Multi-agent platform insurance excess dose identification digital intelligent system based on full-text retrieval knowledge base enhancement engine

Abstract

The invention belongs to the technical field of insurance industry, and particularly relates to a full-text retrieval knowledge base enhancement engine-based insurance excess dose identification digital intelligent system of a multi-agent platform, which comprises a full-text retrieval knowledge base enhancement engine, a multi-agent platform, a user interaction interface and a system integration and control module. According to the system, through efficient data processing and intelligent analysis, the real-time performance and accuracy of medication safety monitoring are remarkably improved, query safety is ensured through the user identity verification unit, the overall stability and reliability of the system are enhanced through introduction of an integration and control module, and through close cooperation and continuous optimization of all the modules, the safety of medication safety monitoring is greatly improved. The method not only reduces human errors, but also greatly improves the efficiency of dose monitoring, shows the huge potential of the digital intelligence technology in the modern insurance industry, and enables insurance companies to quickly make responses and effectively reduce risks when facing complex and changeable medication problems.

Description

Technical Field

[0001] The present invention relates to the technical field of the insurance industry, and specifically to a digital intelligence system for identifying insurance overdose based on a multi-agent platform of a full-text retrieval knowledge base enhancement engine. Background Art

[0002] In the insurance industry, monitoring the insured's medication is an important part of risk control. Traditional overdose identification relies on manual review, which is inefficient and prone to errors. With the development of artificial intelligence technology, it has become possible to use intelligent systems to identify overdose, which not only improves the efficiency of review, but also greatly reduces the error rate. Intelligent systems can quickly identify abnormal medication patterns by analyzing large amounts of medical data and medication records, thereby promptly discovering potential risks. The application of this technology not only reduces the burden of manual review, but also provides insurance companies with more accurate risk assessment tools, further improving the risk management level of the entire industry. Therefore, it is necessary to develop a digital intelligence system for insurance overdose identification based on a multi-agent platform with a full-text retrieval knowledge base enhancement engine. Summary of the invention

[0003] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0004] To solve the above technical problems, according to one aspect of the present invention, the present invention provides the following technical solutions:

[0005] A digital intelligence system for identifying over-dose insurance medication based on a multi-agent platform with a full-text search knowledge base enhancement engine, comprising: a full-text search knowledge base enhancement engine, a multi-agent platform, a user interaction interface, and a system integration and control module;

[0006] The full-text search knowledge base enhancement engine is used to construct a full-text search knowledge base and provide a full-text search function;

[0007] The multi-agent platform is used to achieve overdose identification, risk assessment and system optimization;

[0008] The user interaction interface is used for the user to input query requests and view recognition results;

[0009] The system integration and control module is used to coordinate the work of the full-text retrieval knowledge base enhancement engine and the multi-agent platform.

[0010] As a preferred solution of the digital intelligence system for identifying excessive drug dosage in insurance based on a multi-agent platform of a full-text search knowledge base enhancement engine described in the present invention, wherein: the full-text search knowledge base enhancement engine includes: a data acquisition module, a knowledge base construction module and a full-text search module;

[0011] The data acquisition module is used to collect relevant information from multi-source data;

[0012] The knowledge base construction module is used to perform structured processing on the collected data and construct a full-text retrieval knowledge base;

[0013] The full-text search module is used to implement the full-text search function of the knowledge base.

[0014] As a preferred solution of the digital intelligence system for insurance overdose identification based on a multi-agent platform of a full-text search knowledge base enhancement engine described in the present invention, wherein: the multi-agent platform includes: an overdose identification agent, a risk assessment agent, and a feedback and learning agent;

[0015] The overdose identification agent is used to analyze the insured's medication records based on the information in the full-text retrieval knowledge base;

[0016] The risk assessment agent is used to perform risk assessment on the recognition result of the overdose recognition agent;

[0017] The feedback and learning agent is used to optimize the recognition rules and evaluation model according to the feedback.

[0018] As a preferred solution of the digital intelligence system for identifying insurance overdose based on a multi-agent platform of a full-text search knowledge base enhancement engine described in the present invention, wherein: the user interaction interface includes: an input and output unit, a user identity authentication unit and an interface display unit;

[0019] The input and output unit is used for the user to input query requests and view recognition results;

[0020] The user identity verification unit is used to verify the user identity;

[0021] The interface display unit is used to display the final excess drug dosage identification result and risk assessment report.

[0022] As a preferred solution of the digital intelligence system for identifying excessive drug dosage based on a multi-agent platform of a full-text search knowledge base enhancement engine described in the present invention, the system integration and control module includes: a system scheduling unit, a state monitoring unit and an exception handling unit;

[0023] The system scheduling unit is used to coordinate the work of the full-text retrieval knowledge base enhancement engine and the multi-agent platform;

[0024] The state monitoring unit is used to monitor the system operation status;

[0025] The exception handling unit is used to handle the abnormal conditions during the system operation.

[0026] As a preferred solution of a touch query all-in-one machine according to the present invention, it includes an all-in-one machine body. The all-in-one machine body stores a digital intelligence system for insurance over-dose identification of a multi-agent platform based on a full-text retrieval knowledge base enhancement engine as described in claims 1-5. The all-in-one machine body includes a housing and a touch screen arranged on the surface of the housing. Users use the digital intelligence system through the touch screen.

[0027] As a preferred solution of a touch query all-in-one machine according to the present invention, a dust removal roller is rotatably arranged on the surface of the touch screen along the direction of the touch screen. Dust removal bristles for cleaning the surface of the touch screen are evenly arranged on the surface of the dust removal roller. A driving mechanism for driving the dust removal roller to reciprocate along the surface of the touch screen is arranged on the housing.

[0028] As a preferred solution of a touch query all-in-one machine according to the present invention, the driving mechanism includes fixed seats fixed on the surface of the housing above and below both sides of the touch screen. Reciprocating lead screws are respectively rotatably arranged between two fixed seats on the same left and right side. The inclination of the reciprocating lead screw is the same as the inclination of the touch screen. Transmission blocks are respectively arranged on the rod bodies of the two reciprocating lead screws. The left and right ends of the dust removal roller are respectively rotatably connected to the side walls of the two transmission blocks.

[0029] As a preferred solution of a touch query all-in-one machine according to the present invention, a gear is arranged on the rod body of the dust removal roller near the transmission block. A rack that is always engaged with the transmission block is arranged on the surface of the housing below the gear.

[0030] As a preferred solution of a touch query all-in-one machine according to the present invention, a double-headed servo motor is fixedly arranged on the surface of the housing above the touch screen. Active bevel gears are respectively arranged on the two output shafts of the double-headed servo motor. The upper ends of the two reciprocating lead screws extend and rotatably penetrate the side walls of the fixed seats and are provided with follower bevel gears that engage with the active bevel gears;

[0031] A protective cover for accommodating the driving mechanism is arranged on the surface of the housing. The protective cover is in a "冂" shape, and the protective cover is provided with an activity opening for the displacement and entry and exit of the dust removal roller.

[0032] The beneficial effects of the present invention are as follows: through efficient data processing and intelligent analysis, the real-time and accuracy of medication safety monitoring are significantly improved; the query security is ensured through the user identity authentication unit; the introduction of the integration and control module further enhances the overall stability and reliability of the system; through close collaboration and continuous optimization of each module, not only human errors are reduced, but also the efficiency of medication monitoring is greatly improved, which saves a lot of costs for insurance companies, promotes the improvement of service quality and customer satisfaction of the entire insurance industry, and demonstrates the huge potential of digital technology in the modern insurance industry, so that insurance companies can respond quickly and effectively reduce risks when faced with complex and changeable medication problems;

[0033] When the user needs to control the digital intelligence system through the touch screen, the double-headed servo motor can be started to drive the two reciprocating screws to rotate at the same time through the active bevel gear and the follower bevel gear, so that the two transmission blocks drive the dust removal roller to move back and forth. During the movement of the dust removal roller, since the gear and the rack are always engaged, the dust removal roller will also be driven to rotate continuously. That is, the surface of the touch screen can be cleaned through the outer casing, thereby reducing the dust attached to its surface. After the dust removal brush is cleaned, it can also be put into the protective cover, making it convenient for users to use the touch screen again. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the present invention will be described in detail below in combination with the accompanying drawings and detailed embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0035] Figure 1 is a system block diagram of the present invention;

[0036] Figure 2 A system block diagram of the full-text search knowledge base enhancement engine of the present invention;

[0037] Figure 3 is a system block diagram of the multi-agent platform of the present invention;

[0038] Figure 4 A system block diagram of the user interaction interface of the present invention;

[0039] Figure 5 A system block diagram of the system integration and control module of the present invention;

[0040] Figure 6 It is a structural schematic diagram of the integrated machine body of the present invention;

[0041] Figure 7 For the present invention Figure 6 Schematic diagram of the structure inside the middle protective cover;

[0042] Figure 8 For the present invention Figure 7 Schematic diagram of the structure from the middle side view.

[0043] In the figure: the integrated machine body 100, the shell 110, the touch screen 120, the dust removal roller 200, the dust removal brush 210, the driving mechanism 300, the fixing seat 310, the reciprocating screw 320, the transmission block 330, the gear 340, the rack 350, the double-headed servo motor 360, the follower bevel gear 370, the driving bevel gear 380, the protective cover shell 390, and the opening 391. DETAILED DESCRIPTION

[0044] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0045] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0046] Secondly, the present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention in detail, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0047] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0048] Example 1

[0049] See also Figure 1-Figure 5 , shows a system block diagram of a digital intelligence system for identifying excessive drug dosage in insurance based on a multi-agent platform of a full-text retrieval knowledge base enhancement engine of the present invention;

[0050] A digital intelligence system for identifying overdose of insurance drugs based on a multi-agent platform with a full-text retrieval knowledge base enhancement engine, including

[0051] Full-text search knowledge base enhancement engine, multi-agent platform, user interaction interface and system integration and control module;

[0052] The full-text search knowledge base enhancement engine is used to build a full-text search knowledge base and provide full-text search functions;

[0053] Multi-agent platform is used to achieve overdose identification, risk assessment and system optimization;

[0054] The user interaction interface is used for users to input query requests and view recognition results;

[0055] The system integration and control module is used to coordinate the work of the full-text retrieval knowledge base enhancement engine and the multi-agent platform;

[0056] Among them: the full-text search knowledge base enhancement engine includes: data collection module, knowledge base construction module and full-text search module;

[0057] The data acquisition module is used to collect relevant information from multi-source data;

[0058] The knowledge base construction module is used to structure the collected data and build a full-text retrieval knowledge base;

[0059] The full-text search module is used to realize the full-text search function of the knowledge base;

[0060] The full-text search knowledge base enhancement engine collects relevant information from multi-source data through the data collection module. Specific methods include web crawler technology, API interface calls, data subscription services, etc., to obtain data in various formats such as text, pictures, and videos;

[0061] The knowledge base construction module structures the collected data, performs data cleaning, entity recognition, and relationship extraction on the acquired information, converts unstructured or semi-structured data into structured knowledge items, and stores them in the full-text retrieval knowledge base;

[0062] The full-text search module implements the full-text search function of the knowledge base by establishing an index mechanism. After the user enters a query request, the system will quickly search the index, find relevant knowledge items containing the query keywords, and return them to the user in order of relevance.

[0063] Among them: the multi-agent platform includes: overdose recognition agent, risk assessment agent and feedback and learning agent;

[0064] The overdose identification agent is used to analyze the insured's medication records based on the information in the full-text retrieval knowledge base;

[0065] The risk assessment agent is used to conduct risk assessment on the recognition results of the overdose recognition agent;

[0066] Feedback and learning agents are used to optimize recognition rules and evaluation models based on feedback;

[0067] The overdose identification agent conducts a detailed analysis of the insured's medication records by full-text searching the information in the knowledge base to identify whether there is an overdose. It uses natural language processing technology to parse the text information in the records and compares it with the medication guidelines, dosage standards, etc. in the knowledge base to determine whether the medication records are beyond the normal range.

[0068] The risk assessment agent uses the identification results provided by the overdose identification agent to assess the health risks and insurance risks faced by the insured. It uses statistical analysis, machine learning and other methods to calculate the risk level of overdose behavior based on historical data and relevant risk factors, providing a basis for insurance decision-making.

[0069] The feedback and learning agent optimizes the rules and models of the overdose identification agent and the risk assessment agent based on the feedback from users or experts. It uses reinforcement learning or supervised learning techniques in machine learning to adjust algorithm parameters based on feedback to continuously improve the accuracy of identification and the precision of risk assessment.

[0070] Wherein: the user interaction interface includes: an input and output unit, a user identity authentication unit and an interface display unit;

[0071] The input and output unit is used for users to input query requests and view recognition results;

[0072] The user identity verification unit is used to verify the identity of the user;

[0073] The interface display unit is used to display the final excess drug dosage identification results and risk assessment report; the input-output unit allows users to input their query requests through a touch screen by providing a user-friendly interface; after the user submits the query, the input-output unit sends the request to the system for processing; after the processing is completed, the input-output unit receives the identification results and displays them to the user, who can read them on the screen or listen to the feedback provided by the system;

[0074] The user authentication unit verifies the user's identity by requiring the user to provide specific credentials, which may include a username and password, biometric information such as fingerprint or facial recognition, or a one-time verification code sent via mobile phone or email; the system compares these credentials with the stored user information to confirm the user's identity;

[0075] The interface display unit is responsible for presenting the excess drug dosage identification results and risk assessment reports to users in a clear and easy-to-understand manner; this includes using charts, graphs and text descriptions to display data and analysis results, ensuring that users can easily understand the report content and potential risks

[0076] Among them: the system integration and control module includes: system scheduling unit, status monitoring unit and exception handling unit;

[0077] The system scheduling unit is used to coordinate the work of the full-text retrieval knowledge base enhancement engine and the multi-agent platform;

[0078] The status monitoring unit is used to monitor the system operation status;

[0079] The exception handling unit is used to handle abnormal situations in system operation;

[0080] The system scheduling unit ensures the efficient collaboration of the full-text search knowledge base enhancement engine and the multi-agent platform by formulating task allocation plans and priorities; it is responsible for receiving task requests and making reasonable scheduling based on system resources and task characteristics to optimize overall performance and response speed;

[0081] The status monitoring unit collects system operation data in real time, analyzes system performance indicators, and promptly identifies potential problems and performance bottlenecks. It is also responsible for providing status reports to system administrators so that necessary adjustments and optimizations can be made.

[0082] The exception handling unit identifies errors and abnormal conditions in system operation through a preset exception detection mechanism; once an exception is detected, it automatically triggers the corresponding processing procedures, including restarting the service, switching to the backup system, or notifying maintenance personnel to ensure stable system operation and minimize the impact of exceptions on the business.

[0083] Example 2

[0084] See also Figure 6-Figure 8 , shows a schematic diagram of the structure of a touch-controlled query machine of the present invention, including:

[0085] The integrated machine body 100 stores therein a digital intelligence system for identifying excessive drug dosages of insurance products based on a multi-agent platform with a full-text search knowledge base enhancement engine as described in claims 1 to 5, and the integrated machine body 100 includes a housing 110 and a touch screen 120 disposed on the surface of the housing 110, and a user uses the digital intelligence system through the touch screen 120;

[0086] Wherein: a dust removal roller 200 is arranged on the surface of the touch screen 120 so as to rotate along the direction of the touch screen 120, and dust removal bristles 210 for cleaning the surface of the touch screen 120 are evenly arranged on the surface of the dust removal roller 200, and a driving mechanism 300 for driving the dust removal roller 200 to reciprocate along the surface of the touch screen 120 is arranged on the housing 110;

[0087] Among them: The driving mechanism 300 includes fixing seats 310 fixed on the surface of the outer shell 110 above and below both sides of the touch screen 120. A reciprocating lead screw 320 is rotatably arranged between two fixing seats 310 on the same left and right side. The inclination of the reciprocating lead screw 320 is the same as that of the touch screen 120. Transmission blocks 330 are respectively arranged on the rod bodies of the two reciprocating lead screws 320. The left and right ends of the dust removal roller 200 are respectively rotatably connected to the side walls of the two transmission blocks 330;

[0088] Among them: A gear 340 is arranged on the rod body of the dust removal roller 200 near the transmission block 330. A rack 350 that is always engaged with the transmission block 330 is arranged on the surface of the outer shell 110 below the gear 340;

[0089] Among them: A double-headed servo motor 360 is fixedly arranged on the surface of the outer shell 110 above the touch screen 120. Two output shafts of the double-headed servo motor 360 are respectively provided with driving bevel gears 380. The upper ends of the two reciprocating lead screws 320 extend through the side walls of the fixing seats 310 in a rotating manner and are provided with follower bevel gears 370 that are engaged with the driving bevel gears 380;

[0090] A protective cover 390 for accommodating the driving mechanism 300 is arranged on the surface of the outer shell 110. The protective cover 390 is in a shape of "冂", and the protective cover 390 is provided with a movable opening 391 for the displacement and entry and exit of the dust removal roller 200;

[0091] In the specific use process, when the user needs to control the digital intelligence system through the touch screen 120, the double-headed servo motor 360 can be started. The two reciprocating lead screws 320 are simultaneously driven to rotate through the driving bevel gears 380 and the follower bevel gears 370, so that the two transmission blocks 330 drive the dust removal roller 200 to reciprocate. During the movement of the dust removal roller 200, since the gear 340 and the rack 350 are always engaged, the dust removal roller 200 will also be driven to rotate continuously, that is, the surface of the touch screen 120 can be cleaned by the dust removal bristles 210, so as to reduce the dust attached to its surface. After the dust removal bristles 210 finish cleaning, it can also be received into the protective cover 390 through the opening 391, which is convenient for the user to use the touch screen 120 again.

[0092] Although the present invention has been described above with reference to the embodiments, various modifications may be made thereto and parts thereof may be replaced by equivalents without departing from the scope of the present invention. In particular, as long as there is no structural conflict, the various features in the embodiments disclosed in the present invention may be used in combination with each other in any manner, and the fact that these combinations are not exhaustively described in this specification is only for the sake of omitting space and saving resources. Therefore, the present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A digital intelligence system for identifying overdose of insurance drugs based on a multi-agent platform with a full-text search knowledge base enhancement engine, characterized in that: include: Full-text search knowledge base enhancement engine, multi-agent platform, user interaction interface and system integration and control module; The full-text search knowledge base enhancement engine is used to construct a full-text search knowledge base and provide a full-text search function; The multi-agent platform is used to achieve overdose identification, risk assessment and system optimization; The user interaction interface is used for the user to input query requests and view recognition results; The system integration and control module is used to coordinate the work of the full-text retrieval knowledge base enhancement engine and the multi-agent platform.

2. According to claim 1, a digital intelligence system for identifying excessive drug dosage based on a multi-agent platform with a full-text search knowledge base enhancement engine, characterized in that: The full-text search knowledge base enhancement engine includes: a data acquisition module, a knowledge base construction module and a full-text search module; The data acquisition module is used to collect relevant information from multi-source data; The knowledge base construction module is used to perform structured processing on the collected data and construct a full-text retrieval knowledge base; The full-text search module is used to implement the full-text search function of the knowledge base.

3. According to claim 1, a digital intelligence system for identifying excessive drug dosage based on a multi-agent platform with a full-text search knowledge base enhancement engine, characterized in that: The multi-agent platform includes: an overdose recognition agent, a risk assessment agent, and a feedback and learning agent; The overdose identification agent is used to analyze the insured's medication records based on the information in the full-text retrieval knowledge base; The risk assessment agent is used to perform risk assessment on the recognition result of the overdose recognition agent; The feedback and learning agent is used to optimize the recognition rules and evaluation model according to the feedback.

4. According to claim 1, a digital intelligence system for identifying excessive drug dosage based on a multi-agent platform with a full-text search knowledge base enhancement engine, characterized in that: The user interaction interface includes: an input and output unit, a user identity verification unit and an interface display unit; The input and output unit is used for the user to input query requests and view recognition results; The user identity verification unit is used to verify the user identity; The interface display unit is used to display the final excess drug dosage identification result and risk assessment report.

5. According to claim 1, a digital intelligence system for identifying excessive drug dosage based on a multi-agent platform with a full-text search knowledge base enhancement engine, characterized in that: The system integration and control module includes: a system scheduling unit, a status monitoring unit and an exception handling unit; The system scheduling unit is used to coordinate the work of the full-text retrieval knowledge base enhancement engine and the multi-agent platform; The status monitoring unit is used to monitor the operating status of the system; The exception handling unit is used to handle abnormal situations in system operation.

6. A touch-screen query machine, characterized in that: The invention comprises an integrated machine body (100), wherein the integrated machine body (100) internally stores a digital intelligence system for identifying insurance overdose based on a multi-agent platform of a full-text retrieval knowledge base enhancement engine as described in claims 1 to 5, and the integrated machine body (100) comprises a housing (110) and a touch screen (120) arranged on the surface of the housing (110), and a user uses the digital intelligence system through the touch screen (120).

7. The touch-control query integrated machine according to claim 6, characterized in that: A dust removal roller (200) is arranged on the surface of the touch screen (120) so as to rotate along the direction of the touch screen (120); dust removal bristles (210) for cleaning the surface of the touch screen (120) are evenly arranged on the surface of the dust removal roller (200); and a driving mechanism (300) for driving the dust removal roller (200) to reciprocate along the surface of the touch screen (120) is arranged on the housing (110).

8. The touch-control query integrated machine according to claim 7, characterized in that: The driving mechanism (300) includes fixing seats (310) fixed on the surface of the outer shell (110) above and below both sides of the touch screen (120). A reciprocating lead screw (320) is rotatably arranged between two fixing seats (310) on the same left and right side. The inclination of the reciprocating lead screw (320) is consistent with the inclination of the touch screen (120). Transmission blocks (330) are respectively arranged on the rod bodies of the two reciprocating lead screws (320). The left and right ends of the dust removal roller (200) are respectively rotatably connected to the side walls of the two transmission blocks (330).

9. The touch-control query integrated machine according to claim 8, characterized in that: A gear (340) is arranged on the rod body of the dust removal roller (200) near the transmission block (330). A rack (350) that is always engaged with the transmission block (330) is arranged on the surface of the outer shell (110) below the gear (340).

10. The touch-control query integrated machine according to claim 9, characterized in that: A double-headed servo motor (360) is fixedly arranged on the surface of the outer shell (110) above the touch screen (120). Active bevel gears (380) are respectively arranged on the two output shafts of the double-headed servo motor (360). The upper ends of the two reciprocating lead screws (320) extend through the side walls of the fixing seats (310) in a rotating manner and are provided with follower bevel gears (370) that are engaged with the active bevel gears (380). A protective cover (390) for accommodating the driving mechanism (300) is arranged on the surface of the outer shell (110). The protective cover (390) is in a "冂" shape, and the protective cover (390) is provided with a movable opening (391) for the displacement and entry and exit of the dust removal roller (200).

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