CN111627525A - Management method, system and equipment for diet related rules - Google Patents
Management method, system and equipment for diet related rules Download PDFInfo
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Abstract
The invention discloses a management method, a system and equipment of diet related rules, which are used for marking each diet related rule in a database according to the source and the content of the rule, selecting proper rules according to the marks according to the actual conditions of consumers, generating a diet related personalized rule base meeting the requirements of the consumers and being applied to an intelligent medical system of the consumers. By the method, the system and the equipment for managing the diet-related rules, the rule set meeting the requirements of consumers can be selected as the diet-related personalized rule base of the health management system/the diet management system based on the current situations of different business units, the rules can be adjusted in real time, an information rule management system can be quickly established by taking the diet-related rationality analysis requirements as the target, and the purposes of improving the diet safety of the consumers, improving the life quality, reducing unreasonable medical expenses and reasonably distributing medical resources are achieved.
Description
Technical Field
The invention relates to the technical field of intelligent health management information processing, in particular to a management method, a system and equipment for diet related rationality rules.
Background
People take food as days, and the food is the first need of life of people. The diet comprises drinks and foods, and along with the continuous improvement of the living standard of people, people pay more and more attention to the food therapy and health preservation, and the health care foods are also more and more popular. The health food has specific health function or is intended for supplementing vitamins and minerals, and is suitable for specific people, and has effects of regulating organism function, treating diseases, and preventing acute, subacute or chronic harm to human body. Whether the diet is reasonable and directly related to the safety, health and the like of each person is the key for guaranteeing the human health, controlling unreasonable cost and maintaining the rights and interests of consumers.
With the development and application of modern information technology, the appearance of the intelligent health management system/diet management system provides a good auxiliary tool for intelligent analysis, intelligent management and intelligent recommendation related to diet, so that comprehensive acquisition, analysis and application of mass data become possible, and great effect is gradually played in the aspect of guaranteeing reasonable diet of consumers.
The working principle of the intelligent health management system/diet management system in the aspect of reasonable diet management is that the reasonability of diet of consumers is analyzed according to the actual life and health information of the consumers by taking a rule determined in advance as a standard, or the corresponding diet is intelligently recommended according to the condition of the consumers. Therefore, the key point of assisting diet management by using the intelligent health management system is to establish a set of practical, balanced and scientific diet-related standard rules, so that doctors, pharmacists, health managers, dieticians or consumers and related managers can be assisted to analyze the reasonability of diet of the consumers or recommend related diet to the doctors, the dieticians, the consumers and the like according to the actual conditions of the consumers, so as to achieve the purposes of preventing, finding and avoiding various diet-related risks. The rules in the intelligent health management system/diet management system are based on medical treatment and food related data and data, and are combined with the actual situation of consumers to generate specific reasonable diet related rules by methods of manual processing, big data mining, artificial intelligence deep learning and the like, so the range of rule sources and the actual application level are of great importance to the practicability of the system.
By taking the intelligent health management system/diet management system to assist diet-related rationality analysis as an example, if the standard of the system rule is too low, a large number of false negative analysis results may occur, so that many risks cannot be found by the system, the targets of managing and controlling and inhibiting unreasonable diet-related phenomena cannot be achieved, and the health of the consumer will face risks. Conversely, if the criteria of the system rules are too high, a large number of false positive analysis results may occur, taking some practically rational diets as a problem, and interfering with the normal life of the consumer.
The data of various dietotherapy recipes, the nutritional composition of diet, health food specifications, special medical food/functional beverage specifications, the processing technology of various foods and beverages, the raw materials of various foods and beverages, the nutritional components and content of various foods and beverages, nutritional guidelines and the like are used as professional basis for doctors, health managers and nutriologists to make diet-related plans for consumers, and the related contents are the sources of rules of diet management. The existing diet management system basically establishes system standard rules by taking clinical guidelines, nutritional guidelines and other authoritative data as sources. However, since some of the data source standards, updated versions, changed sources, etc. included in the standard rules have great randomness, it is not easy to know which rules derived from the data such as specifications, guidelines, etc. are included in the standard rules during the process of using the system, and it is not known what version of data is specifically included, there is no way to manage the standard rules used by the user, and it is not possible to accurately control the rationality of the diet analysis based on the standard rules, and it is not possible to establish a diet-related rationality rule standard data system that meets the conditions of the user. Therefore, a method, a system and a device for managing diet related rules according to consumer conditions are needed, so that doctors, nurses and dieticians including consumers and other users of the health management/diet management system can conveniently, accurately and scientifically generate and maintain related rule bases, so that the intelligent health management system can better meet the actual needs of the consumers, assist the users to find and avoid related risks possibly occurring in the diets of the consumers, and provide more reasonable diet suggestions for the consumers.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method helps users of medical institutions, health management institutions/personnel and the like to select proper data ranges and data levels as a basis according to the actual conditions of consumers, establish scientific, practical and balanced diet related rules, and dynamically manage rules corresponding to related contents and data to realize that related intelligent systems can be applied to different consumer groups, and assist users of intelligent health management systems/diet management systems such as doctors, pharmacists, dieticians and health managers to carry out diet-related services such as reasonableness analysis, recommendation, guidance, management, evaluation and the like, so that the intelligent health management systems, particularly the diet management systems, can guarantee reasonable diets of different consumers, and play a greater role in maintaining the safety, health and the like of the consumers.
The invention is realized by the following technical scheme:
the invention provides a method for managing diet-related rules, wherein the diet-related rules comprise rules related to diet-related rationality, and the method comprises the following steps:
marking each/each group of diet-related rules in the database according to the source of the diet-related rules and the content of the rules;
selecting proper rules according to the marks according to the actual conditions of the consumers to generate a diet-related personalized rule base meeting the requirements of the consumers;
the diet-related personalized rule base is applied to the intelligent health management system/diet management system of the consumer.
The method for managing diet-related rules as described above, wherein the source mark of the rules includes at least one of geographic source-related mark, institution source-related mark, material source category-related mark, author source-related mark, evidence level-related mark, administrative certification/recommendation level-related mark, and time/version-related mark.
The method for managing the intelligent diet-related rule comprises the following steps of marking at least one of diet-related marks, analysis item-related marks, diet efficacy-related marks, crowd-related marks, disease-related marks, treatment effect-related marks, personnel-related marks and consumer use-related marks.
A method of managing a diet-related rule as described above, the method further comprising:
the method comprises the steps of setting corresponding grades/scores for part/all marks of each rule/each group of rules according to consumer conditions, and setting relative weights of each mark classification according to actual conditions, so that when a user selects a proper rule, the comprehensive grade/score of the related rule can be calculated according to the grade/score corresponding to each mark of the related rule and the relative weight of each mark classification, and the user can conveniently select the proper rule.
A method of managing a diet-related rule as described above, the method further comprising: the user can set up individualized rule systems of different business subunits according to the requirements of consumers served by the business of each subunit on the basis of the unified rule base, and each subunit is adjusted on the basis of the unified rule base according to the business requirements of the subunit, including the adjustment of the selection of the rules and the adjustment of the application level of the rules, so as to support the relevant requirements of each subunit on the rules.
The management method of the diet-related rules further comprises the step that the user optimizes the diet-related personalized rule base according to the requirements of the consumers, wherein the optimized personalized rule base is realized by adjusting, adding or modifying the selection conditions of the rules of the personalized rule base or modifying the related rules.
A method of managing a diet-related rule as described above, the method further comprising: and comparing the diet related data of the consumers with related rules in the diet related rules in the database, and analyzing the related rules of the diet related of the consumers and the source distribution and the specific content of the rules.
A method of managing a diet-related rule as described above, the method further comprising: the use of rules may be ranked according to the needs of different consumers, and may include: the system comprises at least one level of non-enabling, mandatory, fixed, recommended, suggested, fair, conditional fair, prompt, alert, warning, limit, conditional pass, forbidden, strict forbidden, mandatory forbidden, etc., to support the user's relevant application requirements for different rules.
A method of managing a diet-related rule as described above, the method further comprising: according to the requirements of different users/consumers, a display method of the rules and the marks can be set, so that the users/consumers can view related marks of the diet related rules used in the intelligent health management system/diet management system or view rules corresponding to the related marks.
The present invention also provides a system for managing a diet-related rule including a diet-related rationality rule, the system comprising:
a rule marking unit for marking each/every group of rules in the diet-related rules in the database according to the source of the rules and the content of the rules;
a rule selection unit for selecting an appropriate rule according to the label according to the consumer's demand;
and the rule base generation unit is used for generating the selected rules into an individualized rule base meeting the requirements of consumers and applying the individualized rule base to the intelligent health management system/diet management system.
The present invention also provides a management apparatus for a diet-related rule including a diet-related rationality rule, the management apparatus including:
a rule marking module for marking each/each group of diet related rules in the database according to the source of the rules and the content of the rules;
the rule selection module is used for selecting proper rules according to the requirements of the consumers and the marks;
and the rule base generation module is used for generating a diet-related personalized rule base meeting the requirements of consumers according to the selected rules and applying the personalized rule base to the intelligent health management system.
According to the management method, the management system and the management equipment of the diet-related rules, each rule in the diet-related rules in the intelligent health management system is marked according to the source and the content of the rule, and a user generates a diet-related personalized rule base which meets the requirements of consumers according to the requirements of the consumers to which the user faces and the marked proper rule, and the diet-related personalized rule base is applied to the intelligent health management system. By the method, the system and the equipment for managing the diet related rules, different users can select practical and balanced diet related rule construction standards according to the requirements of the users, select proper data ranges and data levels as the basis to establish a diet related rule base to be applied to an intelligent health management system aiming at different business units, and can dynamically manage related data, so that the users can apply the intelligent health management system to play a greater role in guaranteeing the reasonability and the standard of diet related of the consumers, reducing diet related risks, controlling unreasonable medical expenses and maintaining the safety and rights and interests of the consumers.
Drawings
FIG. 1 is a flowchart of a method for managing diet-related rules according to a first embodiment of the present invention.
Fig. 2 is a system block diagram of a diet-related rule management system according to a second embodiment of the present invention.
Fig. 3 is a hardware block diagram of a diet-related rule management apparatus according to a third embodiment of the present invention.
Detailed Description
To further explain the technical means and effects of the present invention adopted to achieve the intended purpose, the following detailed description of the embodiments of the present invention is provided in conjunction with the accompanying drawings and examples.
Consumers in the present invention refer to subjects analyzed and served by the health management/diet management system, including the general population, and may also include patients in need of nutritional treatment such as: the food can be used for diabetes patients, rickets patients, athletes, weight reducing people, pregnant women, etc. with sugar-free food.
The user in the present invention refers to a user of a health management/diet management system such as a medical institution, a physical examination institution, a pharmacy, a health management company, a health insurance company, a family, a doctor, a nurse, a dietician, and a health manager.
The rules of the invention can be applied to health management systems, diet management systems, and nutrition management systems to provide dietary services to consumers. The system can also be applied to medical systems such as intelligent medical systems, intelligent medication management systems, operation management systems, rehabilitation management systems, medical advice management systems and the like, and is used for providing diet and nutrition support for treatment of patients.
The user business requirements of the present invention refer to the needs of consumers managed and served by the user in relation to a reasonable diet, including efficacy requirements, personalized preference requirements, contraindications, situations requiring caution/attention, allergy situations, medical insurance/welfare situations, economic situations, etc.
In managing diet-related rules, consumers may be individual users or a similar group of people. The related rules can be uniformly formulated and selected according to a class of consumer groups, the consumers can be classified and grouped according to the commonalities and differences of the consumers, and the groups of rules of the class are individually adjusted on the basis of the unified rules of all the classes. The personalization rules can also be managed according to the situation of the individual user.
A first embodiment of the present invention is described with reference to fig. 1. FIG. 1 is a method flow diagram of a method of managing diet-related rules in accordance with the present invention. The invention relates to a management method of an intelligent health management system rule base, wherein the intelligent health management system rule base comprises diet related rationality rules, and the management method of the intelligent health management system rule base comprises the following steps:
s1: each/each set of diet-related relevant rules in the database is tagged according to the source of the rule and the content of the rule.
S2: and selecting a proper rule by the user according to the service requirement and the mark to generate a diet-related personalized rule base meeting the requirement of the consumer.
S3: the diet-related personalized rule base is applied to an intelligent health management system of a consumer.
In the present invention, the mark is a name, and may include various marks, classifications, labels, features, keywords, etc., and if the data is classified according to the issuing organization, the organizations with different attributes, the organization levels and the specific organization names are the classified paths and the classification names, that is, the corresponding marks.
If a user needs to use the intelligent health management system, particularly the diet-related system, to analyze, recommend and guide the diet-related of the consumer, the system should first include diet-related rules, the rule base of the intelligent health management system includes diet-related rationality rules, and the intelligent health management system screens the relevant diet problems according to the diet-related rationality rules in the rule base as a standard. The database in S1 may be a public database, a database provided by a relevant government department/business platform/enterprise/academic organization, or a database created by a user. The sources of relevant dietary rules in the database are based on dietary recipes, nutritional composition of diets, health food specifications, specialist food/functional beverage specifications, processing of various foods and beverages, raw materials of various foods and beverages, nutritional composition and content of various foods and beverages, route and geographical distribution of various foods and beverages (e.g., restaurant maps, shopping mall maps, list of electronic commerce commodities, delivery range and time, etc.), storage manner and storage time of various foods and beverages, prices of various foods and beverages, medical discussion (e.g., compendium of herbs), raw material production place and grade specifications, processing/cooking method guidelines and books, nutritional guidelines and books, industry specifications, textbooks, expert consensus, relevant conference presidentifications, treatises, monographs, inventions, scientific inferences, Experimental reports, analytical reports, test reports, food reviews, restaurant features and evaluation ratings, chef features and evaluation ratings, reports/reports, user scores, test reports, approval documents, relevant regulations, relevant religious beliefs and dietary norms, relevant local diet customs, relevant guidance opinions, relevant policies, relevant systems, relevant catalogs, relevant literature data, relevant price policies, relevant insurance payment protocols, other literature data, other research results with professionality/authority, can be based on a method of evidence-based medicine/nutrition, or probability speculation based on existing data, can also comprise databases established by sources such as various weights/various levels/various ranks needing to be set manually, and can also comprise databases established by information reforming/information analysis/big data analysis, the system can also comprise a database established through artificial intelligence deep learning, a database obtained through data mining and analysis, rules and indexes manually set through data statistical analysis/artificial intelligence deep learning, and related information and rules which are continuously accumulated and refined through experts and dieticians in the working process. The diet database may also be a database built by a combination of the above methods.
In the present invention, diet-related includes, but is not limited to, drinks and foods, and also includes health foods, specialist foods and functional drinks. The drink comprises: water, tea drinks, alcohol drinks, caffeine drinks, carbonic acid drinks, milk drinks, vegetable and fruit juice drinks and the like. The food comprises: solid food, fluid food, liquid food (e.g., soup), and the like. The health food has specific health function or is intended for supplementing vitamins and minerals, and is suitable for specific people, and has effects of regulating organism function, treating diseases, and preventing acute, subacute or chronic harm to human body. The special medical food is a formula food with special medical application, namely a formula food which is specially processed and prepared for meeting the special requirements of people with limited food intake, digestive absorption disorder, metabolic disorder or specific disease states on nutrients or diet. The functional beverage is a beverage which can regulate the functions of human bodies to a certain extent by adjusting the components and the content proportion of nutrients in the beverage.
In the invention, by establishing various marks for the diet-related rationality rules, a user can conveniently and quickly select the rules with suitable marks according to the needs of the consumer to generate a diet-related personalized rule base meeting the needs of the consumer, and the method is applied to an intelligent health management system to carry out intelligent analysis on diet-related services, and the specific application mode comprises diet-related auditing, recommending, guiding, managing and the like. The labeling of diet-related rules may be based on the source of the rules and the content of the rules.
The indicia of origin of the diet-related rules may include geographic origin-related indicia, institution origin-related indicia, material origin category-related indicia, author origin-related indicia, evidence-level-related indicia, administrative certification/recommendation-level-related indicia, time/version-related indicia, etc., or other indicia related to the origin of the rules.
The geographical origin related mark may be marked in a hierarchical manner according to geographical related information, such as continent, region (large), country, region, province (direct prefecture city), city/state/region (small), county, district, and the like. Such as: southeast Asia, USA, Beijing, etc.
The organization source related indicia may be marked according to a drafting/editing/publishing/distributing/issuing/promulgating/publishing/offering organization or platform of the rule source. Including but not limited to: marking according to professional attributes of relevant mechanisms, organizations or platforms; marking according to the administrative attributes of related mechanisms, organizations or platforms; labeling according to authority, specialty and influence of relevant organizations, organizations or platforms; the tags are made according to the relevance of the relevant organization, organization or platform to the consumer. Professional attributes of the relevant organization, organization or platform may include: nutrition research institutions, health research institutions, medical management, pharmacogenomics, medical insurance, medicine, pharmacy, finance, administration, regulation, price, tender purchases, and the like. Administrative attributes of a relevant organization, or platform may include: professional academic groups, industry associations/colleges, academic unions/platforms, government agencies, legislative bodies, judicial bodies, medical insurance agencies, medical groups/conjunctions/alliances/institutions, schools/colleges, research institutes, data analysis agencies, consulting agencies, magazines/journals/newspapers/publishers/professional websites/professional network platforms, and the like. Such as: the guidelines issued by the world health organization, the institutional source names of the rules generated by the guidelines being labeled: the world health organization; the institutional administration attributes are labeled: the international organization belongs to a special institution; the authoritative label is: one stage, etc.
The related mark of the data source category can be marked according to the data type of the rule source and the value of the specific element thereof, and the data type includes but is not limited to: recipes, quality standards, processing techniques, instructions, guidelines, consensus, guidelines, pharmacopoeia, formulary, norms, standards, META analysis reports, data/literature analysis reports, experiments/test reports, research reports, survey reports, monographs/monographs, classical works, classical parties, expert biographies, textbooks, training materials, science popularization articles, medical records/medical records, reports, databases, insurance payment catalogues, bid catalogues, purchase catalogues, price catalogues, and the like.
Author source related tags may be tagged according to the drafter/researcher/author/designer of the rule source.
Evidence level related indicia may be based on evidence levels of rule sources such as: the sources from related laws and regulations or future sources are marked according to evidence grading of evidence based medical methods, including relevant national laws and regulations and relevant international organization laws and regulations, and relevant evidence based medical grading, and specific evidence based medical grading methods include but are not limited to: the method comprises the following steps of carrying out source evidence grade/recommendation grade grading according to the method in the generation process of rule sources and marking the method and the grade according to the method. And the user can customize an evidence level division method according to business needs and mark related evidence.
The administrative certification/recommendation level related marks can be marked according to the administrative certification/recommendation level of the rule source, including the authorities authenticating or rating the related sources by the administrative authorities, industry management authorities, credit evaluation authorities, certification authorities, social organizations, industry organizations and the like, and specific certification or evaluation levels, such as: mandatory level, recommended level, advised level, rational level, prompt level, warning level, restricted level, forbidden level, etc. For example, the relevant industry standards issued by food and drug administration are mandatory.
The time/version related tags may be tagged according to the time and version of the rule source, including but not limited to: source material discussion, formulation, release, revision, publication, validation, revocation, time/version numbers, or related meetings, etc. Such as: the sources of relevant rules for the michelin guideline 2020 shanghai are labeled: geographic origin-Shanghai; organization source, michelin website; time/version-2020.
When the relevant rules are marked according to the sources of the diet relevant rationality rules in the database, various marks of the rule sources can be graded or scored according to the business requirements of different consumers, so that a user can conveniently select the diet relevant rationality rules suitable for the consumers facing the user. The source tags may be ranked in terms of authority/expertise/credibility/influence/applicability, etc. Such as: for the data source related mark, according to the existing related regulations, the diet related specification is the legal diet related basis, the data source related mark from the rules of the health food specification can be set to 1 grade, and for the medical institution user, the authority data source related mark grade can be set to 2 grade, which is lower than the diet specification.
Content indicia for rules in the database may include analysis item related indicia, diet related indicia, usage purpose related indicia, crowd related indicia, disease related indicia, treatment effect related indicia, personnel related indicia, consumer usage related indicia, and other indicia related to the content of the rules.
The analysis item related mark may be marked according to the level and content of the analysis item and its analysis result related to the rule, and may include: at least one of a correlation analysis of efficacy needs, a correlation analysis of personalized preference needs, a correlation analysis of contraindications, a correlation analysis of caution/attention needed, a correlation analysis of interactions, a correlation analysis of allergies, a correlation analysis of shelf life, a correlation analysis of time, a correlation analysis of processing/cooking/eating/drinking methods, a correlation analysis of intake, a correlation analysis of adverse reactions, a correlation analysis of monitoring/assessment measures before/during/after eating, a correlation analysis of medical insurance/welfare, a correlation analysis of economics, a correlation analysis of acquaintance, a correlation analysis of administrative management, a correlation analysis of colloquial moods. For example, the contraindication related markers can comprise specific contraindications, and can be classified into markers of strict, forbidden, unreliability, cautious development, balanced profit and disadvantage development and the like according to severity. For example, administrative related analysis may include: related regulations for protecting wild animals and plants, fishing prohibition regulations and the like.
The diet-related mark can be marked according to the diet related to the rule, including drinks and foods, health-care foods, special medical foods, functional drinks and the like. The drink comprises: water, tea drinks, alcohol drinks, caffeine drinks, carbonic acid drinks, milk drinks, vegetable and fruit juice drinks and the like. The food comprises: solid food, fluid food, liquid food (e.g., soup), and the like. The health food has specific health function or is intended for supplementing vitamins and minerals, and is suitable for specific people, and has effects of regulating organism function, treating diseases, and preventing acute, subacute or chronic harm to human body. The special medical food is a formula food with special medical application, namely a formula food which is specially processed and prepared for meeting the special requirements of people with limited food intake, digestive absorption disorder, metabolic disorder or specific disease states on nutrients or diet. The functional beverage is a beverage which can regulate the functions of human bodies to a certain extent by adjusting the components and the content proportion of nutrients in the beverage.
The usage purpose related mark can be marked according to the usage purpose related by the rule and the value of the specific element thereof, and comprises the following steps: supplementing nutrients, supplementing energy, supplementing water, recovering after operation, controlling calorie intake, coordinating exercise, assisting treatment, regulating appetite, supplying nutrition during pregnancy, supplying nutrition during lactation, and supporting nutrition.
The crowd-related indicia may be marked according to a consumer crowd involved by the rule, including: age, sex, race, weight, genetic-related conditions, family health-related conditions, allergy history, living environment, native place, taste, learning conditions, working conditions, family conditions, hobbies, growth and development, physiological stage, marriage and breeding conditions, eating conditions, work and rest habits, physical disability conditions, mental health conditions, intelligence conditions, immunity conditions, and the like. Consumers herein may also include patients in need of nutritional treatment such as: the food can be used for diabetes patients, rickets patients, athletes, weight reducing people, pregnant women, etc. with sugar-free food.
Disease-associated markers may be labeled according to the disease to which the rule relates, including specifically: disease, symptom, index, feeling, medical history, symptom type, examination result, risk factor, medical history, surgical history, medication history, family medical history, etc. Such as: family history of hemophilia, history of heart bypass surgery, hypertension, high body temperature rise, etc.
The therapeutic effect related marker can be marked according to the therapeutic effect related to the rule and the value of the specific element thereof, and comprises the following steps: the effectiveness of disease prevention and prevention, the cure and cure rate of diseases, index improvement and improvement, aging delay, pain reduction, body function and shape change and the like.
The person-related tags may be tagged according to the persons involved in the rule, including: doctors, pharmacists, nurses, dieticians, testing/testing technicians, administrators, medical insurance auditors, consumers, caregivers, and the like.
The consumer usage related indicia may be marked according to the consumer usage conditions involved by the rules, including: usage rule consumer number, usage rule consumer rating, consumer data analysis, expert opinion, and the like.
When the relevant rules are marked according to the contents of the diet relevant rationality rules in the database, various marks of the rule contents can be graded or scored according to the requirements of different consumers, so that a user can conveniently select the diet relevant rationality rules suitable for the served consumers. Such as: the contraindication mark in the analysis item related marks is set as a first level, and the level of the contraindication related rule is higher, so that the influence of diet correlation on the safety of consumers is highlighted when the diet correlation is analyzed by using the intelligent health management system.
The method for managing the diet-related rule further comprises the following steps: the method comprises the steps of setting corresponding grades/scores for part/all marks of each rule/each group of rules according to consumer conditions, and setting relative weights of each mark classification according to actual conditions, so that when a user selects a proper rule, the comprehensive grade/score of the related rule can be calculated according to the grade/score corresponding to each mark of the related rule and the relative weight of each mark classification, and the user can conveniently select the proper rule.
When the level/score is set for the diet-related rule flags in the database, each rule may be flagged, or rule flag groupings may be set based on the relationship between the rules. Such as: when the level is set for the mechanism source related mark, the domestic medical mechanism users can be divided into one group, the national health committee is uniformly set as the first level, and the city health committee of each province is set as the second level.
The specific calculation method of the comprehensive grade/score is as follows:
rule X includes n markers, such as data source related markers, institution source related markers, disease related markers, and the like.
M＝m1+…+mn
gi(X) a marker m representing a rule XiThe corresponding level/score. T isiIndicates a mark miRelative weight of the label class in which it is located.
G (X) represents the overall level/score of rule X.
The user may set a composite level/score condition for the rules that are desired to be incorporated into the personalized rule base for a particular consumer, and for a rule in the database, if the composite level/score of the rule is higher than the composite level/score condition set by the user, the rule is selected as the rule in the personalized rule base for that consumer population. This facilitates the user to quickly select rules to build the customer personalized rule base.
The user can also set the usage levels of different comprehensive level/score range rules in different service units after selecting the rule range. Specifically, the usage of the rule may be set as follows according to the comprehensive level/score range of the rule: no-enable, force, fixed, recommended, advise, sound, condition sound, prompt, alert, warning, limit, condition pass, inhibit, strictly inhibit, force inhibit, etc. to support the relevant requirements of the system for rule use.
Different intelligent models can be correspondingly generated according to the grade/score set by each mark of each rule and the relative weight of each mark classification, so that the related intelligent models can be used/referenced under the same/similar conditions, and the setting of the intelligent models can be continuously optimized and adjusted in the using process.
In the invention, the diet-related personalized rule base can be independent, can also be a part of the intelligent health management system/diet management system integral rule base, and can also be a part of the intelligent health management system/diet management system knowledge base. The intelligent health management system/diet management system may be a stand-alone system or may be a part of a medical system, a pharmacy system, or a medical insurance system.
The method for managing the diet-related rule further comprises the following steps: the user can set different business subunit personalized rule systems according to different requirements of consumer groups served by each subunit business on the basis of the unified rule base, and each subunit business is adjusted on the basis of the unified rule base according to the business requirements of the subunit business, including adjustment of rule selection and adjustment of rule application level, so as to support the related requirements of each subunit business on the rules.
The generation of the personalized food related compliance rule base can be completed by the user himself, can be completed by a third party assisting the user, and can also be generated by a rule selection scheme which is consistent with other users and is used by the user.
In the present invention, different sub-service units can be set according to different uses of users, such as: auditing, recommending, instructing, medical insurance settlement, E-commerce shopping and the like. Different sub-service units can select different rules according to the needs of the sub-service units, and configure different personalized rule bases.
The sub-business units can be divided and defined according to the actual conditions of the consumers, the dimensions of the areas, the native places, the sex, the age, the nationality, the economic level, the medical history, the family medical history, the genetic related information, the weight, the fertility condition, the development condition and the like and the different levels of the dimensions, different consumers are divided into different sub-business units according to a certain classification method, and users can conveniently and intensively provide services for similar consumers.
For example: when the hospital provides diet-related management for patients, the hospital can use the personalized rule base of the sub-business units of each department on the basis of the unified rule base according to the nutrition requirement conditions of different departments and different patients. The unified rule base of the hospital and the individualized rule base of the sub-business units selected and adjusted by each department and ward form a complete related rule system of the intelligent health management system/diet management system.
For another example: the consumers can be divided into different groups according to the nationality, and a part of common diet rules are selected according to the nationality correlation of the consumers.
The management method of the intelligent health management system rule base further comprises the step that a user optimizes the diet-related personalized rule base according to the requirements of the served consumer groups, wherein the optimization of the personalized rule base is realized by adjusting and adding rule marks or modifying selection conditions of rules of the personalized rule base or modifying related rules.
The management method of the intelligent health management system rule base further comprises the following steps: and comparing the diet related data of the consumer population served by the user/the consumer population of the user sub-business unit with the diet related rules in the database, and analyzing the rules related to the diet related data of the consumers, the rule source distribution and the specific content.
By analyzing the diet related rules, the rule source distribution and the specific content in the database related to the actual diet related data of the consumers, on one hand, the method can further help the users to master the actual condition of the diets of the consumers, and better select and update the diet related rationality rules in the database through the marks of different dimensions of the sources and the content to generate a personalized rule base/system suitable for the requirements of the consumers. On the other hand, the defects in the diet correlation of the user can be analyzed and improved measures can be made through the comparison of the actually used rules of the user with the relevant standards or health management organizations with higher speciality. And when the doctor uses diet correlation or audits and reviews, medical staff are prompted to use the diet correlation rationality rule which is accorded with the diet correlation and the related marks of the source and the content of the diet correlation, so that the rule can be checked, and a user can judge and analyze diet correlation rational compliance better.
The various data acquired by the method for managing a diet-related rule according to the present invention may be all data, or may be data for setting some conditions as needed, for example: data over a certain time period, data of the patient at a certain hospital/department/dietician, etc.
The management method of the related diet rules further comprises a related diet multidimensional element attribute dictionary which is used for processing matching/comparison of data with different sources, different data structures, different descriptions and different data standards with related information and rules in an intelligent health management system rule base.
The diet-related multi-dimensional element attribute dictionary comprises a standard dictionary, a synonym corresponding dictionary and a fuzzy matching dictionary of diet-related element attributes, and the matching/comparison of data with different sources, different data structures, different descriptions and different data standards with the related data and rules of the intelligent health management system rule base is realized by comparing original data with the synonym corresponding dictionary, or firstly converting the original data into a format corresponding to the standard dictionary and then comparing the original data, or carrying out fuzzy matching comparison on the original data, or mixing the methods.
The diet-related multidimensional element attribute dictionary can be established independently or can be included in an intelligent health management system rule base.
The real diet related information is converted through the diet related multidimensional element attribute dictionary, for example, prescription information is as follows: male, age 65, diagnosis: primary hypercholesterolemia, creatinine clearance: 25 ml/min; converting the creatinine clearance rate of 25 ml/min of a consumer into severe renal insufficiency through a diet-related multidimensional element attribute dictionary, and finding a corresponding contraindication related rule in a diet habit rule base: controlling the salt intake.
In the present invention, the marking of rules can be established automatically by big data analysis/artificial intelligence techniques, or manually. By means of big data analysis/artificial intelligence technology, the content of the rule and the key words contained in the source of the rule are automatically searched, compared and judged with the existing mark, and if the content of the rule and the key words are in accordance with the existing mark, the key words are automatically established as the mark. The big data analysis/artificial intelligence technique may include: keyword retrieval, speech recognition, semantic recognition, OCR recognition, gesture recognition, source recognition, reference data analysis, translation of different languages, virtual reality techniques, augmented reality techniques, and the like.
In the invention, the establishment of the personalized rule base of the specific consumer group can be automatically recommended by an artificial intelligence technology according to the analysis of actual business/historical business data and the requirement of a user on the business; or the personalized rule base of similar consumer groups can be used for reference and established after the user confirms. Finding out the most suitable rule of the consumer by analyzing the actual business/historical business data of the consumer and the requirement analysis of the consumer on diet; the personalized rule base suitable for the consumers is generated by comparing the attributes of the consumers such as regions, nationalities, health conditions and the like with the personalized rule base of similar consumers and adjusting the selection of rules.
A method for managing rules of an intelligent medical diet-related system as described above, the method further comprising: according to the requirements of different users/consumers, a display method of the rules and the marks can be set, so that the users/consumers can view related marks of the diet related rules used in the intelligent health management system/diet management system or view rules corresponding to the related marks.
A second embodiment of the present invention is seen in figure 2. Fig. 2 is a system block diagram of a diet-related rule management system according to a second embodiment of the present invention. A management system of a diet-related rule including a diet-related rationality rule according to the present invention includes:
a rule marking unit 11, configured to mark each diet-related relevant rule in the database according to the source of the rule and the content of the rule;
a rule selecting unit 12, configured to select an appropriate rule according to the mark by the user according to the service requirement of the user;
and the rule base generation unit 13 is used for generating a diet-related personalized rule base meeting the requirements of the consumers and applying the personalized rule base to the intelligent health management system/diet management system of the consumers.
In this embodiment, the intelligent health management system includes a diet-related rule base.
The management system of the diet-related rule and the management method of the diet-related rule of the present invention have technical features corresponding to each other, and reference may be made to the description of the foregoing methods, which are not repeated herein.
A third embodiment of the present invention is seen in fig. 3. Fig. 3 is a hardware block diagram of a diet-related rule management device according to a third embodiment of the present invention. A management apparatus of a diet-related rule including a diet-related rationality rule of the present invention includes:
a rule marking module 21 for marking each diet-related relevant rule in the database according to the source of the rule and the content of the rule;
a rule selection module 22 for the user to select an appropriate rule according to the label based on the consumer's requirements;
and the rule base generation module 23 is used for generating a diet-related personalized rule base meeting the requirements of the consumers and applying the personalized rule base to the intelligent health management system of the consumers.
In this embodiment, the intelligent health management system includes a diet-related rule base.
The management device of the diet-related rule and the management method of the diet-related rule of the present invention have technical features in one-to-one correspondence, and reference may be made to the description of the foregoing method, which is not repeated herein.
In summary, according to the management method, system and device for the diet related rules, each diet related rule in the database is marked according to the source and content of the rule, and the user selects an appropriate rule according to the mark according to the consumer demand to generate a diet related personalized rule base meeting the consumer demand, so as to be applied to the intelligent health management system of the consumer. By the method, the system and the equipment for managing the diet-related rules, a user can select a rule set meeting the requirements of different consumers as a diet-related personalized rule base in an intelligent health management system based on the current situations of different business units and can adjust the rules in real time, so that an information rule management system is quickly established aiming at diet-related reasonability and compliance management and control requirements, and the aims of improving the diet health safety of the consumers, improving the life quality of the consumers, reducing unreasonable medical expenses and reasonably distributing medical resources are fulfilled.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (11)
1. A method of managing diet-related rules, the diet-related rules including diet-related rationality rules, the method comprising:
tagging each/each group of diet-related rules in the database according to the source of the diet-related rules and the content of the rules;
selecting proper rules according to the marks according to the actual conditions of the consumers to generate a diet-related personalized rule base meeting the requirements of the consumers;
the diet-related personalized rule base is applied to the intelligent health management system/diet management system of the consumer.
2. A method of managing dietary-related rules according to claim 1, wherein: the source mark of the rule comprises at least one of a geographic source related mark, an organization source related mark, a material source category related mark, an author source related mark, an evidence level related mark, an administrative certification/recommendation level related mark and a time/version related mark.
3. A method of managing dietary-related rules according to claim 1, wherein: the content indicia of the rules include at least one of diet related indicia, analysis item related indicia, diet efficacy related indicia, population related indicia, disease related indicia, treatment effect related indicia, personnel related indicia, consumer usage related indicia.
4. A method for managing dietary related rules according to any one of claims 1-3, further comprising: the method comprises the steps of setting corresponding grades/scores for part/all marks of each rule/each group of rules according to consumer conditions, and setting relative weights of each mark classification according to actual conditions, so that when a user selects a proper rule, the comprehensive grade/score of the related rule can be calculated according to the grade/score corresponding to each mark of the related rule and the relative weight of each mark classification, and the user can conveniently select the proper rule.
5. A method for managing diet-related rules according to any one of claims 1-4, characterized in that said method further comprises: the user can set up individualized rule systems of different business subunits according to the business requirements of the subunits on the basis of the unified rule base, and each subunit can adjust on the basis of the unified rule base according to the business requirements of the subunit, including the adjustment of the selection of the rules and the adjustment of the rule application level, so as to support the relevant requirements of each subunit on the rules.
6. A method of managing diet-related rules according to any one of claims 1-5, characterized in that: the method also comprises the step that the user optimizes the personalized rule base according to the requirement of the consumer, wherein the optimization of the personalized rule base is realized by adjusting and adding the rule marks, or modifying the selection conditions of the rules of the personalized rule base, or modifying the related rules.
7. A method for managing diet-related rules according to any one of claims 1-6, said method further comprising: and comparing the diet related data of the consumers with rules in the diet related rules in the database, and analyzing the rules related to the diets of the consumers and the source distribution and the specific content of the rules.
8. A method for managing diet-related rules according to any one of claims 1-7, characterized in that said method further comprises: the use of rules may be ranked according to the needs of different consumers, and may include: the system comprises at least one level of non-enabling, mandatory, fixed, recommended, suggested, fair, conditional fair, prompt, alert, warning, limit, conditional pass, forbidden, strict forbidden, mandatory forbidden, etc., to support the user's relevant application requirements for different rules.
9. A method for managing diet-related rules according to any one of claims 1-8, characterized in that said method further comprises: according to the requirements of different users/consumers, the display method of the rules and the marks can be set, so that the users/consumers can view the related marks of the diet related rules used in the intelligent medical system or view the rules corresponding to the related marks.
10. A system for managing diet-related rules, the diet-related rules including a diet-related rationality rule, the system comprising:
the rule marking unit is used for marking each rule/each group of rules related to diet in the database according to the source of the rules and the content of the rules;
a rule selection unit for selecting an appropriate rule according to the label according to the consumer's demand;
and the rule base generation unit is used for generating a diet related personalized rule base meeting the requirements of the consumers according to the selected rules and applying the diet related personalized rule base to the intelligent medical system of the consumers.
11. A management device of diet-related rules including diet-related rationality rules, characterized in that the management device comprises:
a rule marking module for marking each/every group of diet related rules in the database according to the source of the rules and the content of the rules;
the rule selection module is used for selecting proper rules according to the requirements of the consumers and the marks;
and the rule base generation module is used for generating a diet-related personalized rule base meeting the requirements of the consumers according to the selected rules and applying the personalized rule base to the intelligent medical system of the consumers.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107705834A (en) * | 2017-10-10 | 2018-02-16 | 中山大学 | A kind of dietary recommendations continued system based on Recognition with Recurrent Neural Network |
| CN108461124A (en) * | 2018-03-27 | 2018-08-28 | 周梦杰 | Nutrition Management method based on personalized precision and diet guide system |
| CN109509117A (en) * | 2018-09-30 | 2019-03-22 | 口碑(上海)信息技术有限公司 | A kind of vegetable recommended method, apparatus and system |
| CN109559798A (en) * | 2018-11-30 | 2019-04-02 | 北京远大前程数据科技有限公司 | A kind of healthy diet big data management system |
| CN110853723A (en) * | 2019-11-24 | 2020-02-28 | 曹庆恒 | Intelligent medicine guidance method, system and equipment |
| CN110867237A (en) * | 2019-11-15 | 2020-03-06 | 曹庆恒 | Method, system and equipment for managing rule base of reasonable and compliant medication system |
-
2020
- 2020-06-04 CN CN202010497986.3A patent/CN111627525A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107705834A (en) * | 2017-10-10 | 2018-02-16 | 中山大学 | A kind of dietary recommendations continued system based on Recognition with Recurrent Neural Network |
| CN108461124A (en) * | 2018-03-27 | 2018-08-28 | 周梦杰 | Nutrition Management method based on personalized precision and diet guide system |
| CN109509117A (en) * | 2018-09-30 | 2019-03-22 | 口碑(上海)信息技术有限公司 | A kind of vegetable recommended method, apparatus and system |
| CN109559798A (en) * | 2018-11-30 | 2019-04-02 | 北京远大前程数据科技有限公司 | A kind of healthy diet big data management system |
| CN110867237A (en) * | 2019-11-15 | 2020-03-06 | 曹庆恒 | Method, system and equipment for managing rule base of reasonable and compliant medication system |
| CN110853723A (en) * | 2019-11-24 | 2020-02-28 | 曹庆恒 | Intelligent medicine guidance method, system and equipment |
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