommendation item is generated according to each extracted physical examination information extraction result; at least one candidate physical examination recommendation item is compared with the existing physical examination item of the target physical examination package each time at least one candidate physical examination recommendation item is generated; the candidate physical examination item that is different from the existing physical examination item in the at least one candidate physical examination recommendation item generated each time is taken as a sub-add-on package of the physical examination add-on package, and the sub-add-on package is recommended to the user terminal of the physical examination user.

[0062] It can be understood that in the case that the total number of online is greater than a preset number, the plurality of preset recommendation manners are sequentially called according to the target priority, and the physical examination associated information corresponding to the physical examination user is sequentially extracted in order to obtain a physical examination information extraction result; at least one candidate physical examination recommendation item is generated according to each extracted physical examination information extraction result; at least one candidate physical examination recommendation item is compared with the existing physical examination item of the target physical examination package each time at least one candidate physical examination recommendation item is generated, so that the candidate physical examination item that is different from the existing physical examination item in the at least one candidate physical examination recommendation item generated each time is taken as a sub-add-on package of the physical examination add-on package, and the sub-add-on package is recommended to the user terminal of the physical examination user.

[0063] In the above embodiment, for the case that the total number of online users of physical examination is greater than the preset number, in order to ensure the recommendation efficiency, the physical examination items of the physical examination package add-on are recommended to the physical examination user in sequence according to the bit sequence of the target priority, so as to generate and display the physical examination add-on package in sections according to the target priority, so as to generate and display the target physical examination items with high target priority preferentially, so that the user terminal can still quickly receive the recommended add-on information in the case that the physical examination user has a large amount of online consultation, so as to quickly respond to the needs of the physical examination user and improve the recommendation efficiency. In order to avoid the risk of misoperation caused by long waiting time, thereby causing the recommendation to fail.

[0064] The target recommendation priority of the above-mentioned multiple preset recommendation modes is determined according to the user type and user information of the physical examination user as follows.

[0065] In the first scenario, it is determined that the user type is the first preset type and the user information includes historical physical examination report information, and the target recommendation priority is arranged in the following preset recommendation mode and the priority parameter of each preset recommendation mode is sequentially reduced: family doctor recommendation mode, abnormal index recommendation mode, questionnaire recommendation mode, report recommendation mode and artificial intelligence model recommendation mode; the priority parameter is positively correlated with the priority.

[0066] The above-mentioned first preset type represents a new physical examination user.

[0067] In the second scenario, it is determined that the user type is the first preset type and the user information does not include historical physical examination report information, and the target recommendation priority is arranged in the following preset recommendation mode and the priority parameter is sequentially reduced: family doctor recommendation mode, abnormal index recommendation mode, questionnaire recommendation mode, report recommendation mode and artificial intelligence model recommendation mode, and the priority parameters of the report recommendation mode and the artificial intelligence model recommendation mode are set to 0; the priority parameter of 0 represents that the corresponding preset recommendation mode is not called.

[0068] In the third scenario, it is determined that the user type is the second preset type, and the target recommendation priority is arranged in the following preset recommendation mode and the priority parameter is sequentially reduced: artificial intelligence model recommendation mode, report recommendation mode, abnormal index recommendation mode, family doctor recommendation mode and questionnaire recommendation mode.

[0069] The above-mentioned second preset type represents an old physical examination user who has been physically examined.

[0070] As an implementation, in order to obtain the physical examination related information of the physical examination user, before the physical examination related information of the physical examination user is extracted according to the information extraction process corresponding to each of the plurality of preset recommendation modes, and a plurality of physical examination information extraction results are obtained, the target recommendation mode interacted with the physical examination user is first selected from the plurality of preset recommendation modes; the preset interactive question and answer information related to the physical examination index is associated with the target recommendation mode and sent to the user terminal of the physical examination user; and the target input information of the preset interactive question and answer information returned by the user terminal of the physical examination user is accepted to extract the physical examination related information from the target input information.

[0071] In order to realize the above functions, the physical examination information recommendation device comprises a hardware structure and / or a software module corresponding to each function. Those skilled in the art should easily realize that the algorithm steps of each example described in combination with the embodiments disclosed in the present application can be realized in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the form of hardware or computer software driven hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0072] The present disclosure also provides a physical examination information recommendation device as shown in Figure 3 The device comprises an extraction unit 301 configured to extract physical examination related information of a physical examination user according to an information extraction process corresponding to each of a plurality of preset recommendation modes, and obtain a plurality of physical examination information extraction results; a determination unit 302 configured to obtain a plurality of candidate physical examination recommendation items according to the plurality of physical examination information extraction results; and a screening unit 303 configured to select a target physical examination item different from an existing physical examination item in a target physical examination package of the physical examination user from the plurality of candidate physical examination recommendation items, and recommend the target physical examination item as a physical examination add-on package to a user terminal of the physical examination user.

[0073] In an implementation, the extraction unit 301 is further configured to determine a target recommendation priority of the plurality of preset recommendation modes according to a user type and user information of the physical examination user, and the target priority represents an order of recommending the plurality of preset recommendation modes to the user.

[0074] In another implementation, the extraction unit 301 is specifically configured to determine a total number of online users of the physical examination user, and in a case where the total number of online users is greater than a preset number, sequentially call the plurality of preset recommendation modes according to the target recommendation priority to sequentially extract the physical examination related information of the physical examination user, and sequentially obtain one of the plurality of physical examination information extraction results.

[0075] In another implementation, the screening unit 303 is specifically configured to: generate at least one candidate physical examination recommendation item according to the physical examination information extraction result of each extraction; compare the at least one candidate physical examination recommendation item with the existing physical examination items of the target physical examination package each time the at least one candidate physical examination recommendation item is generated; and recommend the sub-add-on package of the physical examination add-on package to the user terminal of the physical examination user by taking the candidate physical examination items different from the existing physical examination items in the at least one candidate physical examination recommendation item generated each time as the sub-add-on package of the physical examination add-on package.

[0076] In another implementation, the plurality of preset recommendation manners include a report recommendation manner, an abnormal index recommendation manner, a questionnaire recommendation manner, a family doctor recommendation manner, and an artificial intelligence model recommendation manner; the artificial intelligence model recommendation manner includes a preset model; the preset model represents an association relationship between the multi-dimensional physical examination index information and the abnormal physical examination item, and the preset model is trained based on sample data including user physiological feature information, historical physical examination report information, user basic attribute information, user selected physical examination package information of this time, and an abnormal index physical examination item.

[0077] In another implementation, the screening unit 303 is specifically configured to: generate at least one candidate physical examination recommendation item according to the physical examination information extraction result of each extraction; compare the at least one candidate physical examination recommendation item with the existing physical examination items of the target physical examination package each time the at least one candidate physical examination recommendation item is generated; and recommend the sub-add-on package of the physical examination add-on package to the user terminal of the physical examination user by taking the candidate physical examination items different from the existing physical examination items in the at least one candidate physical examination recommendation item generated each time as the sub-add-on package of the physical examination add-on package.

[0078] In another implementation, before the information of the user is extracted according to the information extraction process corresponding to each of the plurality of preset recommendation modes, the device is further configured to: select a target recommendation mode from the plurality of preset recommendation modes, the target recommendation mode being interacted with the user; associate the target recommendation mode with preset interactive question and answer information related to the health index, and send the preset interactive question and answer information to the user terminal of the user; and accept the target input information of the preset interactive question and answer information returned by the user terminal of the user, and extract the health-related information from the target input information.

[0079] As to the device in the above embodiments, the specific manners in which the units perform operations have been described in detail in the embodiments of the method, and thus will not be described here in detail.

[0080] Figure 4 is a schematic diagram of an electronic device provided by the present application. As Figure 4 The electronic device 50 can include at least one processor 501 and a memory 503 for storing processor-executable instructions. The processor 501 is configured to execute the instructions in the memory 503 to implement the health information recommendation method in the following embodiments.

[0081] In addition, the electronic device 50 can further include a communication bus 502, at least one communication interface 504, an input device 506, and an output device 505.

[0082] The processor 501 can be a central processing unit (CPU), a micro processing unit, an ASIC, or one or more integrated circuits for controlling the execution of programs of the present application.

[0083] The communication bus 502 can include a path for transmitting information between the above components.

[0084] The communication interface 504 uses any transceiver device to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc.

[0085] The input device 506 is used to receive input signals and the output device 505 is used to output signals.

[0086] The memory 503 can be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM), or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, a magnetic disk storage or other magnetic storage devices, or any other medium capable of storing desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to this. The memory can exist independently and be connected to the processing unit through a bus. The memory can also be integrated with the processing unit.

[0087] The memory 503 is configured to store instructions for implementing the solutions of the present application, and the processor 501 is configured to execute the instructions stored in the memory 503.

[0088] In a specific implementation, as an example, the processor 501 can include one or more CPUs, such as the CPU0 and the CPU1 in the Figure 4 In a specific implementation, as an example, the processor 501 can include one or more CPUs, such as the CPU0 and the CPU1 in the

[0089] In a specific implementation, as an example, the electronic device 50 can include a plurality of processors, such as the processor 501 and the processor 507 in the Figure 4 In a specific implementation, as an example, the electronic device 50 can include a plurality of processors, such as the processor 501 and the processor 507 in the

[0090] The electronic device includes a processor 501 and a memory 503 for storing instructions executable by the processor 501, as shown in Figure 4 The processor 501 is configured to execute the executable instructions to implement the physical examination information recommendation method of any possible implementation manner described above, and achieve the same technical effects. To avoid repetition, details are not described here.

[0091] The embodiment of the present application further provides a computer readable storage medium, when instructions in the computer readable storage medium are executed by a processor of a physical examination information recommendation device or an electronic device, the physical examination information recommendation device or the electronic device can execute the physical examination information recommendation method of any possible implementation manner described above. And can achieve the same technical effects, to avoid repetition, here will not repeat.

[0092] The embodiment of the present application further provides a computer program product, including a computer program or instructions, the computer program or instructions are executed by a processor to execute the physical examination information recommendation method of any possible implementation manner described above. And can achieve the same technical effects, to avoid repetition, here will not repeat.

[0093] Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the application being indicated by the following claims.

[0094] It should be understood that the application is not limited to the precise construction that has been described above and shown in the accompanying drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the application. The scope of the application is limited only by the appended claims.

Claims

1. A method for recommending physical examination information, characterized in that: The method comprises: Extracting the physical examination related information of the physical examination user according to the information extraction processes corresponding to the multiple preset recommendation methods, and obtaining multiple physical examination information extraction results; Obtaining multiple candidate physical examination recommendation items based on the multiple physical examination information extraction results; From the multiple candidate physical examination recommendation items, a target physical examination item that is different from the existing physical examination items in the target physical examination package of the physical examination user is selected, and the target physical examination item is recommended to the user terminal of the physical examination user as a physical examination additional item package.

2. The method for recommending physical examination information according to claim 1, characterized in that: Before extracting the physical examination-related information of the physical examination user according to the information extraction processes corresponding to the plurality of preset recommendation methods and obtaining a plurality of physical examination information extraction results, the method further includes: The target recommendation priorities of the plurality of preset recommendation methods are determined according to the user type and user information of the physical examination user; the target priority represents the order in which the plurality of preset recommendation methods are recommended to the user.

3. The method for recommending physical examination information according to claim 2, wherein: The physical examination-related information of the physical examination user is extracted according to the information extraction processes corresponding to the multiple preset recommendation methods, and multiple physical examination information extraction results are obtained, including: Determine the total number of online users of the physical examination; When the total number of online users is greater than the preset number, the multiple preset recommendation methods are called in sequence according to the target recommendation priority, and the physical examination related information corresponding to the physical examination user is extracted in sequence, and one physical examination information extraction result from the multiple physical examination information extraction results is obtained in sequence.

4. The method for recommending physical examination information according to claim 3, wherein: The method further comprises: generating at least one candidate physical examination recommendation item according to each extracted physical examination information extraction result; Each time the at least one candidate physical examination recommendation item is generated, the at least one candidate physical examination recommendation item is compared with existing physical examination items of the target physical examination package; Among the at least one candidate physical examination recommendation item generated each time, a candidate physical examination item that is different from the existing physical examination item is used as a sub-item package of the physical examination additional item package, and the sub-item package is recommended to the user terminal of the physical examination user.

5. The method for recommending physical examination information according to claim 2, wherein: The multiple preset recommendation methods include a report recommendation method, an abnormal indicator recommendation method, a questionnaire recommendation method, a family doctor recommendation method, and an artificial intelligence model recommendation method; the artificial intelligence model recommendation method includes a preset model; the preset model represents the correlation between multi-dimensional physical examination indicator information and abnormal physical examination items, and the preset model is trained based on sample data, and the sample data includes user physiological characteristics information, historical physical examination report information, user basic attribute information, the physical examination package information selected by the user this time, and abnormal indicator physical examination items.

6. The method for recommending physical examination information according to claim 5, characterized in that: The determining, based on the user type and user information of the physical examination user, target recommendation priorities of the plurality of preset recommendation methods includes: Determining that the user type is a first preset type and the user information includes historical physical examination report information, arranging the order according to the following preset recommendation methods, descending the priority parameters of each preset recommendation method in turn, and setting the target recommendation priority: family doctor recommendation method, abnormal indicator recommendation method, questionnaire recommendation method, report recommendation method, and artificial intelligence model recommendation method; the priority parameter is positively correlated with the priority; Determining that the user type is the first preset type and the user information does not include historical physical examination report information, arranging the order according to the following preset recommendation methods, setting the target recommendation priority in descending order of priority parameters: family doctor recommendation method, abnormal indicator recommendation method, questionnaire recommendation method, report recommendation method, and artificial intelligence model recommendation method, and setting the priority parameters of the report recommendation method and the artificial intelligence model recommendation method to 0; a priority parameter of 0 indicates that the corresponding preset recommendation method is not called; Determine that the user type is the second preset type, arrange the order according to the following preset recommendation method, and set the target recommendation priority with priority parameters in descending order: artificial intelligence model recommendation method, report recommendation method, abnormal indicator recommendation method, family doctor recommendation method and questionnaire recommendation method.

7. The method for recommending physical examination information according to any one of claims 1 to 6, characterized in that: Before extracting the physical examination-related information of the physical examination user according to the information extraction processes corresponding to the plurality of preset recommendation methods and obtaining a plurality of physical examination information extraction results, the method further includes: Filtering a target recommendation method for interacting with the physical examination user from the multiple preset recommendation methods; Associating the target recommendation method with preset interactive question-and-answer information related to the physical examination indicators, and sending the information to the user terminal of the physical examination user; Accept the target input information of the preset interactive question and answer information returned by the user terminal of the physical examination user, so as to extract the physical examination related information from the target input information.

8. A physical examination information recommendation device, characterized in that: The device comprises: An extraction unit is used to extract the physical examination related information of the physical examination user according to the information extraction processes corresponding to the multiple preset recommendation methods, and obtain multiple physical examination information extraction results; a determining unit, configured to obtain a plurality of candidate physical examination recommendation items based on the plurality of physical examination information extraction results; The screening unit is used to select a target physical examination item that is different from the existing physical examination items in the target physical examination package of the physical examination user from the multiple candidate physical examination recommendation items, so as to recommend the target physical examination item as a physical examination additional item package to the user terminal of the physical examination user.

9. A physical examination information recommendation system, characterized in that: The method is configured to execute the medical examination information recommendation method according to any one of claims 1 to 7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the physical examination information recommendation method according to any one of claims 1 to 7.

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