CN113990518A

CN113990518A - Information generation method and device, electronic equipment and storage medium

Info

Publication number: CN113990518A
Application number: CN202111243020.8A
Authority: CN
Inventors: 吴家林; 黄海峰; 代小亚; 王华伟; 佟卓远; 陆之晨; 李雪
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2021-10-25
Filing date: 2021-10-25
Publication date: 2022-01-28
Anticipated expiration: 2041-10-25
Also published as: CN113990518B

Abstract

The disclosure provides an information generation method, an information generation device, electronic equipment and a storage medium, and relates to the technical field of computers, in particular to the technical field of artificial intelligence such as knowledge maps and AI medical treatment. The specific implementation scheme is as follows: generating an instruction according to the received diagnosis information, and acquiring corresponding knowledge information; in the knowledge information, determining knowledge needing to be reminded when the diagnosis information is generated according to the diagnosis information generation instruction; and generating reminding information according to the knowledge needing to be reminded. The embodiment of the disclosure can provide effective assistance and support for medical behaviors.

Description

Information generation method and device, electronic equipment and storage medium

Technical Field

The present disclosure relates to the field of computer technology, and more particularly to the field of artificial intelligence techniques such as knowledge-graph and AI medical treatment.

Background

With the development of computer technology, the quality and efficiency of various aspects of people's life are improved, for example, people can obtain better and efficient life experience through computer technology in clothes and eating houses.

In addition to the clothes and eating habits, medical treatment is also an extremely important aspect of people's lives. Generally, the medical process has strong dependence on the subjective ability of medical staff, so there are many possible hidden dangers in the process of medical action, for example, there may be errors in human judgment to cause major life and health problems, and the medical knowledge data volume is very large, so that under special conditions, omission easily occurs. With the development of computer technology, better application of computer technology to the medical field can be considered, and the quality and efficiency of medical procedures can be improved.

Disclosure of Invention

The disclosure provides an information generation method, an information generation device, an electronic device and a storage medium.

According to an aspect of the present disclosure, there is provided an information generating method including:

generating an instruction according to the received diagnosis information, and acquiring corresponding knowledge information;

in the knowledge information, determining knowledge needing to be reminded when the diagnosis information is generated according to a diagnosis information generation instruction;

and generating reminding information according to the knowledge needing reminding.

According to another aspect of the present disclosure, there is provided an information generating apparatus including:

the knowledge information acquisition module is used for generating an instruction according to the received diagnosis information and acquiring corresponding knowledge information;

the knowledge determining module is used for determining knowledge which needs to be reminded when the diagnosis information is generated according to the diagnosis information generation instruction in the knowledge information;

and the reminding information generating module is used for generating reminding information according to the knowledge needing to be reminded.

According to another aspect of the present disclosure, there is provided an electronic device including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method according to any one of the embodiments of the present disclosure.

According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform a method in any of the embodiments of the present disclosure.

According to another aspect of the present disclosure, there is provided a computer program product comprising computer programs/instructions which, when executed by a processor, implement the method in any of the embodiments of the present disclosure.

According to the technology disclosed by the invention, the instruction and the medical knowledge information can be generated according to the diagnosis information, and whether the matters needing reminding or attention exist can be judged, so that good support and assistance effects can be provided for medical diagnosis activities, and the reliability of medical diagnosis behaviors can be improved.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

FIG. 1 is a schematic flow chart diagram of an information generation method according to an embodiment of the present disclosure;

FIG. 2 is a schematic flow chart diagram of an information generation method according to another embodiment of the present disclosure;

FIG. 3 is a schematic diagram of a CDSS system architecture according to an example of the present disclosure;

FIG. 4A is a knowledge management flow diagram according to an example of the present disclosure;

FIG. 4B is a schematic diagram of knowledge disambiguation according to an example of the present disclosure;

FIG. 5 is a schematic diagram of knowledge information content according to an example of the present disclosure;

FIG. 6 is a functional module configuration schematic according to an example of the present disclosure;

FIG. 7 is a schematic diagram of a people management architecture according to an example of the present disclosure;

FIG. 8 is a schematic diagram of log statistics according to an example of the present disclosure;

FIG. 9 is a schematic diagram of an information generating apparatus according to an embodiment of the present disclosure;

FIG. 10 is a schematic diagram of an information generating apparatus according to another embodiment of the present disclosure;

FIG. 11 is a schematic diagram of an information generating apparatus according to yet another embodiment of the present disclosure;

FIG. 12 is a schematic diagram of an information generating apparatus according to yet another embodiment of the present disclosure;

FIG. 13 is a schematic diagram of an information generating apparatus according to yet another embodiment of the present disclosure;

FIG. 14 is a schematic illustration of a presentation interface according to an example of the present disclosure;

fig. 15 is a block diagram of an electronic device used to implement the method of the information generation method of the embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

An embodiment of the present disclosure first provides an information generating method, as shown in fig. 1, including:

step S11: generating an instruction according to the received diagnosis information, and acquiring corresponding knowledge information;

step S12: in the knowledge information, determining knowledge needing to be reminded when the diagnosis information is generated according to a diagnosis information generation instruction;

step S13: and generating reminding information according to the knowledge needing reminding.

In the present embodiment, the diagnosis information generation instruction may be a diagnosis information generation instruction generated in response to a medical staff performing various medical activities such as diagnosis, examination, dressing, prescription, surgery, injection, and examination report in medical and medical-related activities, or may be a diagnosis information generation instruction generated in response to a medical staff performing an arbitrary-purpose prescription line.

The diagnostic information generation instruction may be an instruction to generate diagnostic information for an individual patient.

The corresponding knowledge information may be any medical action related to the diagnostic information generation instruction or knowledge information related to medical supplies and medicines. For example, the diagnosis information generation instruction is used to generate a checklist, which requires the use of the instrument a and the medicine B, and the related knowledge information may be knowledge information of the instrument a and the medicine B.

The knowledge information may also include objective knowledge information that requires special attention in medical activities, or knowledge information related to set safety rules.

For example, the diagnostic information generation instruction is used to generate an examination order that requires the use of the device a and the drug B, and the related knowledge information may be knowledge information of the device a and the drug B, which may include special safety conditions for using the device a and the drug B, requirements for the patient or the type of patient to be accommodated, and so on.

Knowledge information may also include subjective information obtained during a medical activity that may change or personnel information that may change, such as patient registration information, information about the patient that medical personnel manually record during a medical activity.

The knowledge information may include knowledge that needs to be reminded when generating the diagnostic information, which is determined according to the diagnostic information generation command, and knowledge that needs to be reminded when generating the diagnostic information, which may include various requirements, items that need to be noticed, specification of a special processing method, content that is easily overlooked, and the like, in the diagnostic information generation command and the knowledge information.

For example, there may be a plurality of alternative examination modalities for the same medical index or disease, but different examination modalities may be applicable to different patients, for example, some examination modalities are applicable to patients without a certain serious disease, some examination modalities are applicable to adult patients, some examination modalities are not applicable to elderly patients, and so on.

In the knowledge information, the knowledge which needs to be reminded when the diagnosis information is generated is determined according to the diagnosis information generation instruction, and whether the diagnosis information which is generated by the current medical staff possibly has errors which are contrary to the knowledge information or not can be determined according to the diagnosis information generation instruction and the knowledge information. For example, a minor patient may prescribe an examination order that uses an examination modality suitable for adults.

The reminding information is generated according to the knowledge needing to be reminded, and the knowledge needing to be reminded can be displayed in the forms of pop-up boxes and the like in the forms of characters, images and the like, so that medical staff who send the information generation instruction can visually see the reminding information.

The embodiment of the present disclosure can be applied to a medical Clinical Decision Support System (CDSS), which generally refers to a computer System capable of providing Support for Clinical Decision, and the System fully utilizes available and suitable computer technology, and improves and enhances Decision efficiency through a human-computer interaction mode for semi-structured or unstructured medical problems. The CDSS establishes and maintains a medical knowledge map through learning authoritative textbooks, guidelines, high-quality medical records of the third hospital and the like, and creates a multi-model decision system based on AI (Artificial Intelligence) technologies such as the medical knowledge map, natural language processing and the like and strictly following the medical evidence-following rule, so that the CDSS is suitable for all scenes in hospitals (emergency) clinics, wards, inspection departments, pharmacies, nursing and the like. The CDSS system provides clinical decision support services such as auxiliary diagnosis, treatment scheme recommendation, similar medical record recommendation, medical advice quality control, medical record content quality control, medical knowledge inquiry and the like for medical behaviors.

The embodiment of the disclosure can also be applied to a clinical assistant decision integration platform of a CDSS system, namely a unified knowledge background management platform of a plurality of CDSS product lines. CDSS front-end system has many product lines such as standard version, basic edition, reasonable medicine of using, and each product line falls to the ground the back, all needs backstage knowledge management platform, and wherein existing independent function has between the product line, has general function again, and each product line all can use same set of medical knowledge, has consequently designed and has realized CDSS integration platform, promotes the commonality of knowledge, promotes the reasonable division of platform, improves and delivers standardizedly.

In the embodiment, whether the items needing reminding or attention exist can be judged according to the diagnosis information generation instruction and the medical knowledge information, so that good support and assistance effects can be provided for medical diagnosis activities, and the reliability of medical diagnosis behaviors is improved.

In one embodiment, in the knowledge information, determining knowledge that needs to be reminded when the diagnosis information is generated according to the diagnosis information generation instruction comprises:

and when the diagnosis information corresponding to the diagnosis information generation instruction conflicts with the first target knowledge information in the knowledge information, taking the first target knowledge information as the knowledge needing to be reminded.

In this embodiment, the conflict between the diagnostic information corresponding to the diagnostic information generation instruction and the first target knowledge information in the knowledge information may be that the diagnostic information does not meet the requirement of the first target knowledge information, or violates the first target knowledge information.

The first target knowledge information may be a knowledge information, for example, a D-test is suitable for a class E patient.

The first target knowledge information may also be a combination of multiple knowledge information, for example, a D-test is suitable for a class E patient, and the current patient is not a class E patient.

In this embodiment, when the knowledge information includes first target knowledge information that is contrary to the diagnosis information, the information that needs to be reminded is generated according to the first target knowledge information, that is, the medical staff that sends the diagnosis information generation instruction can view or know the first target knowledge information by way of displaying or the like, so that the number of times of generating the diagnosis information by mistake is reduced as much as possible, repeated orders or wrong medical behaviors are avoided being executed due to the generation of the diagnosis information by mistake, and the accuracy and efficiency of the medical behaviors are improved.

when the diagnosis information to be generated by the diagnosis information generation command does not include the notice required by the second target knowledge information in the knowledge information, the second target knowledge information is used as the knowledge to be reminded.

The notice required by the second target knowledge information in the knowledge information may be, for example, a notice and preparation required by the patient for performing the examination, or a missed item of a medicine commonly used by the patient.

Specifically, for example, the test items may be those requiring preparation of a drug to be taken orally in advance, fasting, or the like, or those requiring the discontinuation of a special drug.

In this embodiment, the second target knowledge information that may be omitted can be used as the knowledge that needs to be reminded, and the reminding information is generated according to the second target knowledge information, so that important items can be avoided from being omitted, inefficient situations such as adding orders and changing orders during order opening can be avoided, and omission in the diagnosis information can also be avoided.

In one embodiment, the knowledge information includes at least one of:

medical first knowledge information of a target hospital at which a patient is attending;

patient information extracted from the patient historical diagnostic information;

patient information provided by the patient on his or her own;

inheriting second knowledge information obtained in the hospital from knowledge of the target hospital; the knowledge-inheriting hospital is a hospital capable of sharing the second knowledge information to the target hospital.

The medical first knowledge information of the target hospital where the patient is visiting may be knowledge information used within the target range, may be derived from public medical knowledge, or may be medical knowledge within a knowledge system built in the target hospital itself.

The patient information extracted from the patient historical diagnosis information can be the patient historical examination result, the current fracture, pregnancy, post-operation stage and other specific physical conditions of the patient, the special reaction after the patient takes a specific medicine, the current disease of the patient, the long-term chronic disease of the patient, the internal benign lesion which does not need short-term review in the patient body, the benign lesion which needs short-term review in the patient body, the degree of the benign lesion of the patient, the possible malignant lesion of the patient and the like.

In this embodiment, the patient information provided by the patient may be information that is filled in when the patient registers the patient information in the target hospital, or information that is provided by another person to assist the patient registration and record.

In this embodiment, the knowledge-inheritance hospital may be a hospital in the same system as the target hospital, for example, a hospital that is also affiliated with an F medical research institution, a hospital that is also affiliated with a G medical advanced education institution, or a hospital that is located at a different address in the same hospital.

The knowledge-inheriting hospital may also be a hospital belonging to the same medical general category as the target hospital, such as a hospital belonging to the same specialty as the target hospital, a hospital belonging to the same category of traditional Chinese medicine as the target hospital, and the like.

The knowledge-bearing hospital may be a hospital having a set work transfer/work transfer relationship with the target user. For example, the H hospital is a third-level first hospital and the like, and is a third-level first hospital closest to the I-community hospital, so that medical work to be transferred by the I-community hospital can be transferred to the H hospital by general default, the H hospital can be a knowledge inheritance hospital of the I-community hospital, and the I hospital can also be a knowledge inheritance hospital of the H hospital.

The knowledge-inheriting hospital may also be a specially-pre-established hospital. For example, if there is a certain cooperative relationship between hospital H and hospital J, hospital H and hospital J can be set as knowledge inheritance hospitals.

The knowledge-inheriting hospital may also be a superior hospital of the target hospital or a hospital of the same level as the target hospital.

In the embodiment, the knowledge information can be obtained through multiple ways, so that the content of the knowledge information is greatly enriched, a more complete knowledge map is established, and the convenience, efficiency and accuracy of medical behaviors are improved.

In one embodiment, in the case where the knowledge information includes medical first knowledge information of a target hospital at which the patient is visiting, as shown in fig. 2, the method further includes:

step S21: acquiring autonomous medical knowledge information of a target hospital, wherein the autonomous medical knowledge information comprises autonomous terms used in the target hospital;

step S22: associating the autonomous terms with the general terms in the general medical knowledge information to obtain an association result;

step S23: and taking the correlation result, the autonomous medical knowledge information and the general medical knowledge information as first knowledge information.

The autonomous medical knowledge information of the target hospital may be medical knowledge information used inside the target hospital, such as medical research results of staff inside the target hospital, general habitual knowledge information inside the target hospital, and the like.

The general medical knowledge information may be medical knowledge information in a standard manner, a standard expression, such as standard terms, standard definitions, standard operating specifications, standard medical regulations or specifications, etc., which are well known in the medical field.

The association of the autonomous term with the general term in the general medical knowledge information may be the association of the autonomous term with a standard term expressing the same meaning. For example, a standard name for a disease is associated with a common abbreviation within the target hospital. For another example, drugs belonging to the same number and having different names are associated with each other.

The association result, the autonomous medical knowledge information, and the general medical knowledge information may be used as the first knowledge information, and the autonomous medical knowledge information and the general medical knowledge information may be combined according to the association result, and the combined knowledge information may be used as the first knowledge information.

In the embodiment, the autonomous medical knowledge information and the general medical knowledge information of the target hospital are associated to obtain the first knowledge information fusing the autonomous medical knowledge and the general medical knowledge of the target hospital, so that internal habits and achievements of the target hospital are retained, the general medical knowledge is utilized, the content of the knowledge is enriched, and more valuable reminding information can be provided for medical behaviors.

In one embodiment, the knowledge information comprises knowledge information generated according to original knowledge fields recorded by original files in the repository, and/or knowledge field update contents recorded by patch files of the original files.

In this embodiment, the original knowledge resource may be initially acquired knowledge information, and as the knowledge develops and is updated, a patch file of the original file may be generated for part of the updated knowledge, and the updated knowledge content may be iterated by using part of the patch file.

In the embodiment, partial knowledge content is updated in an iterative manner, instead of replacing all knowledge when new knowledge is generated, so that the replacement time is saved, and the replacement efficiency is improved.

In one embodiment, the diagnostic information generation instruction includes an instruction received by controlling a presentation interface, and the generation process of the presentation interface includes the following steps:

generating a front-end display component according to the customized information of the target hospital;

and generating a display interface according to the front-end display component.

In this embodiment, the customized information of the target hospital may be module information of the target hospital, for example, the generated modules are different for different hospitals. The target hospital's customization information may be used to determine which specific modules need to be provided to the target hospital.

For example, in the case where only primary medical services are provided at a relatively low level of a target hospital, the modules of the basic functions or the primary function modules may be customized by customizing information. In the case where the target hospital is relatively high-level and high-level medical services are provided, the high-level function module or the standard function module may be customized by the customization information.

In this embodiment, the same functional components of the same module can be reused, so that not only can the utilization rate of the components be improved, but also the development operation of the client of the target hospital can be reduced.

In one embodiment, the presentation interface comprises a presentation item for receiving a diagnostic information generation instruction; the method further comprises the following steps:

determining login authority according to information of a login user who logs in the display interface, wherein the login authority comprises default authority corresponding to the identity of the login user and authority authorized by an authorizer of the login user;

and determining the display item according to the login authority.

In this embodiment, the loggers who show the interface may be medical staff. The login authority of the medical staff can be related to the position and department of the medical staff.

The login authority can be determined through the account number, the password and other verification information used by the login user during login. The identity of the login user can be divided by levels or by information such as specific departments.

For example, after a pharmacy staff logs in the display interface, the pharmacy staff can view information of all medicines, but information of functional modules for prescribing the medicines does not exist.

A presentation interface may be as shown in fig. 14, including information in multiple dimensions. In this embodiment, the authorizer of the registrar may be a superior registrar of the registrar. The same management can be performed by level for different loggers. The higher the level of the loggers, the more information can be displayed on the display interface. The login authority of the loggers in the same level may be the same or may be different due to the attribute of the loggers themselves, such as departments. The display interface of the superior loggers can display all information in the display interface of the subordinate loggers, and information which does not exist in the display interface of the subordinate loggers can be authorized for the subordinate loggers, so that the subordinate loggers can also view other authorized information in the display interface.

In the embodiment, the corresponding display items can be determined according to the login permission of the loggers, so that different information can be displayed for different loggers, individuation of the display interface is realized, disorder of the display interface of medical staff caused by too much irrelevant content in the displayed information is avoided, and the work efficiency and the work convenience of the medical staff are improved.

In one embodiment, the front-end display component is generated according to the customized information of the target hospital, and comprises:

according to the customized information of the target hospital, sub-components required by each section are respectively determined;

determining a total set of sub-components required by a target hospital according to the sub-components required by each section;

and generating a front-end display component according to the sub-component total set and the basic configuration corresponding to the target hospital.

According to the embodiment, the target hospital front-end display component can be generated according to specific customized information of the target hospital, so that system configuration can be flexibly increased, and if a certain product line is additionally provided with a new module, only functional modules need to be added under corresponding configuration files. Unified management and distribution as required of the CDSS system can be realized, and delivery standardization of other hospital clients such as a target hospital is improved.

In an example of the disclosure, the CDSS integrated platform mainly includes several modules, such as knowledge management, system management, personnel management, log query, data statistics, medical record quality control, rational medication, License uploading, and the like, wherein the most closely related to the CDSS system is the knowledge management module, which manages knowledge of 26 dimensions, such as medicine, operation, treatment, physical sign, customized population, and the like, the target hospital uploads a term dictionary table on the platform to obtain a corresponding medical knowledge to a local Mongo database, and a rule validation engine of the CDSS system reads the knowledge data to perform medical order quality control, medication quality control, diagnosis quality control function operation, and the like. The term Knowledge is obtained by mapping the full-scale Knowledge stored in advance into a local Mongo library through a disambiguation algorithm of KG (Knowledge Graph).

In this example, the CDSS system architecture is shown in fig. 3. Specifically, the system comprises a CDSS front-end system 31, a database part and a CDSS integration platform 32. The CDSS front-end system comprises a standard edition, a basic edition, a reasonable medicine application edition and the like. The standard edition comprises functional units such as intelligent inquiry, diagnosis recommendation, treatment recommendation, document quality control, medical advice quality control, case knowledge retrieval and the like. The basic edition comprises functional units such as intelligent inquiry, auxiliary diagnosis, treatment recommendation, document quality control, diagnosis quality control, case knowledge retrieval and the like. Rational administration may include functional units such as administration quality control. The CDSS front-end system 31 is used by medical staff for logging in when generating diagnostic information and the like, and provides functions of model calculation and a rule engine. The CDSS integration platform 32 is used for the administrator of the target hospital to perform operations such as adding, deleting, and modifying data. The system specifically comprises functional units such as data statistics (BI, Business Intelligence), knowledge management, system management, personnel management, case quality control, log query, license uploading, rational medication and the like. The CDSS integration platform 32 may manage data stored in the database portion through the CDSS integration platform 32. The data statistics function unit of the CDSS integration platform 32 may obtain the log file from the CDSS front-end system 31 for statistics, and the obtained statistical data may be stored in an ES (Elastic Search) database 33 of the database portion. The database portion also includes a Mongo database 34 for storing term knowledge, a full-scale database 35 for storing full-scale knowledge, and the like.

The target hospital 36 may fuse information such as autonomic knowledge used within the target hospital with full knowledge including standard medical knowledge by uploading term files to the CDSS integrated platform 32.

The CDSS front-end system 31 provides clinical assistance to medical staff at the target hospital based on the information stored in the database section during the work of the medical staff at the target hospital.

In an example disclosed by the invention, knowledge management is a core function of a CDSS (compact description and retrieval) integrated platform, a hospital can import terms belonging to the hospital by uploading a dictionary table in the hospital, adding new terms and the like, the platform compares the total knowledge generated based on a medical knowledge map in a total knowledge base with the uploaded terms through a disambiguation algorithm, and directly pulls the knowledge to a Mongo database if the comparison is successful, and manual intervention comparison is needed if the comparison is to be confirmed or fails, so that the correct knowledge mapping is ensured.

In another specific example, the knowledge management flow is shown in FIG. 4A. The hospital internal glossary 41 is generated through the files such as the dictionary table, the newly added internal knowledge, the data view and the like in the hospital, and the hospital glossary 41 and the standard glossary are disambiguated through the disambiguation algorithm 42. In this example, the disambiguation may be an entity disambiguation, i.e., for named entities, they may tend to be ambiguous themselves, resulting in the possible ambiguity in terms uploaded by the target hospital, and thus requiring disambiguation to correspond to unique KG criteria medical knowledge. The target hospital glossary may be used as an input entity to pull candidate data in the ES database for comparison based on the input entity.

In one specific implementation, for a drug, the pull strategy may be that the name and manufacturer of the drug are consistent with the compared items in the internal glossary 41, i.e., are listed as candidates. For each candidate result, feature extraction is performed in the internal glossary 41 and the standard glossary according to the characteristics of the dosage form, the name, the standard number, the specification, the manufacturer, and the like of the drug. The relevant features are scored from top to bottom according to a rule, with the rule being broader and lower, according to terms extracted from the standard glossary, which may be the same as the internal glossary 41.

The scoring rules may be divided into three by group. The first may be a pre-filtering rule, such as direct filtering to filter drugs in the standard glossary in case of inconsistent drug dosage forms.

The second may be a three attribute comparison rule. For pharmaceutical and non-pharmaceutical products, three gradients can be used, including: the three attributes (name, specification and manufacturer of the medicine) are consistent, and the Chinese and pharmaceutical standards are consistent. The three attributes (name, specification and manufacturer) are consistent. The Chinese medicine standard characters are consistent.

The third type may introduce new criteria for two-attribute comparison rules. For a drug, the manufacturer ignores the specification attribute when only one drug is available. In the case where both attributes (drug name, manufacturer) are consistent and the national drug standard is consistent, or both attributes (drug name, manufacturer) are consistent, the compared terms in the hospital glossary 41 are considered to be consistent with the terms in the standard glossary.

The internal term table 41 is input into a comparison and scoring of the entities and the candidate entities, and the term with the highest score is taken as a comparison term table 44 in the comparison result.

In the internal term table 41, the matching result indicates that it is impossible to determine whether the terms match, and a list 431 to be confirmed may be generated, and confirmation may be performed based on the subsequent confirmation information, and the matching term table 44 may be supplemented according to the confirmation situation.

In the internal term table 41, the term that cannot be matched in the standard term table is indicated by the comparison result, and the list 432 to be supplemented is generated, and the list is confirmed according to the subsequent supplementary information, and the comparison term table 44 is supplemented according to the confirmation condition.

In one specific example, the data format in which the medical term knowledge of the CDSS-integrated platform is stored in the monto database contains four fields, respectively: a term field for recording term information; a base field for recording the base knowledge after comparison; a patch field for recording updates of knowledge; and a data field for recording the current latest knowledge. When the term is disambiguated, the standard medical knowledge in the full-scale knowledge base is pulled and stored in the base field, in which case the data field is the same as the base field.

After the corresponding relationship between the internal term table 41 and the standard term table is completely determined, the local knowledge table of the initial version is generated through the knowledge generation operation 45 and the full-scale knowledge table of the initial version, and after the full-scale knowledge table of the initial version is generated, the local knowledge table of the modified version can be obtained through manual operation and the like according to the full-scale knowledge table of the modified version. In the case where updated knowledge is present, an updated full or local knowledge table may be generated based on only the updated portion. In one specific example of the present disclosure, disambiguation algorithm 42 may also be improved by various versions of the full or local knowledge tables.

In another example of the present disclosure, as shown in fig. 4B, the medical knowledge information disambiguation process comprises:

step S46: and (4) inputting. And inputting the autonomous knowledge information of the target hospital.

Step S47: and (6) candidate pulling. And pulling standard knowledge information which is possibly the same as each piece of autonomous knowledge information according to the autonomous knowledge information and the standard knowledge information of the target hospital.

Step S48: and (5) feature extraction. Feature extraction may be performed on the autonomous knowledge information and the pulled standard knowledge information. The characteristics can be added, combined, modified and deleted through a characteristic manager, and the characteristics can specifically comprise medicine polarity, article specification, name, manufacturer, national drug standard word size and the like.

Step S49: and (6) sorting. And aiming at each piece of autonomous knowledge information, sequencing the candidate standard knowledge information according to the similarity between the pulled candidate standard knowledge information and the pulled autonomous knowledge information.

Step S410: and (6) outputting. And outputting the closest standard knowledge information aiming at each piece of autonomous knowledge information.

In a specific example, the storage of all Knowledge information of a target hospital can be performed by using a structured (Structure) or Semi-structured (Semi-Structure) or a Knowledge database (KB) combining the structured and Semi-structured, and the Knowledge retrieval is performed by means of ES.

In a specific example, updates to the knowledge field can be recorded using a JSON Patch (JS Object Notification Patch) component. A JSON Patch is a format that describes changes to a JSON document and may be used to avoid sending the entire document when only a portion of the document has changed. When used in conjunction with the HTTP (Hypertext Transfer Protocol) Patch method, the JSON Patch allows partial updates to the HTTP API (Application Programming Interface) in a standard-compliant manner. Common operations include add, remove, replace. Therefore, the Patch file generated by combining the JSON Patch component and the HTTP Patch component can be specifically adopted in the disclosed example.

Each time knowledge is updated, the CDSS front end only needs to send patch files to inform of the changed data and does not send the full knowledge data. After the CDSS integrated platform takes the changed data, the CDSS integrated platform calculates through the base field and the patch field to obtain the latest data field, the changed data in the patch file is also retained in the patch field, and the subsequent operation recording module reads the patch field to show the difference between the information before and after the knowledge update, as shown in fig. 5, information such as the operation type, the specific index, the operator, the operation content and the like is recorded. The disclosed example can completely record all changes of medical knowledge in the database part in the life cycle, and all data related to indexes, including operation records composed of operation types (modification, addition or deletion, and the like), operation time, operation contents, and the like.

In a specific implementation manner, considering that more than one community health service center in the primary medical area may have different term knowledge or may adopt the same term knowledge in all areas, to solve the above situation, the CDSS integrated platform of the example of the present disclosure implements regional multi-organization knowledge inheritance. The mechanism storage adopts a tree structure, the superior-subordinate relation among hospitals is obvious and expandable, and the inheritance configuration can be set into various inheritance modes such as all inheritance, inheritance as required and all independence. Each mechanism can maintain own term knowledge and can inherit the term knowledge of the superior mechanism, when the mechanism is configured to be completely inherited, the child mechanism inherits the whole term knowledge of the superior mechanism, when the mechanism is configured to be inherited as required, the child mechanism inherits only partial term knowledge of the superior mechanism, and when the mechanism is configured to be completely independent, the term knowledge of the child mechanism and the term knowledge of the parent mechanism are independent and do not influence each other. Although the processing logic of the knowledge inheritance of multiple mechanisms is complex, the expansibility and flexibility of the system are greatly improved.

In the present disclosure example, both the CDSS front-end system and the CDSS integrated platform may have an update condition, and in this example, a dynamic rendering mechanism is used to render a front-end interface, that is, the front-end interface may be dynamically rendered according to a schema component returned by a back-end, the CDSS front-end page is componentized and configured, the back-end returns API data and the schema component to the front-end, and the front-end page dynamically loads the component and renders according to a component type. Therefore, manual updating of platform operators of the front-end or target hospitals is not needed under the updating condition, workload of front-end personnel participation is low, or development is hardly needed, only a small amount of development manpower is needed, front-end and back-end joint debugging time is saved, and the iteration efficiency of the whole system is greatly accelerated.

In a specific example, the CDSS front-end system has a plurality of product lines such as a standard edition, a basic edition, a rational medicine application and the like, and after each product line falls to the ground, a background management platform is required, wherein the product lines have both an independent function and a general function, and each product line can use the same set of medical knowledge. The disclosed example can realize the function module fusion of multiple product lines of the CDSS front-end system, the platform back-end adopts the configuration file mode, each product line has its own configuration file, for example, in an example, as shown in fig. 6, the front-end system standard edition of the target hospital needs to configure module (or unit, the same back) a, module B, and module C; configuring a module B, a module C and a module D for the basic edition; a module E and a module F are needed to be configured for the reasonable medicine use plate; the control of the medical records needs to configure the module A and the module E, then the rear end fuses the modules under the configuration files of each product line before loading the system configuration, and all the modules of the CDSS integrated platform which are required to be provided for a target hospital under the final configuration file comprise: module A, module B, module C, module D, module E, and module F.

Still referring to fig. 6, the system configuration finally returned by the CDSS platform is a component that is obtained by fusing the whole body (including module a, module B, module C, module D, module E, and module F) obtained by fusing the configuration files such as the standard version, the basic version, the rational medication, the medical record quality control, and the like, with the system configuration existing in the Mongo database again, so that the system configuration can be flexibly increased, and if a new module is added to a certain product line, only the functional module needs to be added to the corresponding configuration file. By the method, the CDSS system can be uniformly managed and distributed as required, and the integrated platform can be well adapted no matter the CDSS deployed currently is a standard edition or a basic edition, so that the delivery standardization is improved.

In the disclosed example, the medical staff's privileges are related to the accounting hierarchy set in the CDSS. The user of the CDSS integrated platform can have three roles: super manager, general user. In a specific implementation manner, the super administrator can be set to have only one character, and the character has no business authority and is only used for performing system-level operations such as personnel management, system configuration, License initialization, knowledge inheritance configuration and the like.

In another specific example, as shown in fig. 7, the personnel management system is an account system adopted by the CDSS integrated platform is in a tree structure, a super administrator may create an administrator and a common user, the administrator may create the administrator and the common user, and the common user does not have the authority of personnel management. The administrator has management authority for deleting, modifying and the like for all lower levels under the own authority tree. For example, administrator B may manage administrator B1, administrator B2, administrator B3, general user B31, administrator B31, administrator B311, while administrator B31 may only manage administrator B311. If the administrator B is deleted, the administrator B1, the administrator B2, the administrator B3 and all the subordinates thereof are hung below the super administrator according to the original authority, and the whole personnel system tree cannot be disconnected by deleting one person in the middle. The service authority of the user is given to the next level through the super manager, the authority of the subordinate user cannot exceed the authority owned by the superior user, the authority which the superior user does not have cannot be given to the subordinate user, and when a certain authority of the superior user is deleted, all users under the authority tree can delete the authority. The tree structure design can ensure that the permission of the platform is minimized, and redundant permissions are avoided.

In an implementation manner, considering that a medical institution deploying a standard version of a CDSS front-end system needs to improve the electronic medical record rating capability, and a medical institution deploying a basic version of the CDSS front-end system needs to check the CDSS use condition of each medical point in an area, a platform integrates a standard version BI and a basic version BI, and meets the requirements of different product lines through the standard version BI and the basic version BI, respectively, as shown in fig. 8, the platform can perform log analysis statistics, expression proportion, change trend and other information on various statistical charts at different times. The CDSS system writes operations into a central control log when performing various diagnostic quality controls and medical order quality controls, analyzes the daily log once every certain time (for example, 5 minutes) by an offline analysis log script, writes a result of a statistical index generated after data generated within a certain time interval is subjected to logic processing into the ES, and the CDSS integrated platform directly reads the result of the ES to display the result on the platform. In addition, the CDSS integration platform also has various offline tools to guarantee the problem of BI historical data caused by server migration, faults and the like, and the delivery stability is guaranteed.

The knowledge disambiguation comparison is carried out through the disclosed example, the disambiguation algorithm solves the problem of term coding confusion, and the knowledge generated based on the medical knowledge map is mapped to hospital terms and has uniqueness. Meanwhile, management of different versions of knowledge can be realized: knowledge data change can be managed through the JSON Patch component, and operation can be recorded, so that the difficulty of incremental updating is solved.

The knowledge inheritance of multiple mechanisms is performed by the disclosed examples: a large amount of knowledge dimensions such as medicines support regional multiple mechanisms, knowledge inheritance configuration is supported, and SaaS (software as a service) upgrading of CDSS is achieved.

Project iteration efficiency can be improved through the dynamic rendering mechanism of the disclosed example. Because the platform page adopts a dynamic rendering mechanism, the front end performs dynamic rendering according to the schema component returned by the back end, the component is reused, only incremental development is needed, the manpower input by the front end development is reduced, and the project iteration efficiency is greatly improved.

The integration of multi-product line modules is carried out through the disclosed example, the functional modules of each product line of the CDSS are combined, unified management is carried out, distribution is carried out according to needs during delivery, delivery standardization is improved, and personalized customization is not needed for different product lines.

By performing authority control through the disclosed example, the CDSS integrated platform strictly limits system function allocation and personnel authority. After the CDSS integrated platform is delivered, the CDSS integrated platform can be used only after being authorized and initialized by License, and the authority of platform personnel is given layer by the creation of superior personnel, so that the platform function can not be used more hierarchically.

In addition, the CDSS platform of the example disclosed by the disclosure also supports statistics of data generated by the CDSS service and generation of a visual report, covers indexes of all services such as CDSS standard version, basic level version and reasonable medication, and can be used as an important standard of hospital rating.

In this embodiment, a certain contribution can be made to quality control of medical actions, a certain problem can be found, and quality of generation of diagnostic information such as medical orders can be improved.

An embodiment of the present disclosure further provides an information generating apparatus, as shown in fig. 9, including:

a knowledge information obtaining module 91, configured to obtain corresponding knowledge information according to the received diagnosis information generation instruction;

the knowledge determining module 92 is configured to determine, in the knowledge information, knowledge that needs to be reminded when the diagnostic information is generated according to the diagnostic information generation instruction;

and the reminding information generating module 93 is used for generating reminding information according to the knowledge required to be reminded.

In one embodiment, as shown in FIG. 10, a knowledge determination module includes:

the first determining unit 101 is configured to, when the diagnostic information corresponding to the diagnostic information generation instruction conflicts with the first target knowledge information in the knowledge information, use the first target knowledge information as the knowledge that needs to be reminded.

In one embodiment, as shown in FIG. 11, a knowledge determination module includes:

the second determining unit 111 is configured to determine the second target knowledge information as knowledge to be reminded when the diagnosis information to be generated by the diagnosis information generation instruction does not include the notice required by the second target knowledge information in the knowledge information.

In one embodiment, the knowledge information includes at least one of:

patient information provided by the patient on his or her own;

In one embodiment, in a case where the knowledge information includes medical first knowledge information of a target hospital at which the patient is visiting, as shown in fig. 12, the information generating apparatus further includes:

an autonomous knowledge module 121 for acquiring autonomous medical knowledge information of the target hospital, the autonomous medical knowledge information including autonomous terms used inside the target hospital;

the association module 122 is configured to associate the autonomous term with a generic term in the generic medical knowledge information to obtain an association result;

a first knowledge information module 123, configured to use the association result, the autonomous medical knowledge information, and the general medical knowledge information as the first knowledge information.

In one embodiment, the presentation interface comprises a presentation item for receiving a diagnostic information generation instruction; as shown in fig. 13, the information generating apparatus further includes:

the authority determining module 131 is configured to determine a login authority according to information of a login user who logs in the display interface, where the login authority includes a default authority corresponding to an identity of the login user and an authority authorized by an authorizer of the login user;

and the display item module 132 is used for determining the display item according to the login authority.

In one embodiment, the generating of the presentation interface includes generating a front-end presentation component according to the customized information of the target hospital, including:

The embodiment of the disclosure can be applied to the artificial intelligence fields of big data, knowledge maps, artificial intelligence medical treatment and the like.

In the technical scheme of the disclosure, the acquisition, storage, application and the like of the personal information of the related user all accord with the regulations of related laws and regulations, and do not violate the good customs of the public order.

The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.

FIG. 15 shows a schematic block diagram of an example electronic device 150 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 15, the apparatus 150 includes a computing unit 151 that can perform various appropriate actions and processes in accordance with a computer program stored in a Read Only Memory (ROM)152 or a computer program loaded from a storage unit 158 into a Random Access Memory (RAM) 153. In the RAM 153, various programs and data necessary for the operation of the device 150 can also be stored. The calculation unit 151, the ROM 152, and the RAM 153 are connected to each other by a bus 154. An input/output (I/O) interface 155 is also connected to bus 154.

A number of components in device 150 are connected to I/O interface 155, including: an input unit 156 such as a keyboard, a mouse, or the like; an output unit 157 such as various types of displays, speakers, and the like; a storage unit 158 such as a magnetic disk, an optical disk, or the like; and a communication unit 159, such as a network card, modem, wireless communication transceiver, or the like. The communication unit 159 allows the device 150 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunications networks.

Computing unit 151 may be a variety of general purpose and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 151 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 151 executes the respective methods and processes described above, such as the information generation method. For example, in some embodiments, the information generation method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 158. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 150 via the ROM 152 and/or the communication unit 159. When the computer program is loaded into the RAM 153 and executed by the computing unit 151, one or more steps of the information generating method described above may be performed. Alternatively, in other embodiments, the computing unit 151 may be configured to perform the information generation method by any other suitable means (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.

It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.

The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. An information generating method, comprising:

in the knowledge information, determining knowledge needing to be reminded when the diagnosis information is generated according to the diagnosis information generation instruction;

and generating reminding information according to the knowledge needing to be reminded.

2. The method of claim 1, wherein the determining, in the knowledge information and according to the diagnostic information generation instruction, knowledge that needs to be reminded when generating diagnostic information includes:

and under the condition that the diagnosis information corresponding to the diagnosis information generation instruction conflicts with first target knowledge information in the knowledge information, taking the first target knowledge information as knowledge needing to be reminded.

3. The method according to claim 1 or 2, wherein the determining, in the knowledge information and according to the diagnosis information generation instruction, knowledge that needs to be reminded when generating diagnosis information includes:

and when the diagnosis information to be generated by the diagnosis information generation instruction does not contain the attention required by the second target knowledge information in the knowledge information, taking the second target knowledge information as the knowledge required to be reminded.

4. The method of any of claims 1-3, wherein the knowledge information comprises at least one of:

patient information provided by the patient on his or her own;

inheriting second knowledge information obtained in the hospital from knowledge of the target hospital; the knowledge inheritance hospital is a hospital that can share second knowledge information to the target hospital.

5. The method of claim 4, wherein in the event that the knowledge information includes medical first knowledge information of a target hospital at which the patient is visiting, the method further comprises:

acquiring autonomous medical knowledge information of a target hospital, wherein the autonomous medical knowledge information comprises autonomous terms used inside the target hospital;

associating the autonomous term with a general term in general medical knowledge information to obtain an association result;

taking the correlation result, the autonomous medical knowledge information, and the general medical knowledge information as the first knowledge information.

6. The method according to any one of claims 1 to 5, wherein the knowledge information comprises knowledge information generated according to original knowledge fields recorded by original files in a repository, and/or generated according to updated contents of knowledge fields recorded by patch files of original files.

7. The method according to any one of claims 1-6, wherein the diagnostic information generation instructions include instructions received through a control presentation interface, the generation of which comprises the steps of:

and generating the display interface according to the front-end display component.

8. The method of claim 7, wherein the presentation interface includes a presentation item for receiving the diagnostic information generation instruction; the method further comprises the following steps:

and determining the display item according to the login authority.

9. The method of claim 7 or 8, wherein the generating a front-end presentation component according to the customized information of the target hospital comprises:

determining a total set of sub-components required by the target hospital according to the sub-components required by each section;

10. An information generating apparatus comprising:

11. The apparatus of claim 10, wherein the knowledge determination module comprises:

and the first determining unit is used for taking the first target knowledge information as the knowledge needing to be reminded when the diagnosis information corresponding to the diagnosis information generating instruction conflicts with the first target knowledge information in the knowledge information.

12. The apparatus of claim 10 or 11, wherein the knowledge determination module comprises:

and a second determination unit configured to determine, when the diagnostic information to be generated by the diagnostic information generation instruction does not include a notice required by second target knowledge information in the knowledge information, the second target knowledge information as knowledge to be reminded.

13. The apparatus of any of claims 10-12, wherein the knowledge information comprises at least one of:

patient information provided by the patient on his or her own;

14. The apparatus of claim 13, wherein in the case where the knowledge information includes medical first knowledge information of a target hospital at which the patient is visiting, the apparatus further comprises:

an autonomous knowledge module for obtaining autonomous medical knowledge information of a target hospital, the autonomous medical knowledge information including autonomous terms used inside the target hospital;

the association module is used for associating the autonomous term with a general term in the general medical knowledge information to obtain an association result;

a first knowledge information module for taking the correlation result, the autonomous medical knowledge information, and the general medical knowledge information as the first knowledge information.

15. The apparatus according to any one of claims 10 to 14, wherein the knowledge information comprises knowledge information generated according to original knowledge fields recorded by original files in a repository, and/or generated according to updated contents of knowledge fields recorded by patch files of original files.

16. The apparatus according to any one of claims 10-15, wherein the diagnostic information generation instructions include instructions received by controlling a presentation interface, the presentation interface generation process including the steps of:

17. The apparatus of claim 16, wherein the presentation interface comprises a presentation item for receiving the diagnostic information generation instruction; the device further comprises:

the authority determining module is used for determining login authority according to information of a login user who logs in the display interface, wherein the login authority comprises default authority corresponding to the identity of the login user and authority authorized by an authorizer of the login user;

and the display item module is used for determining the display item according to the login authority.

18. The apparatus according to claim 16 or 17, wherein the generating of the presentation interface includes generating a front-end presentation component according to the customized information of the target hospital, including:

19. An electronic device, comprising:

at least one processor; and

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-9.

20. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-9.

21. A computer program product comprising computer programs/instructions, characterized in that the computer programs/instructions, when executed by a processor, implement the steps of the method of any of claims 1 to 9.