CN108122611A - A kind of information recommendation method, device and storage medium, program product - Google Patents
A kind of information recommendation method, device and storage medium, program product Download PDFInfo
- Publication number
- CN108122611A CN108122611A CN201711407945.5A CN201711407945A CN108122611A CN 108122611 A CN108122611 A CN 108122611A CN 201711407945 A CN201711407945 A CN 201711407945A CN 108122611 A CN108122611 A CN 108122611A
- Authority
- CN
- China
- Prior art keywords
- information
- symptom
- disease
- symptom information
- user
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The embodiment of the present application discloses a kind of information recommendation method, and for recommending corresponding medical treatment resource information for user, this method includes：Ontology knowledge base is established, ontology knowledge base includes the correspondence of symptom information and disease information；Symptom information input by user is obtained, using symptom information input by user as specified symptom information；According to ontology knowledge base, the degree of correlation of calculating disease information and specified symptom information；Determine that the degree of correlation meets the disease information of preset condition as target information from disease information, target information is used to recommend corresponding medical treatment resource information to user.
Description
Technical field
This application involves Internet technical fields, and in particular to a kind of information recommendation method, device and storage medium, journey
Sequence product.
Background technology
Reservation based on the internet or mobile Internet services such as register, pay the fees are provided for patient towards specified doctor
Treatment services in the institute of institute reduce the time of queuing of patients's waiting, realize disclosure, the justiceization of medical resource.But patient
Which section office needed when needing medical, it is also necessary to self decision-making of patient or the artificial hospital guide service for seeking hospital.
Therefore, the existing reservation based on the internet or mobile Internet service of registering is truly real not yet
Now recommend suitable medical resource for patient, it is more likely that patient is caused to delay best occasion for the treatment, in some instances it may even be possible to be examined by mistake
It treats.
The content of the invention
In view of this, the embodiment of the present application provides a kind of information recommendation method, device and storage medium, program product, with
The technical issues of solving that effectively medical resource can not be recommended for user in the prior art.
To solve the above problems, technical solution provided by the embodiments of the present application is as follows：
A kind of information recommendation method, establishes ontology knowledge base, and the ontology knowledge base includes symptom information and disease information
Correspondence, the described method includes：
Symptom information input by user is obtained, using the symptom information input by user as specified symptom information；
According to the ontology knowledge base, the degree of correlation of the disease information and the specified symptom information is calculated；
Determine that the degree of correlation meets the disease information of preset condition as target information, institute from the disease information
Target information is stated for recommending corresponding medical treatment resource information to the user.
Optionally, the method further includes：
Related symptoms information is calculated according to the symptom information input by user, recommends the related disease to the user
Shape information.
Optionally, it is described that related symptoms information is calculated according to the symptom information input by user, including：
Whole diseases that there is correspondence with the symptom information input by user are searched from the ontology knowledge base
The set of information is as the first disease information set；
Searched from the ontology knowledge base has correspondence with disease information in the first disease information set
The set of symptom information is as the first symptom information set；
According to the weight of each symptom information in the first symptom information set in the first symptom information set
Each symptom information carries out descending sort and obtains ranking results, and related symptoms information is determined according to the ranking results, described each
The quantity of the weight of a symptom information disease information corresponding with the symptom information is inversely proportional.
Optionally, the method further includes：
The symptom information that user selects from the related symptoms information is obtained, by the symptom information input by user
And the symptom information that the user selects from the related symptoms information is as specified symptom information；
According to the ontology knowledge base, the degree of correlation of the disease information and the specified symptom information is calculated；
Determine that the degree of correlation meets the target information of preset condition from the disease information, the target information is used
In recommending corresponding medical treatment resource information to the user.
Optionally, it is described according to the ontology knowledge base, calculate the phase of the disease information and the specified symptom information
Guan Du, including：
According to the weight of each symptom information in the ontology knowledge base and the ontology knowledge base, the disease is calculated
Sick information and the degree of correlation of the specified symptom information, the weight disease corresponding with the symptom information of each symptom information
The quantity of sick information is inversely proportional.
Optionally, the weight according to each symptom information in the ontology knowledge base and the ontology knowledge base,
The degree of correlation of the disease information and the specified symptom information is calculated, including：
It is searched from the ontology knowledge base and whole disease informations of the specified symptom information with correspondence
Set is as the second disease information set；
Searched from the ontology knowledge base has corresponding close with any disease information in the second disease information set
The set of the symptom information of system is as the second symptom information set；
The second symptom information set and the specified symptom information are taken into intersection, obtain the 3rd symptom information set；
The sum of weight of each symptom information in the 3rd symptom information set is calculated, as first as a result, calculating institute
The sum of weight of each symptom information in the second symptom information set is stated, as second as a result, the power of each symptom information
The quantity of weight disease information corresponding with the symptom information is inversely proportional；
The ratio of first result and second result is calculated, is believed as the disease information and the specified symptom
The degree of correlation of breath.
Optionally, the correspondence of the symptom information and disease information is stored in ontology knowledge in the form of graph model
In storehouse.
A kind of information recommending apparatus, described device include：
Unit is established, for establishing ontology knowledge base, the ontology knowledge base includes pair of symptom information and disease information
It should be related to；
First acquisition unit, for obtaining symptom information input by user, using the symptom information input by user as
Specify symptom information；
First computing unit, for according to the ontology knowledge base, calculating the disease information and believing with the specified symptom
The degree of correlation of breath；
First determination unit, for determining that the degree of correlation meets the disease letter of preset condition from the disease information
As target information, the target information is used to recommend corresponding medical treatment resource information to the user breath.
Optionally, described device further includes：
Second computing unit, for calculating related symptoms information according to the symptom information input by user；
Recommendation unit, for recommending the related symptoms information to the user.
Optionally, second computing unit, including：
First searches subelement, has for being searched from the ontology knowledge base with the symptom information input by user
There is the set of whole disease informations of correspondence as the first disease information set；
Second searches subelement, for being searched from the ontology knowledge base and disease in the first disease information set
Sick information has the set of the symptom information of correspondence as the first symptom information set；
Sort subelement, for according to the weight of each symptom information in the first symptom information set to described the
Each symptom information carries out descending sort and obtains ranking results in one symptom information set, and phase is determined according to the ranking results
Symptom information is closed, the quantity of the weight disease information corresponding with the symptom information of each symptom information is inversely proportional.
Optionally, described device further includes：
Second acquisition unit, for obtaining the symptom information that user selects from the related symptoms information, by the use
The symptom information that the symptom information of family input and the user select from the related symptoms information is believed as specified symptom
Breath；
3rd computing unit, for according to the ontology knowledge base, calculating the disease information and believing with the specified symptom
The degree of correlation of breath；
Second determination unit, for determining that the degree of correlation meets the target letter of preset condition from the disease information
Breath, the target information are used to recommend corresponding medical treatment resource information to the user.
Optionally, first computing unit is specifically used for according to the ontology knowledge base and the ontology knowledge base
In each symptom information weight, calculate the degree of correlation of the disease information and the specified symptom information, each symptom
The quantity of the weight of information disease information corresponding with the symptom information is inversely proportional.
Optionally, first computing unit, including：
3rd searches subelement, for being searched from the ontology knowledge base with the specified symptom information with corresponding
The set of whole disease informations of relation is as the second disease information set；
4th searches subelement, for being searched from the ontology knowledge base with appointing in the second disease information set
One disease information has the set of the symptom information of correspondence as the second symptom information set；
Subelement is obtained, for the second symptom information set and the specified symptom information to be taken intersection, obtains the
Three symptom information set；
First computation subunit, for calculating the sum of weight of each symptom information in the 3rd symptom information set,
As first as a result, calculating the sum of weight of each symptom information in the second symptom information set, as second as a result,
The quantity of the weight disease information corresponding with the symptom information of each symptom information is inversely proportional；
Second computation subunit for calculating the ratio of first result and second result, is believed as the disease
The degree of correlation of breath and the specified symptom information.
Optionally, the correspondence of the symptom information and disease information is stored in ontology knowledge in the form of graph model
In storehouse.
A kind of computer readable storage medium is stored with instruction in the computer readable storage medium storing program for executing, works as described instruction
When running on the terminal device so that the terminal device performs above-mentioned information recommendation method.
A kind of computer program product, when the computer program product is run on the terminal device so that the terminal
Equipment performs above-mentioned information recommendation method.
It can be seen that the embodiment of the present application has the advantages that：
The embodiment of the present application pre-establishes the ontology knowledge base of the correspondence including symptom information and disease information,
After obtaining symptom information input by user, the disease that each disease information is inputted with the user can be calculated according to ontology knowledge base
The degree of correlation of shape information can determine target information according to the degree of correlation from each disease information, which can be with
It prompts symptom information input by user possible corresponding disease information, can further be recommended according to the target information to user
Medical treatment resource information, such as to user's recommendation which hospital department should be gone to go to a doctor, recommend medical treatment money so as to fulfill for user
Source.
Description of the drawings
Fig. 1 is a kind of Application Scenarios-Example figure of information recommendation method provided by the embodiments of the present application；
Fig. 2 is a kind of flow chart of information recommendation method provided by the embodiments of the present application；
Fig. 3 is the exemplary plot of ontology knowledge base provided by the embodiments of the present application；
Fig. 4 is the displaying examples of interfaces figure that target information is determined on terminal device provided by the embodiments of the present application；
Fig. 5 is a kind of flow chart of method for calculating the degree of correlation provided by the embodiments of the present application；
Fig. 6 a are the weight disease information corresponding with the symptom information of each symptom information provided by the embodiments of the present application
Quantitative relation exemplary plot；
Fig. 6 b are the weight exemplary plot of each symptom information provided by the embodiments of the present application；
Fig. 7 is a kind of flow chart for calculating related symptoms information approach provided by the embodiments of the present application；
Fig. 8 is the displaying examples of interfaces figure that target information is determined on terminal device provided by the embodiments of the present application；
Fig. 9 is a kind of structure diagram of information recommending apparatus provided by the embodiments of the present application.
Specific embodiment
It is below in conjunction with the accompanying drawings and specific real to enable the above-mentioned purpose of the application, feature and advantage more obvious understandable
Mode is applied to be described in further detail the embodiment of the present application.
It is usually that hospital is directly provided in service is registered in the existing reservation based on internet or mobile Internet
And the medical treatment resource informations such as section office are selected for user, which kind of medical treatment resource information user selects generally require user self to determine
Plan can not be that user recommends suitable medical resource.Therefore, the existing reservation based on internet or mobile Internet is hung
Number service is truly embodied as user and recommends suitable medical resource not yet, so as to which user is caused to delay most preferably
Therapic opportunity, in some instances it may even be possible to by wrong medical information.
For this purpose, the embodiment of the present application provides a kind of information recommendation method, device and storage medium, program product, to solve
The technical issues of effectively can not recommending medical resource for user in the prior art, is realized definite corresponding with specified symptom information
Disease information recommends medical treatment resource information corresponding with the disease information so that user can find suitable medical treatment to user
Resource is gone to a doctor.
The method that the embodiment of the present application is provided can be applied on the terminal device with data-handling capacity, such as
It can be realized, can also be realized by computer by the APP (application program, Application) on terminal device；Also
Server can be utilized to complete the method described in the present embodiment, and each result for being obtained server by terminal device is shown
To user；Server can also be utilized to interact the method for realizing the embodiment of the present application, the embodiment of the present application with terminal device
This is not limited.
Referring to Fig. 1, Fig. 1 shows an application scenarios of the embodiment of the present application.In the application scenarios, server 103
In be pre-established with ontology knowledge base, ontology knowledge base includes the correspondence of symptom information and disease information.User 101 can
To input symptom information in the APP on terminal device 102, server 103 can obtain symptom information input by user, will
Symptom information input by user, according to ontology knowledge base, calculates the disease information and the finger as specified symptom information
Determine the degree of correlation of symptom information, while target information can be determined from each disease information according to the degree of correlation.Terminal is set
Standby 102, which can obtain the target information, is shown, which can prompt possible corresponding disease input by user
Information, so that terminal device 102 further can recommend medical treatment resource information according to the target information to user.Wherein, terminal
Equipment 102 shows that the displaying interface of target information can be as shown in Fig. 1 104 to user.
It should be noted that above application scene is for only for ease of the understanding present invention and shows, embodiment party of the invention
Formula is unrestricted in this regard.On the contrary, embodiments of the present invention can be applied to applicable any scene.
Below in conjunction with the accompanying drawings, the various non-limiting embodiments that the present invention will be described in detail.
The embodiment of the present application provides a kind of information recommendation method, shown in Figure 2, shows in the embodiment of the present application and carries
A kind of flow chart of the information recommendation method supplied, may comprise steps of：
Step 201：Symptom information input by user is obtained, using the symptom information input by user as specified symptom
Information.
Wherein, user can input at least one symptom information, the symptom letter of the user's input according to the situation of itself
Breath can be used as and specify symptom information, i.e., can include at least one specified symptom information in the present embodiment.
The realization of the method provided by the present embodiment can using ontology knowledge base as foundation, performing this reality
Before applying the method that example is provided, ontology knowledge base can be pre-established, the ontology knowledge base includes symptom information and believes with disease
The correspondence of breath, to be determined to specify the corresponding disease information of symptom information according to ontology knowledge base.
It should be noted that disease information, symptom information can be obtained through a variety of ways in embodiments of the present invention,
And the relation data of disease information and symptom information, in this way, can be according to the disease information, the symptom information and the pass
For coefficient according to the ontology knowledge base for establishing disease information and symptom information, the form of expression of the ontology knowledge base can be such as Fig. 3 institutes
Show.
The ontology knowledge base can describe the correspondence between disease information and symptom information, for example, shown in Fig. 3
Symptom information " becoming thin ", " more drinks ", " diuresis " and " more foods " have correspondence with disease information " 1 patients with type Ⅰ DM " respectively, adopt
It is described with resource description framework (Resource Description Framework, abbreviation RDF), each correspondence exists
It can be represented in Fig. 3 with the line with arrow.
The ontology knowledge base can also describe the classification relation of disease information, symptom information, for example, the disease shown in Fig. 3
Sick information " type 1 diabetes ", " insulin-dependent diabetes mellitus " etc. belong to diabetes in classification, are described using RDF；
Disease information " diabetes " belongs to endocrine and metabolism systemic disease in classification, using RDF vocabulary definitions (RDF Schema,
Abbreviation RDFS) language description, each classification relation can represent in figure 3 with the line with arrow.
The ontology knowledge base can also describe the synonymy between disease information or the synonymy between symptom information, example
Such as, the disease information shown in Fig. 3 " type 1 diabetes " and disease information " insulin-dependent diabetes mellitus " are synonymies, disease
Shape information " headache ", " head pain " and " headache " are synonymies, using Web Ontology Languages (Web Ontology
Language, abbreviation OWL) it is described, each synonymy can be represented in figure 3 with the line with arrow.
It is understood that for the ease of searching the correspondence of symptom information and disease information in ontology knowledge base,
So as to quickly determine corresponding disease information according to symptom information input by user, search efficiency is improved, in this implementation
In some possible realization methods of example, the correspondence of symptom information and disease information is stored in body in the form of graph model
In knowledge base.
Step 202：According to the ontology knowledge base, it is related to the specified symptom information to calculate the disease information
Degree.
Since ontology knowledge base includes the correspondence of symptom information and disease information, it can be known according to body
Know symptom information in storehouse and determine disease information corresponding with specifying symptom information with the correspondence of disease information.Ordinary circumstance
Under, the disease information corresponding with specified symptom information determined may include multiple, various disease information and the specified symptom
The degree of correlation of information may be different so that according to the appropriate level of various disease information medical treatment resource information recommended to the user
Difference, for example, the degree of correlation of disease information and specified symptom information is bigger, then, it is recommended to the user according to the disease information
Medical treatment resource information corresponding with the disease information is more suitable.For this purpose, can calculate the disease information specifies symptom information with this
The degree of correlation, so as to according to the degree of correlation determine for user recommend medical treatment resource information used in disease information.
It calculates the disease information and the realization method of the degree of correlation of the specified symptom information will carry out in following embodiment
It is discussed in detail.,
Step 203：Determine that the degree of correlation meets the disease information of preset condition as target from the disease information
Information, the target information are used to recommend corresponding medical treatment resource information to the user.
After the degree of correlation is calculated, can correspondence be had from specified symptom information according to the size of the degree of correlation
All disease informations in determine that the degree of correlation meets the disease information of preset condition as target information, terminal device may be used also
The target information to be shown to user, so that subsequently corresponding medical resource can be recommended to user according to the target information
Information.
Determine that the degree of correlation meets one of the disease information of preset condition as target information from the disease information
Planting realization method can be：After the degree of correlation is calculated, judge whether the degree of correlation reaches first threshold, if the correlation
Degree reaches first threshold, then using the corresponding disease information of the degree of correlation as target information.Wherein, the first threshold can be with
Rule of thumb it is configured.
For example, the degree of correlation for calculating disease information A and specified symptom information in step 202 is 33%, disease information
The degree of correlation of B and specified symptom information is 26%, and disease information C and the degree of correlation of specified symptom information are 20%, if the first threshold
It is worth for 25%.By the judgement to each degree of correlation, 33% is more than first threshold 25%, and 26% is more than first threshold 25%,
20% is less than first threshold 25%, hence, it can be determined that disease information A and disease information B can be used as target information.
Determine that the degree of correlation meets the disease information of preset condition as the another of target information from the disease information
A kind of realization method can be：After the degree of correlation is calculated, each disease information is carried out from big to small according to the degree of correlation
Sequence is lined up, obtains the sequence number of each disease information in the sequence, the sequence number from small to large, is determined from the disease information
Go out disease information of the sequence number less than second threshold as target information.Wherein, the second threshold can rule of thumb be carried out
It sets.
Continue using the degree of correlation of foregoing obtained disease information A and specified symptom information as 33%, disease information B is with referring to
The degree of correlation of symptom information is determined for 26%, and the degree of correlation of disease information C and specified symptom information is exemplified by 20%, due to 33%
It is more than 20% more than 26%, 26%, then above-mentioned disease information can be lined up sequence：Disease information A, disease information B, disease
Information C, then the serial number 1 of disease information A, disease information B serial numbers 2, disease information C serial numbers 3 in the sequence, if
Two threshold values are 3, then disease information A and disease information B of the sequence number less than 3 can be determined as target information.
The present embodiment provided on the terminal device determine target information displaying interface can with as shown in figure 4, its
In, 401 represent symptom information input by user as " indigestion ", and 403 represent possible target information, it can in addition contain logical
It crosses dotted line frame in 403 and shows the corresponding degree of correlation of each target information.
In addition, it is necessary to explanation, the target information obtained in the embodiment of the present application do not represent the healthy shape of user
Condition, the target information are used to recommend corresponding medical treatment resource information to user, with guide user to corresponding medical institutions just
It examines.
The embodiment of the present application pre-establishes the ontology knowledge base of the correspondence including symptom information and disease information,
After obtaining symptom information input by user, the disease that each disease information is inputted with the user can be calculated according to ontology knowledge base
The degree of correlation of shape information can determine target information according to the degree of correlation from each disease information, which can be with
It prompts symptom information input by user possible corresponding disease information, can further be recommended according to the target information to user
Medical treatment resource information, such as to user's recommendation which hospital department should be gone to go to a doctor, recommend medical treatment money so as to fulfill for user
Source.
For the degree of correlation for calculating disease information and specified symptom information, in the related art, mainly according to each disease
Sick information is capable of the quantity of matched specified symptom information, weighs disease information and the degree of correlation of specified symptom information, so as to
Determine disease information corresponding with specified symptom information.For example, user provides 5 specified symptom informations, it is assumed that some disease
Sick information D1Have matched 4 specified symptom informations therein, and another disease information D2Have matched 3 specified symptoms therein
Information, it is seen then that disease information D1The quantity of matched specified symptom information is more than disease information D2Matched specified symptom information
Quantity, then then think disease information D1It is higher than disease information D with the degree of correlation of specified symptom information2Believe with specified symptom
The degree of correlation of breath, accordingly, it is possible to can determine whether out that disease information corresponding with this 5 specified symptom informations is D1Likelihood ratio D2
Greatly, then may recommend and disease information D to user1Corresponding medical treatment resource information.
It is each but in the method for the degree of correlation for weighing disease information and specified symptom information provided in correlation technique
It is identical for the importance for determining disease information to specify symptom information, and actual conditions are not so.In some cases
Under, many different disease informations may correspond to identical symptom information, but the symptom information is in the important of various disease information
Property may be different.If disease information has corresponding close with symptom information of high importance in specified symptom information
System, then the disease information is more likely that this specifies symptom information corresponding disease information, according to the disease information to user
The medical treatment resource information of recommendation may be more suitable.
For example, in the above example, disease information D1Matched 4 specified symptom informations may all be to determining disease
The very small symptom information of information importance, and disease information D2Matched 3 specified symptom informations may all be to determining disease
The sick very big symptom information of information importance, in that way it is possible to cause D2Believe with the degree of correlation of specified symptom information higher than disease
Cease D1With the degree of correlation of specified symptom information, disease information D2It is more likely disease information corresponding with specified symptom information,
It should recommend and disease information D to user2Corresponding medical treatment resource information.
It can be seen that correlation technique is capable of the quantity of matched specified symptom information only in accordance with each disease information, to count
Calculating the method for disease information and the degree of correlation of specified symptom information may cause the disease information determined inaccurate, and then lead
Cause medical treatment resource information recommended to the user improper.
For this purpose, a kind of step 202 calculating possible realization method of the degree of correlation can be：According to ontology knowledge base and
The weight of each symptom information in the ontology knowledge base calculates the degree of correlation that the disease information specifies symptom information with this, institute
The quantity for stating the weight disease information corresponding with the symptom information of each symptom information is inversely proportional, the power of each symptom information
Weight can represent importance of the symptom information for definite disease information, and the weight of each symptom information is bigger, represents the disease
Shape information is higher for the importance for determining disease information.
A kind of information recommendation method based on foregoing offer, it is shown in Figure 5, it shows in the embodiment of the present application and provides
A kind of weight according to each symptom information in the ontology knowledge base and the ontology knowledge base, calculate the disease
The flow chart of information and the method for the degree of correlation of the specified symptom information, may comprise steps of：
Step 501：Whole diseases that there is correspondence with the specified symptom information are searched from the ontology knowledge base
The set of sick information is as the second disease information set.
Step 502：It searches from the ontology knowledge base and has with any disease information in the second disease information set
There is the set of the symptom information of correspondence as the second symptom information set.
Step 503：The second symptom information set and the symptom information input by user are taken into intersection, obtain the
Three symptom information set.
Step 504：The sum of weight of each symptom information in the 3rd symptom information set is calculated, as the first knot
Fruit calculates the sum of weight of each symptom information in the second symptom information set, as second as a result, each disease
The quantity of the weight of shape information disease information corresponding with the symptom information is inversely proportional.
Under normal circumstances, a symptom information can correspond to multiple disease informations, if symptom information includes " head
Bitterly ", " headache " be many disease informations all may corresponding symptom information, so being based purely on " headache " to determine
Symptom information may corresponding disease information be relatively difficult, therefore it is in determining the corresponding disease information of symptom information
Importance very little, then the weight of the symptom information can be smaller；If symptom information includes " blood back tears blood ", due to " returning
Courageous and upright tears blood " is only present in a few disease information, then the symptom information can be as the typical case of these disease informations
Symptom information, the importance for determining the corresponding disease information of symptom information is larger, then the weight of the symptom information can be with
It is larger.
Therefore, the quantity of the weight of each symptom information disease information corresponding with the symptom information is related, for example, respectively
The quantity of the weight of a symptom information disease information corresponding with the symptom information is inversely proportional, as shown in Figure 6 a, wherein, horizontal seat
Mark NsRepresent the quantity of disease information corresponding with the symptom information, ordinate WsRepresent the weight with the symptom information.
Wherein, to ensure that the quantity of the weight disease information corresponding with the symptom information of each symptom information is inversely proportional,
The weight of each symptom information can rule of thumb directly set weight for each symptom information, and be stored in ontology knowledge
In storehouse；The weight of each symptom information can also utilize disease information corresponding with the symptom information according to ontology knowledge base
Quantity be calculated.
As a kind of example, the power of the symptom information is calculated using the quantity of disease information corresponding with the symptom information
The formula of weight can be as follows：
Wherein, s represents a symptom information, WsRepresent the weight of the symptom information, N represents that ontology knowledge base includes
Disease information sum, NsRepresent the quantity of the disease information comprising symptom information s.
The weight of each symptom information calculated can be in the form of a list stored on server or terminal device, such as
Shown in Fig. 6 b, wherein, the numerical value in dotted line frame can represent the weight of each symptom information, and it can be modified.When
So, the weight of each symptom information can also be calculated in real time during information recommendation.
Step 505：The ratio of first result and second result is calculated, as the disease information and the finger
Determine the degree of correlation of symptom information.
For example, all sympotomatic sets input by user are combined into S1={ s1, s2... sv..., sm, with specifying in ontology knowledge base
Symptom information has the set D of whole disease informations of correspondence1={ d1, d2... dk..., dl, using the set as
Two disease information set.For set D1={ d1, d2... dk..., dlIn a certain disease information dk, from ontology knowledge base
It searches and disease information dkAll sympotomatic sets be combined into Sdk, as the second symptom information set, by the second symptom information collection
Close SdkIn belong to specified symptom information symptom information form set as the 3rd symptom information set S'dk.Calculate S'dkIn
The sum of weight of each symptom information, as first as a result, and calculating SdkIn each symptom information the sum of weight, as
Two results.Finally, by calculating the ratio of the first result and the second result, disease information d is obtainedkWith specified symptom information
The degree of correlation.
Calculate disease information dkWith the degree of correlation r of specified symptom informationdkFormula can be as follows：
Wherein, rdkRepresent disease information dkWith the degree of correlation of specified symptom information, s ∈ SdkExpression belongs to the second symptom letter
Cease set SdkIn symptom information, s ∈ S'dkExpression belongs to the 3rd symptom information set S'dkIn symptom information, wsRepresent every
The weight of a symptom information,Represent to calculate each symptom information in the 3rd symptom information set weight it
With,Represent to calculate the sum of weight of each symptom information in the second symptom information set.
The present embodiment is when calculating the degree of correlation of disease information and symptom information, it is contemplated that each symptom information is for this
The importance of disease information, and represent each symptom information for the disease information using the weight of each symptom information
Importance, can the more accurately degree of correlation of disease information and symptom information, so as to accurately determine target information,
Recommend more suitable medical treatment resource information for user.
After target information is determined as specified symptom information using symptom information input by user, in some cases,
Since symptom information input by user may be partial symptoms information or symptom information input by user is not typical case
Symptom information, in order to ensure in the corresponding disease information of definite specify information, specify symptom information it is more comprehensive, more
It can reflect the classical symptom information of disease information, it is corresponding with specified symptom information so as to more accurately determine
Disease information, and then recommend more suitable medical treatment resource information for user.
In the embodiment of the present application, after symptom information input by user is got, can also be inputted according to the user
Symptom information calculate related symptoms information, so as to user show target information when, to user related symptoms is recommended to believe
Breath so that user can make choice from related symptom information, adjusts according to selected related symptoms information and specifies symptom
Information redefines target information, recommends more suitable medical treatment resource information for user.
It is shown in Figure 7, a kind of flow of the calculating related symptoms information approach provided in the embodiment of the present application is provided
Figure, may comprise steps of：
Step 701：Searched from the ontology knowledge base has correspondence with the symptom information input by user
The set of whole disease informations is as the first disease information set.
Step 702：From the ontology knowledge base search with the first disease information set in disease information have pair
The set for the symptom information that should be related to is as the first symptom information set.
Step 703：Weight according to each symptom information in the first symptom information set believes first symptom
Each symptom information carries out descending sort and obtains ranking results in breath set, determines that related symptoms are believed according to the ranking results
Breath, the quantity of the weight disease information corresponding with the symptom information of each symptom information are inversely proportional.
In the present embodiment, by taking symptom information input by user is symptom information s as an example, calculated according to symptom information s
During related symptoms information, first, whole disease informations that there is correspondence with symptom information s are searched from ontology knowledge base
Collection be combined into D2={ d1, d2... dj..., dp, as the first disease information set.Then, for the first disease information set
D2In all disease informations, from ontology knowledge base search with disease information in the first disease information set have it is corresponding pass
The symptom information of system, if for d1The symptom information found is s1、s2, for d2The symptom information found is s1、…s2、
si, for djThe symptom information found is s1..., sq, it is similar, to the corresponding symptom information of each disease information into
Row is searched, and forms the first symptom information set using all symptom informations found, which may be
S2={ s1, s2... si..., sq}.After again, according to the first symptom information set S2={ s1, s2... si..., sqIn each disease
The weight of shape information carries out descending sort to each symptom information in the first symptom information set and obtains ranking results, according to institute
It states ranking results and determines related symptoms information.
It is understood that the present embodiment can be from big to small ranked up according to the weight of each symptom information, obtain
Ranking results be s1, s2... si..., sq, then can using selected and sorted top n symptom information as recommend symptom information,
So that user makes choice, when symptom information of the selected and sorted in top n, there is symptom information s, then skip symptom information s
Continuation is continuously chosen backward, the symptom information until selecting top n.
For example, N can take 6, then by s1, s2... si..., sqSymptom information s of the middle sequence preceding 61、s2、s3、s4、s5With
s6As related symptoms information, user is recommended, so that user is from symptom information s1、s2、s3、s4、s5And s6Middle selection and user
Matched symptom information.
It should be noted that the acquisition modes of the weight for each symptom information that the present embodiment is previously mentioned are in abovementioned steps
It has been carried out introducing in detail in 504, details are not described herein again.
After related symptoms information is obtained, the related symptoms information, the exhibition of the related symptoms information can be shown to user
Show that interface can be as shown in Fig. 4 402.
User can be according to the situation of itself, selection and the matched symptom information of user from the related symptoms information, such as
In Fig. 8 shown in 802, in the related symptoms information that user need to be shown in 402 select symptom information postpartum gastrointestinal symptom and
Yellowing of the skin.Then, the symptom information selected according to user from the related symptoms information, by symptom information input by user
And the symptom information that is selected from the related symptoms information of user is as specified symptom information, perform again step 202 to
Method described in step 203.Target information is finally obtained as shown in Fig. 8 803, and provides each target information and specified disease
The degree of correlation of shape information.To compare it can be found that the present embodiment, utilizes shown in the target information shown in 803 and 403
The symptom information that user selects from related symptom information is to target information and each target information and specified symptom information
The degree of correlation is adjusted, and more accurate target information is shown to user.
Wherein, step 202, the specific implementation of step 203 may refer to previous embodiment, and details are not described herein again.
A kind of method of information recommendation based on foregoing offer, the embodiment of the present application additionally provide a kind of information recommendation
Device, shown in Figure 9, Fig. 9 shows a kind of structure diagram for the device for realizing information recommendation, and described device includes establishing
Unit 901, first acquisition unit 902, the first computing unit 903 and the first determination unit 904：
Described to establish unit 901, for establishing ontology knowledge base, the ontology knowledge base includes symptom information and disease
The correspondence of information；
The first acquisition unit 902, for obtaining symptom information input by user, by the symptom input by user
Information is as specified symptom information；
First computing unit 903, for according to the ontology knowledge base, calculating the disease information and the finger
Determine the degree of correlation of symptom information；
First determination unit 904, for determining that the degree of correlation meets preset condition from the disease information
As target information, the target information is used to recommend corresponding medical treatment resource information to the user disease information.
Optionally, described device further includes：
Second computing unit, for calculating related symptoms information according to the symptom information input by user；
Recommendation unit, for recommending the related symptoms information to the user.
Optionally, second computing unit, including：
First searches subelement, has for being searched from the ontology knowledge base with the symptom information input by user
There is the set of whole disease informations of correspondence as the first disease information set；
Second searches subelement, for being searched from the ontology knowledge base and disease in the first disease information set
Sick information has the set of the symptom information of correspondence as the first symptom information set；
Sort subelement, for according to the weight of each symptom information in the first symptom information set to described the
Each symptom information carries out descending sort and obtains ranking results in one symptom information set, and phase is determined according to the ranking results
Symptom information is closed, the quantity of the weight disease information corresponding with the symptom information of each symptom information is inversely proportional.
Optionally, described device further includes：
Second acquisition unit, for obtaining the symptom information that user selects from the related symptoms information, by the use
The symptom information that the symptom information of family input and the user select from the related symptoms information is believed as specified symptom
Breath；
3rd computing unit, for according to the ontology knowledge base, calculating the disease information and believing with the specified symptom
The degree of correlation of breath；
Second determination unit, for determining that the degree of correlation meets the target letter of preset condition from the disease information
Breath, the target information are used to recommend corresponding medical treatment resource information to the user.
Optionally, first computing unit is specifically used for, according to the ontology knowledge base and the ontology knowledge base
In each symptom information weight, calculate the degree of correlation of the disease information and the specified symptom information, each symptom
The quantity of the weight of information disease information corresponding with the symptom information is inversely proportional.
Optionally, first computing unit, including：
3rd searches subelement, for being searched from the ontology knowledge base with the specified symptom information with corresponding
The set of whole disease informations of relation is as the second disease information set；
4th searches subelement, for being searched from the ontology knowledge base with appointing in the second disease information set
One disease information has the set of the symptom information of correspondence as the second symptom information set；
Subelement is obtained, for the second symptom information set and the specified symptom information to be taken intersection, obtains the
Three symptom information set；
First computation subunit, for calculating the sum of weight of each symptom information in the 3rd symptom information set,
As first as a result, calculating the sum of weight of each symptom information in the second symptom information set, as second as a result,
The quantity of the weight disease information corresponding with the symptom information of each symptom information is inversely proportional；
Second computation subunit for calculating the ratio of first result and second result, is believed as the disease
The degree of correlation of breath and the specified symptom information.
Optionally, the correspondence of the symptom information and disease information is stored in ontology knowledge in the form of graph model
In storehouse.
The embodiment of the present application pre-establishes the ontology knowledge base of the correspondence including symptom information and disease information,
After obtaining symptom information input by user, the disease that each disease information is inputted with the user can be calculated according to ontology knowledge base
The degree of correlation of shape information can determine target information according to the degree of correlation from each disease information, which can be with
It prompts symptom information input by user possible corresponding disease information, can further be recommended according to the target information to user
Medical treatment resource information, such as to user's recommendation which hospital department should be gone to go to a doctor, recommend medical treatment money so as to fulfill for user
Source.
It should be noted that each embodiment is described by the way of progressive in this specification, each embodiment emphasis is said
Bright is all difference from other examples, and just to refer each other for identical similar portion between each embodiment.For reality
For applying system disclosed in example or device, since it is corresponded to the methods disclosed in the examples, so description is fairly simple,
Reference may be made to the description of the method.
It should also be noted that, herein, relational terms such as first and second and the like are used merely to one
Entity or operation with another entity or operate distinguish, without necessarily requiring or implying these entities or operation it
Between there are any actual relationship or orders.Moreover, term " comprising ", "comprising" or its any other variant meaning
Covering non-exclusive inclusion, so that process, method, article or equipment including a series of elements not only include
Those elements, but also including other elements that are not explicitly listed or further include for this process, method, article or
The intrinsic element of person's equipment.In the absence of more restrictions, the element limited by sentence "including a ...", and
It is not precluded in the process including the element, method, article or equipment that also there are other identical elements.
Hardware, processor can be directly used with reference to the step of method or algorithm that the embodiments described herein describes
The combination of the software module or the two of execution is implemented.Software module can be placed in random access memory (RAM), memory, only
Read memory (ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or
In any other form of storage medium well known in technical field.
The foregoing description of the disclosed embodiments enables professional and technical personnel in the field to realize or using the application.
A variety of modifications of these embodiments will be apparent for those skilled in the art, it is defined herein
General Principle can in other embodiments be realized in the case where not departing from spirit herein or scope.Therefore, originally
Application is not intended to be limited to the embodiments shown herein, and is to fit to special with principles disclosed herein and novelty
The consistent most wide scope of point.
Claims (10)
1. a kind of information recommendation method, which is characterized in that establish ontology knowledge base, the ontology knowledge base include symptom information with
The correspondence of disease information, the described method includes：
Symptom information input by user is obtained, using the symptom information input by user as specified symptom information；
According to the ontology knowledge base, the degree of correlation of the disease information and the specified symptom information is calculated；
Determine that the degree of correlation meets the disease information of preset condition as target information, the target from the disease information
Information is used to recommend corresponding medical treatment resource information to the user.
2. according to the method described in claim 1, it is characterized in that, the method further includes：
Related symptoms information is calculated according to the symptom information input by user, to the user related symptoms is recommended to believe
Breath.
3. according to the method described in claim 2, it is characterized in that, described calculate phase according to the symptom information input by user
Symptom information is closed, including：
Whole disease informations that there is correspondence with the symptom information input by user are searched from the ontology knowledge base
Set as the first disease information set；
The symptom that there is correspondence with disease information in the first disease information set is searched from the ontology knowledge base
The set of information is as the first symptom information set；
According to the weight of each symptom information in the first symptom information set to each in the first symptom information set
Symptom information carries out descending sort and obtains ranking results, and related symptoms information, each disease are determined according to the ranking results
The quantity of the weight of shape information disease information corresponding with the symptom information is inversely proportional.
4. according to the method described in claim 2, it is characterized in that, the method further includes：
The symptom information that user selects from the related symptoms information is obtained, by the symptom information input by user and institute
Symptom information that user selects from the related symptoms information is stated as specified symptom information；
According to the ontology knowledge base, the degree of correlation of the disease information and the specified symptom information is calculated；
Determine that the degree of correlation meets the target information of preset condition from the disease information, the target information is used for institute
It states user and recommends corresponding medical treatment resource information.
5. the method according to claim 1 or 4, which is characterized in that it is described according to the ontology knowledge base, calculate the disease
Sick information and the degree of correlation of the specified symptom information, including：
According to the weight of each symptom information in the ontology knowledge base and the ontology knowledge base, the disease information is calculated
With the degree of correlation of the specified symptom information, the weight disease information corresponding with the symptom information of each symptom information
Quantity is inversely proportional.
6. according to the method described in claim 5, it is characterized in that, described know according to the ontology knowledge base and the body
Know the weight of each symptom information in storehouse, calculate the degree of correlation of the disease information and the specified symptom information, including：
The set for whole disease informations that there is correspondence with the specified symptom information is searched from the ontology knowledge base
As the second disease information set；
Searched from the ontology knowledge base has correspondence with any disease information in the second disease information set
The set of symptom information is as the second symptom information set；
The second symptom information set and the specified symptom information are taken into intersection, obtain the 3rd symptom information set；
The sum of weight of each symptom information in the 3rd symptom information set is calculated, as first as a result, calculating described the
The sum of weight of each symptom information in two symptom information set, as second as a result, the weight of each symptom information with
The quantity of the corresponding disease information of the symptom information is inversely proportional；
The ratio of first result and second result is calculated, the phase as the disease information and the specified symptom information
Guan Du.
7. according to the method described in claim 1, it is characterized in that, the correspondence of the symptom information and disease information is to scheme
The form of model is stored in ontology knowledge base.
8. a kind of information recommending apparatus, which is characterized in that described device includes：
Unit is established, for establishing ontology knowledge base, the ontology knowledge base includes symptom information pass corresponding with disease information
System；
First acquisition unit, for obtaining symptom information input by user, using the symptom information input by user as specified
Symptom information；
First computing unit, for according to the ontology knowledge base, calculating the disease information and the specified symptom information
The degree of correlation；
First determination unit, for determining that the degree of correlation meets the disease information conduct of preset condition from the disease information
Target information, the target information are used to recommend corresponding medical treatment resource information to the user.
9. a kind of computer readable storage medium, which is characterized in that instruction is stored in the computer readable storage medium storing program for executing, when
When described instruction is run on the terminal device so that terminal device perform claim requirement 1-7 any one of them information pushes away
Recommend method.
10. a kind of computer program product, which is characterized in that when the computer program product is run on the terminal device, make
Obtain terminal device perform claim requirement 1-7 any one of them information recommendation methods.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711407945.5A CN108122611B (en) | 2017-12-22 | 2017-12-22 | Information recommendation method and device, storage medium and program product |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711407945.5A CN108122611B (en) | 2017-12-22 | 2017-12-22 | Information recommendation method and device, storage medium and program product |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108122611A true CN108122611A (en) | 2018-06-05 |
| CN108122611B CN108122611B (en) | 2021-05-07 |
Family
ID=62231252
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711407945.5A Active CN108122611B (en) | 2017-12-22 | 2017-12-22 | Information recommendation method and device, storage medium and program product |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108122611B (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109300535A (en) * | 2018-07-06 | 2019-02-01 | 北京康夫子科技有限公司 | Hospital guide's method, hospital guide's device and machine readable storage medium |
| CN110175295A (en) * | 2019-06-21 | 2019-08-27 | 卓尔智联(武汉)研究院有限公司 | Advertisement position recommended method, electronic equipment and computer readable storage medium |
| CN110504028A (en) * | 2019-08-22 | 2019-11-26 | 上海软中信息系统咨询有限公司 | A kind of disease way of inquisition, device, system, computer equipment and storage medium |
| CN110648754A (en) * | 2018-06-27 | 2020-01-03 | 北京百度网讯科技有限公司 | Department recommendation method, device and equipment |
| CN110911005A (en) * | 2019-11-22 | 2020-03-24 | 傲网信息科技（厦门）有限公司 | Data analysis system and server |
| WO2020113544A1 (en) * | 2018-12-07 | 2020-06-11 | Beijing Didi Infinity Technology And Development Co., Ltd. | Artificial intelligence medical symptom recognition system based on end-to-end learning |
| CN111951955A (en) * | 2020-08-13 | 2020-11-17 | 神州数码医疗科技股份有限公司 | Method and device for constructing clinical decision support system based on rule reasoning |
| CN111986793A (en) * | 2020-09-03 | 2020-11-24 | 平安国际智慧城市科技股份有限公司 | Diagnosis guide processing method and device based on artificial intelligence, computer equipment and medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102184314A (en) * | 2011-04-02 | 2011-09-14 | 中国医学科学院医学信息研究所 | Deviation symptom description-oriented automatic computer-aided diagnosis method |
| KR20140058244A (en) * | 2012-11-06 | 2014-05-14 | 한국 한의학 연구원 | Apparatus and method for searching nature of a disease on based symptom weight |
| CN103885971A (en) * | 2012-12-20 | 2014-06-25 | 阿里巴巴集团控股有限公司 | Data pushing method and data pushing device |
| CN104102816A (en) * | 2014-06-20 | 2014-10-15 | 周晋 | Symptom match and machine learning-based automatic diagnosis system and method |
| CN104463754A (en) * | 2014-12-30 | 2015-03-25 | 天津迈沃医药技术有限公司 | Method for building medical ontology database based on disease characteristics |
| CN104200069B (en) * | 2014-08-13 | 2017-08-04 | 周晋 | A kind of medication commending system and method based on symptom analysis and machine learning |
| CN107330287A (en) * | 2017-07-10 | 2017-11-07 | 叮当（深圳）健康机器人科技有限公司 | A kind of disease information analysis method and device |
-
2017
- 2017-12-22 CN CN201711407945.5A patent/CN108122611B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102184314A (en) * | 2011-04-02 | 2011-09-14 | 中国医学科学院医学信息研究所 | Deviation symptom description-oriented automatic computer-aided diagnosis method |
| KR20140058244A (en) * | 2012-11-06 | 2014-05-14 | 한국 한의학 연구원 | Apparatus and method for searching nature of a disease on based symptom weight |
| CN103885971A (en) * | 2012-12-20 | 2014-06-25 | 阿里巴巴集团控股有限公司 | Data pushing method and data pushing device |
| CN104102816A (en) * | 2014-06-20 | 2014-10-15 | 周晋 | Symptom match and machine learning-based automatic diagnosis system and method |
| CN104200069B (en) * | 2014-08-13 | 2017-08-04 | 周晋 | A kind of medication commending system and method based on symptom analysis and machine learning |
| CN104463754A (en) * | 2014-12-30 | 2015-03-25 | 天津迈沃医药技术有限公司 | Method for building medical ontology database based on disease characteristics |
| CN107330287A (en) * | 2017-07-10 | 2017-11-07 | 叮当（深圳）健康机器人科技有限公司 | A kind of disease information analysis method and device |
Non-Patent Citations (1)
| Title |
|---|
| 徐奕枫等: ""智能导医系统中TF-IDF权重改进算法研究"", 《计算机工程与应用》 * |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110648754A (en) * | 2018-06-27 | 2020-01-03 | 北京百度网讯科技有限公司 | Department recommendation method, device and equipment |
| CN109300535A (en) * | 2018-07-06 | 2019-02-01 | 北京康夫子科技有限公司 | Hospital guide's method, hospital guide's device and machine readable storage medium |
| WO2020113544A1 (en) * | 2018-12-07 | 2020-06-11 | Beijing Didi Infinity Technology And Development Co., Ltd. | Artificial intelligence medical symptom recognition system based on end-to-end learning |
| CN112655054A (en) * | 2018-12-07 | 2021-04-13 | 北京嘀嘀无限科技发展有限公司 | Artificial intelligence medical symptom identification system based on end-to-end learning |
| CN112655054B (en) * | 2018-12-07 | 2024-08-20 | 北京嘀嘀无限科技发展有限公司 | Artificial intelligence medical symptom recognition system based on end-to-end learning |
| CN110175295A (en) * | 2019-06-21 | 2019-08-27 | 卓尔智联(武汉)研究院有限公司 | Advertisement position recommended method, electronic equipment and computer readable storage medium |
| CN110504028A (en) * | 2019-08-22 | 2019-11-26 | 上海软中信息系统咨询有限公司 | A kind of disease way of inquisition, device, system, computer equipment and storage medium |
| CN110911005A (en) * | 2019-11-22 | 2020-03-24 | 傲网信息科技（厦门）有限公司 | Data analysis system and server |
| CN111951955A (en) * | 2020-08-13 | 2020-11-17 | 神州数码医疗科技股份有限公司 | Method and device for constructing clinical decision support system based on rule reasoning |
| CN111986793A (en) * | 2020-09-03 | 2020-11-24 | 平安国际智慧城市科技股份有限公司 | Diagnosis guide processing method and device based on artificial intelligence, computer equipment and medium |
| CN111986793B (en) * | 2020-09-03 | 2023-09-19 | 深圳平安智慧医健科技有限公司 | Diagnosis guiding processing method and device based on artificial intelligence, computer equipment and medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108122611B (en) | 2021-05-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108122611A (en) | A kind of information recommendation method, device and storage medium, program product | |
| US11133111B2 (en) | Methods and systems for an artificial intelligence support network for vibrant constitutional guidance | |
| US11250062B2 (en) | Artificial intelligence methods and systems for generation and implementation of alimentary instruction sets | |
| US12001964B2 (en) | Artificial intelligence advisory systems and methods for behavioral pattern matching and language generation | |
| KR102088980B1 (en) | System and Method for Providing personalized hospital information | |
| US20200321116A1 (en) | Methods and systems for generating an alimentary instruction set identifying an individual prognostic mitigation plan | |
| US10685052B2 (en) | Method of and system for information retrieval | |
| US20210004377A1 (en) | Methods and systems for automated analysis of behavior modification data | |
| US11568351B2 (en) | Systems and methods for arranging transport of alimentary components | |
| US11393589B2 (en) | Methods and systems for an artificial intelligence support network for vibrant constitutional guidance | |
| US11328819B2 (en) | Methods and systems for an artificial intelligence fitness professional support network for vibrant constitutional guidance | |
| US20220309403A1 (en) | Systems and methods for implementing generated alimentary instruction sets based on vibrant constitutional guidance | |
| US11205140B2 (en) | Methods and systems for self-fulfillment of an alimentary instruction set based on vibrant constitutional guidance | |
| CN109935337A (en) | A kind of medical record lookup method and system based on similarity measurement | |
| WO2017039755A1 (en) | Fast and accurate search generating a ranked list of healthcare providers | |
| US20180344239A1 (en) | Managing Evidence-Based Rules | |
| Rewane et al. | Food recognition and health monitoring system for recommending daily calorie intake | |
| CN111968740B (en) | Diagnostic label recommendation method and device, storage medium and electronic equipment | |
| JP2009031900A (en) | Medical checkup data processor | |
| US20220054091A1 (en) | Methods and systems for self-fulfillment of an alimentary instruction set based on vibrant constitutional guidance | |
| US11222727B2 (en) | Systems and methods for generating alimentary instruction sets based on vibrant constitutional guidance | |
| CN116368577A (en) | Analysis based on test result level | |
| JP3194666B2 (en) | Disease prevention counseling system | |
| CN113688854A (en) | Data processing method and device and computing equipment | |
| US20190172592A1 (en) | Apparatus for patient record identification |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |