CN109817312A - A kind of medical treatment guidance method and computer equipment - Google Patents
A kind of medical treatment guidance method and computer equipment Download PDFInfo
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- 238000003745 diagnosis Methods 0.000 claims abstract description 30
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Abstract
本发明实施例提供了一种就诊引导方法及计算机设备，涉及计算机技术领域。本发明实施例通过获取患者的第一病症描述信息以及患者个人信息；然后，利用疾病类型分析模型对第一病症描述信息进行大数据处理，得到分析结果，其中，分析结果包括与第一病症描述信息对应的候选疾病类型；从而，检测候选疾病类型中是否存在满足预设条件的指定疾病类型；若检测到候选疾病类型中存在满足预设条件的指定疾病类型，将指定疾病类型确定为目标疾病类型；进而，根据目标疾病类型以及患者个人信息生成推荐就诊信息，并输出推荐就诊信息。因此，本发明实施例提供的技术方案能够准确地确定出患者患病情况，并准确提供更符合患者需求的导诊结果。
Embodiments of the present invention provide a medical consultation guidance method and computer equipment, which relate to the technical field of computers. In the embodiment of the present invention, the first disease description information and the patient's personal information are obtained; then, the disease type analysis model is used to perform big data processing on the first disease description information, and an analysis result is obtained, wherein the analysis result includes the first disease description and the first disease description. The candidate disease type corresponding to the information; thus, it is detected whether there is a specified disease type that meets the preset condition in the candidate disease type; if it is detected that there is a specified disease type that meets the preset condition in the candidate disease type, the specified disease type is determined as the target disease. Then, according to the target disease type and the patient's personal information, the recommended medical treatment information is generated, and the recommended medical treatment information is output. Therefore, the technical solutions provided by the embodiments of the present invention can accurately determine the patient's disease condition, and accurately provide a diagnosis result that better meets the needs of the patient.
Description
[technical field]
The present invention relates to field of computer technology more particularly to a kind of medical bootstrap technique and computer equipments.
[background technique]
In medical system, the patient area of hospital is a most crowded region, and patient area is registered crowded, and patient registers tired
It is difficult.It registers crowded problem to alleviate patient area, proposes that patient is in addition to that can arrive hospital by medical services in conjunction with internet
Patient area is registered, and can also be registered by online booking.
Although online booking registers and can alleviate patient area and register crowded problem, since most of patient is to medicine
The scarcity of knowledge, patient is in sick register, it is not known which department should be gone to seek doctor's interrogation, therefore, registered treatment in patient
In the process, hospital guide is just particularly important.
But existing hospital guide's service is based primarily upon the page formats such as picture+text and passes through confirmation user information, pain portion
Position, the information such as symptom description provide hospital guide's service for patient, and this hospital guide service is according only to painful area, the letter such as symptom description
Breath cannot accurately determine the disease condition of patient, provide accurate hospital guide's result.
[summary of the invention]
In view of this, the embodiment of the invention provides a kind of medical bootstrap technique and computer equipment, it can accurately really
Patient's situation is made, and the hospital guide's result for more meeting patient demand is accurately provided.
In a first aspect, the embodiment of the invention provides a kind of medical bootstrap technique, the medical bootstrap technique includes:
The first illness description information of acquisition patient and the personal patient information；
Big data processing is carried out to the first illness description information using disease type analysis model, obtains analysis knot
Fruit, wherein the analysis result includes candidate disease type corresponding with the first illness description information；
It detects in the candidate disease type with the presence or absence of the specified disease type for meeting preset condition；
If the specified disease type for existing in the candidate disease type and meeting preset condition is detected, by the specified disease
Sick type is determined as target disease type；
It is generated according to the target disease type and the personal patient information and recommends diagnosis information, and pushed away described in output
Recommend diagnosis information.
The aspect and any possible implementation manners as described above, it is further provided a kind of implementation,
If the specified disease type for meeting preset condition is not detected from the candidate disease type, output is used for
The prompt information of prompt the second illness description information of input.
The aspect and any possible implementation manners as described above, it is further provided a kind of implementation, the detection institute
It states in candidate disease type and includes: with the presence or absence of the specified disease type for meeting preset condition
The probability of illness of each candidate disease type is obtained from the analysis result；
Whether the probability of illness for detecting each candidate disease type meets threshold value, obtains testing result；
The candidate disease type that probability of illness in the testing result meets threshold value is determined as the specified disease type.
The aspect and any possible implementation manners as described above, it is further provided a kind of implementation is deposited when detecting
At least two meet preset condition specified disease type when, it is described detect in the candidate disease type exist meet it is pre-
If the specified disease type of condition, the specified disease type is determined as target disease type, comprising:
The size for comparing the probability of illness of the specified disease type, obtains comparison result；
By the maximum specified disease type of probability of illness in comparison result, it is determined as target disease type.
The aspect and any possible implementation manners as described above, it is further provided a kind of implementation is deposited when detecting
At least two meet preset condition specified disease type when, it is described detect in the candidate disease type exist meet it is pre-
If the specified disease type of condition, the specified disease type is determined as target disease type, comprising:
The display information of each specified disease type of output；
Obtain the operation information that the patient is directed to the display information, and the finger that will be indicated in the operation information
Determine disease type and is determined as the target disease type.
The aspect and any possible implementation manners as described above, it is further provided a kind of implementation, in the detection
It whether there is after meeting the specified disease type of preset condition in the candidate disease type, the method also includes:
Obtain the corresponding medical evaluation information of the target disease type；
It is generated according to the medical evaluation information and the personal patient information and recommends diagnosis information, and pushed away described in output
Recommend diagnosis information.
The aspect and any possible implementation manners as described above, it is further provided a kind of implementation, in the acquisition
After the corresponding medical evaluation information of the target disease type, comprising:
Obtain the weight configuration information of the medical evaluation information Yu the personal patient information；
It is generated according to the weight configuration information, the medical evaluation information and the personal patient information and recommends to go to a doctor
Information, and export the recommendation diagnosis information.
The aspect and any possible implementation manners as described above, it is further provided a kind of implementation, the acquisition are suffered from
The first illness description information of person and the personal patient information, comprising:
The the first illness description information and personal patient information for acquiring the patient correspond to voice messaging；
The voice messaging is identified, to obtain the first illness description information；And
The personal patient information corresponding with the voice messaging is obtained from default personal patient information's database,
In, the personal patient information includes at least: one of patient age, gender, passing medical history, address or much information.
Second aspect, the embodiment of the invention provides a kind of medical guide device, which includes:
Acquiring unit, for obtain patient the first illness description information and the personal patient information；
Processing unit, for being carried out at big data using disease type analysis model to the first illness description information
Reason obtains analysis result, wherein the analysis result includes candidate disease class corresponding with the first illness description information
Type；
Detection unit, for detecting in the candidate disease type with the presence or absence of the specified disease class for meeting preset condition
Type；
Determination unit, if for detecting the specified disease class for existing in the candidate disease type and meeting preset condition
The specified disease type is determined as target disease type by type；
Recommendation unit recommends medical letter for generating according to the target disease type and the personal patient information
Breath, and export the recommendation diagnosis information.
The third aspect the embodiment of the invention provides a kind of computer equipment, including memory, processor and is stored in
In the memory and the computer program that can run on the processor, which is characterized in that described in the processor executes
Method described in any one of first aspect is realized when computer program.
Fourth aspect, the embodiment of the invention provides a kind of computer readable storage medium, including computer-readable instruction,
When computer is read and executes the computer-readable instruction, so that computer realizes side described in any one of first aspect
Method.
Above-mentioned technical proposal has the following beneficial effects:
Technology provided by the invention, the first illness description information and the personal patient information by acquisition patient,
And big data processing is carried out to the first illness description information using disease type analysis model, thus by combining big data
Technology, so that obtaining candidate disease type more meets the first illness description information, also, by being in detection candidate disease type
It is no to there is the specified disease type for meeting preset condition, the target illness type of patient can be more accurately oriented, and it is comprehensive
The target disease type for considering patient and personal patient information are closed, so that more meeting patient's to the diagnosis information that patient recommends
Medical demand.Therefore, technical solution provided by the invention compared with the prior art, can accurately determine out patient's feelings
Condition, and the hospital guide's result for more meeting patient demand is accurately provided.
[Detailed description of the invention]
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be to needed in the embodiment attached
Figure is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for this field
For those of ordinary skill, without any creative labor, it can also be obtained according to these attached drawings other attached
Figure.
Fig. 1 is a kind of flow diagram of medical bootstrap technique provided by the embodiment of the present invention；
Fig. 2 is the flow diagram of the medical bootstrap technique of another kind provided by the embodiment of the present invention；
Fig. 3 is the flow diagram of the medical bootstrap technique of another kind provided by the embodiment of the present invention；
Fig. 4 is the flow diagram of the medical bootstrap technique of another kind provided by the embodiment of the present invention；
Fig. 5 is the flow diagram of the medical bootstrap technique of another kind provided by the embodiment of the present invention；
Fig. 6 is the flow diagram of the medical bootstrap technique of another kind provided by the embodiment of the present invention；
Fig. 7 is a kind of composition block diagram of medical guide device provided by the embodiment of the present invention；
Fig. 8 is the composition block diagram of computer equipment provided by the embodiment of the present invention.
[specific embodiment]
For a better understanding of the technical solution of the present invention, being retouched in detail to the embodiment of the present invention with reference to the accompanying drawing
It states.
It will be appreciated that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Base
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts it is all its
Its embodiment, shall fall within the protection scope of the present invention.
The term used in embodiments of the present invention is only to be not intended to be limiting merely for for the purpose of describing particular embodiments
The present invention.In the embodiment of the present invention and the "an" of singular used in the attached claims, " described " and "the"
It is also intended to including most forms, unless the context clearly indicates other meaning.
It should be appreciated that term "and/or" used herein is only a kind of incidence relation for describing affiliated partner, indicate
There may be three kinds of relationships, for example, A and/or B, can indicate: individualism A, exist simultaneously A and B, individualism B these three
Situation.In addition, character "/" herein, typicallys represent the relationship that forward-backward correlation object is a kind of "or".
It will be appreciated that though illness description letter may be described using term first, second etc. in embodiments of the present invention
Breath, but these illness description informations should not necessarily be limited by these terms.These terms are only used to for illness description information being distinguished from each other out.
For example, the first illness description information can also be referred to as the second illness and retouch in the case where not departing from range of embodiment of the invention
Information is stated, similarly, the second illness description information can also be referred to as the first illness description information.
Depending on context, word as used in this " if " can be construed to " ... when " or " when ...
When " or " in response to determination " or " in response to detection ".Similarly, depend on context, phrase " if it is determined that " or " if detection
(condition or event of statement) " can be construed to " when determining " or " in response to determination " or " when the detection (condition of statement
Or event) when " or " in response to detection (condition or event of statement) ".
The disease condition of patient cannot accurately be determined by being directed to existing hospital guide's service, provide asking for accurate hospital guide's result
Topic, the present invention proposes, by getting through the case data of hospital, the dynamic case library of magnanimity constantly rolled is formed, to adopt
With big data analysis technology, hospital guide's service is realized.
Under the guidance of the thinking, this programme embodiment provides following feasible embodiment.
The embodiment of the present invention provides a kind of medical bootstrap technique.
Specifically, referring to FIG. 1, it is the flow diagram of medical bootstrap technique provided by the embodiment of the present invention, such as
Shown in Fig. 1, method includes the following steps:
102, the first illness description information and the personal patient information of patient are obtained.
Specifically, the interactive interface that patient can be provided by executing the terminal of the medical bootstrap technique, utilizes mouse, key
Disk or touch-control write screen and input oneself current illness information and personal patient information.Alternatively, patient can also use voice
Input mode inputs oneself illness description information and personal patient information to the terminal for executing the medical bootstrap technique.
104, big data processing is carried out to the first illness description information using disease type analysis model, obtains analysis knot
Fruit, wherein analysis result includes the corresponding candidate disease type of the first illness description information.
Wherein, disease type analysis model is that a large amount of case data accumulated all the year round based on each hospital and clinic are established
's.
Specifically, the establishment process of the disease type analysis model are as follows: firstly, being carried out to a large amount of case data got
Analysis, obtains the symptom that a variety of disease types and every kind of disease type include；Then, the symptom for including by every a kind of disease type
It is handled, obtains the feature vector of every class disease type, using the feature vector of every class disease type as training sample
Input data；Using disease type as the output data of training sample, the input data of training sample is input to training pattern
In, the training pattern is trained using machine learning algorithm, to obtain the disease type analysis model.Wherein, machine
Learning algorithm can be logistic regression algorithm, algorithm of support vector machine, neural network algorithm or decision Tree algorithms etc..
106, it detects in candidate disease type with the presence or absence of the specified disease type for meeting preset condition.
If the specified disease type for existing in candidate disease type and meeting preset condition 108, is detected, by specified disease class
Type is determined as target disease type.
110, it is generated according to target disease type and personal patient information and recommends diagnosis information, and export the medical letter of recommendation
Breath.
Personal patient information involved in the present invention includes at least: patient age, gender, passing medical history, one in address
Kind or much information.
Recommendation diagnosis information of the present invention can include but is not limited to: medical hospital, accurate visit and medical doctor
It is raw etc..
Technology provided by the invention, by obtaining the first illness description information and the personal patient information of patient, and benefit
Big data processing is carried out to the first illness description information with disease type analysis model, to make by combining big data technology
It must obtain candidate disease type and more meet the first illness description information, also, by whether there is in detection candidate disease type
Meet the specified disease type of preset condition, can more accurately orient the target illness type of patient, and comprehensively considers
The target disease type of patient and personal patient information, so that more meeting the medical need of patient to the diagnosis information that patient recommends
It asks.Therefore, technical solution provided by the invention compared with the prior art, can accurately determine out patient's situation, and quasi-
The hospital guide's result for more meeting patient demand is really provided.
There is also the need to explanation, patient and non-professional doctor, patient are inputting oneself first to execution terminal
When illness information, the most apparent first illness description of some current illnesss can be only had input, and since many diseases exist
Identical illness in clinical manifestation, the candidate disease type sometimes obtained according to the first illness information of patient may go back nothing
The illness type of patient is recognized accurately in method, accordingly, it is considered to above situation be arrived, after executing the step 106, if from candidate disease
The specified disease type for meeting preset condition is not detected in type, output is for prompting mentioning for the second illness description information of input
Show information, thus, it executes terminal and obtains the second illness description information, and yet further determined according to the second illness description information
Disease type.
Above-mentioned this mode can be, according to the illness description information of patient's input for the first time, to filter out a part in fact
Then disease type judges whether there is the specified disease type for meeting preset condition in this part disease type, if it is judged that
The specified disease type for not meeting preset condition then obtains second of illness description information inputted of patient, and is based on patient
The illness description information of second of input is further determining that disease type, and execution, which judges whether there is, again meets preset condition
Specified disease type the step of, so recycle, until the specified disease type for obtaining meeting preset condition.
Further, in order to relatively rapid and accurately determine out the illness type of patient, the present invention is directed to step
With the presence or absence of the realization for the specified disease type for meeting preset condition in rapid 106 detection candidate disease type, providing one kind can
Capable implementation, as shown in Figure 2, comprising:
201, the probability of illness of each candidate disease type is obtained from analysis result.
Specifically, the i.e. disease type analysis model is in addition to the corresponding candidate disease of available first illness description information
Except type, the probability of illness of each candidate disease type can also be determined using owned a large amount of case data.If
Disease type analysis model can export the probability of illness of each candidate disease type, establish the disease using a large amount of case data
When sick type analysis model, the corresponding case load of every kind of disease type can also be counted, and by disease type and every kind of disease
Output data of the corresponding case load of sick type as training sample, to can be predicted by what machine learning training obtained
Disease type and corresponding probability of illness.
202, whether the probability of illness for detecting each candidate disease type meets threshold value, obtains testing result.
203, it will test probability of illness in result and meet the candidate disease type of threshold value and be determined as specified disease type.
Further, full when detecting the presence of at least two in order to more accurately be that patient recommends diagnosis information
When the specified disease type of sufficient preset condition, the most probable illness of patient can be inferred to from least two specified disease types
Type, thus, based on obtained most probable illness type, the recommendation diagnosis information of generation is more accurate, and recommends patient.Knot
The implementation method of above-mentioned steps 106 is closed, meets preset condition if being directed to step 108 and detecting to exist in candidate disease type
Specified disease type, is determined as the realization of target disease type, provides two kinds of feasible implementations by specified disease type,
Include:
The first implementation, as shown in Figure 3, comprising:
A301, comparison specify the size of the probability of illness of disease type, obtain comparison result.
A302, by the maximum specified disease type of probability of illness in comparison result, be determined as target disease type.
Second of implementation, as shown in Figure 4, comprising:
The display information of B301, each specified disease type of output.
B302, the operation information that patient is directed to display information, and the specified disease type that will be indicated in operation information are obtained
It is determined as target disease type.
Wherein, which is mainly used for selecting target disease type from multiple specified disease types.
Further, in order to guarantee that the diagnosis information for recommending patient adopts rate by what patient successfully adopted, the present invention is mentioned
Another implementation is supplied, if as shown in figure 5, step 108, which detects to exist in candidate disease type, meets preset condition
Specified disease type, after specified disease type is determined as target disease type, method further include:
109a, the corresponding medical evaluation information of target disease type is obtained.
The medical evaluation information involved in the present invention be suffered from this target disease type patient to itself treatment process
Evaluation information.The medical evaluation information includes: the environment of medical hospital, the attitude of medical doctor, professional standards, goes to a doctor
The evaluation informations such as effect and medical expenditure.
109b, it is generated according to medical evaluation information and personal patient information and recommends diagnosis information, and it is medical to export recommendation
Information.
In order to further ensure recommending the demand that the recommendation diagnosis information of patient more meets patient, in conjunction with above-mentioned implementation
Example, the present invention furthermore presents a kind of implementation, as shown in fig. 6, the above method includes:
109c, the weight configuration information for obtaining medical evaluation information and personal patient information.
109d, it is generated according to weight configuration information, medical evaluation information and personal patient information and recommends diagnosis information, and
Diagnosis information is recommended in output.
Wherein, above-mentioned medical evaluation information and the weight configuration information of personal patient information can have patient according to oneself
Demand configuration.
In a concrete application scene, execute terminal obtain the corresponding medical evaluation information of target disease type it
Afterwards, the voice prompting whether inquiry patient is arranged weight configuration information can be inputted, if patient wants with the medical evaluation letter of setting
Breath and the weight configuration information of personal patient information can be by speech forms to execution after receiving the voice prompting
Terminal input weight configuration information, for example, patient says " medical evaluation information and personal patient information account for 70% and 30% respectively ",
The voice for executing terminal acquisition patient obtains medical evaluation information and accounts for 70% and patient individual's letter after speech analysis is handled
Breath account for 30% weight configuration information, thus, execute terminal comprehensively consider medical evaluation information and personal patient information, preferentially to
The recommendation diagnosis information that patient recommends medical evaluation information high.
Further, the relevant information that itself is quickly and easily inputted in order to facilitate patient is directed to step 102 acquisition
The first illness description information of patient and the realization of personal patient information, comprising: acquire the first illness description information of patient
And personal patient information corresponds to voice messaging；Identify voice messaging, to obtain the first illness description information, and, from default
Personal patient information corresponding with voice messaging is obtained in personal patient information's database.
Due to some essential informations that personal patient information is patient, these information of patient hardly change, or
Say that these information of patient only have that renewal frequency is very small, based on time, in order to reduce patient to the letter for executing terminal input message
Breath amount executes medical boot time to save every time, can establish personal patient information's database, suffers from each obtain
When person's personal information, can directly it be transferred from personal patient information's database.In addition, the tone color of everyone sound, audio etc.
Feature is different, tone color, the audio of everyone sound be it is unique, therefore, a trouble can be uniquely characterized with sound
Person.Therefore, it under the guidance of above-mentioned thinking, in one embodiment of the invention, can be utilized by the sound characteristic of identification voice
Index information of the sound characteristic as retrieval is searched corresponding with the sound characteristic in default personal patient information's database
Personal patient information.There is also the need to explanations, use patient's sound as the mark of patient, are called and suffered from using patient's sound
Personal patient information in person's personal information database can guarantee the safety of personal patient information to a certain extent.
It should be noted that terminal involved in the embodiment of the present invention can include but is not limited to personal computer
(Personal Computer, PC), personal digital assistant (Personal Digital Assistant, PDA), wireless handheld
Equipment, tablet computer (Tablet Computer), mobile phone etc..
It should be noted that the executing subject of above-mentioned steps can be located locally for medical guide device, the device
The application of terminal, or can also be the plug-in unit or Software Development Kit (Software being located locally in the application of terminal
Development Kit, SDK) etc. functional units, the embodiment of the present invention is to this without being particularly limited to.
It is understood that the application can be mounted in the application program (nativeApp) in terminal, or may be used also
To be a web page program (webApp) of browser in terminal, the embodiment of the present invention is to this without limiting.
Medical bootstrap technique, the embodiment of the present invention provided by based on the above embodiment further provide the realization above method
The medical guide device embodiment of each step and method in embodiment.
Referring to FIG. 7, its composition block diagram for guide device of going to a doctor provided by the embodiment of the present invention.As shown in Fig. 7,
The device includes: acquiring unit 41, processing unit 42, detection unit 43, determination unit 44, recommendation unit 45.Wherein, it obtains single
Member 41, for obtaining the first illness description information and the personal patient information of patient；Processing unit 42, for utilizing disease class
Type analysis model carries out big data processing to the first illness description information, obtains analysis result, wherein analyzing result includes
Candidate disease type corresponding with the first illness description information；Whether detection unit 43 deposits for detecting in candidate disease type
In the specified disease type for meeting preset condition；Determination unit 44, if meeting in advance for detecting to exist in candidate disease type
If specified disease type is determined as target disease type by the specified disease type of condition；Recommendation unit 45, for according to target
Disease type and personal patient information, which generate, recommends diagnosis information, and exports recommendation diagnosis information, wherein personal patient information
It includes at least: one of patient age, gender, passing medical history, address or much information.
In the embodiment of the present invention, optionally, which further includes output unit, if the output unit is used for
The specified disease type for meeting preset condition is not detected from candidate disease type, output is for prompting the second illness of input to retouch
State the prompt information of information.
In the embodiment of the present invention, optionally, detection unit 43 is executed in detection candidate disease type with the presence or absence of satisfaction
When the specified disease type of preset condition, specifically for obtaining the probability of illness of each candidate disease type；And detection is each
Whether the probability of illness of candidate disease type meets threshold value, obtains testing result；Also, it will test probability of illness in result to meet
The candidate disease type of threshold value is determined as specified disease type.
In the embodiment of the present invention, optionally, meet preset condition when detection unit 43 detects the presence of at least two
When specified disease type, determination unit 44 executes the specified disease class for detecting and existing in candidate disease type and meeting preset condition
Type is specifically used for when specified disease type is determined as target disease type, relatively specifies the big of the probability of illness of disease type
It is small, obtain comparison result；And by the maximum specified disease type of probability of illness in comparison result, it is determined as target disease class
Type.
In the embodiment of the present invention, optionally, meet preset condition when detection unit 43 detects the presence of at least two
When specified disease type, determination unit 44 executes the specified disease class for detecting and existing in candidate disease type and meeting preset condition
Type is specifically used for when specified disease type is determined as target disease type, exports the display letter of each specified disease type
Breath；And patient is obtained for the operation information of display information, and the specified disease type indicated in operation information is determined as
Target disease type.
In the embodiment of the present invention, optionally, detected in detection unit 43 pre- with the presence or absence of meeting in candidate disease type
If after the specified disease type of condition, acquiring unit 41 is also used to obtain the corresponding medical evaluation information of target disease type；
To, recommendation unit 45 can be also used for according to evaluation information and the personal patient information's generation recommendation diagnosis information of going to a doctor, and
Diagnosis information is recommended in output.
In the embodiment of the present invention, optionally, the corresponding medical evaluation letter of target disease type is obtained in acquiring unit 41
After breath, acquiring unit 41 can be also used for obtaining the weight configuration information of medical evaluation information and personal patient information；To,
Recommendation unit 45, which can be also used for being generated according to weight configuration information, medical evaluation information and personal patient information, recommends to go to a doctor
Information, and export recommendation diagnosis information.
In the embodiment of the present invention, optionally, acquiring unit 41 be used for obtain patient the first illness description information and
When personal patient information, voice letter is corresponded to specifically for the first illness description information and personal patient information for acquiring patient
Breath；And know voice messaging, to obtain the first illness description information and personal patient information.
Wherein, identification voice is specifically included with obtaining the first illness description information and personal patient information: from default
Personal patient information corresponding with voice messaging is obtained in personal patient information's database.
Above-mentioned medical bootstrap technique, the portion that the present embodiment is not described in detail are able to carry out by each unit in this present embodiment
Point, it can refer to the related description of medical bootstrap technique.
Referring to FIG. 8, it is a kind of composition block diagram of computer equipment provided in an embodiment of the present invention, as shown in Fig. 8,
The computer equipment includes memory 51, processor 52 and is stored in the meter that can be run in memory 51 and on the processor 52
Calculation machine program, processor 52 realize the medical bootstrap technique of any of the above-described when executing computer program.
The embodiment of the invention provides a kind of computer readable storage mediums, including computer-readable instruction, work as computer
When reading and executing computer-readable instruction, so that computer realizes the medical bootstrap technique of any of the above-described.
Above-mentioned technical proposal has the following beneficial effects:
Technology provided by the invention, by obtaining the first illness description information and the personal patient information of patient, and benefit
Big data processing is carried out to the first illness description information with disease type analysis model, to make by combining big data technology
It must obtain candidate disease type and more meet the first illness description information, also, by whether there is in detection candidate disease type
Meet the specified disease type of preset condition, can more accurately orient the target illness type of patient, and comprehensively considers
The target disease type of patient and personal patient information, so that more meeting the medical need of patient to the diagnosis information that patient recommends
It asks.Therefore, technical solution provided by the invention compared with the prior art, can accurately determine out patient's situation, and quasi-
The hospital guide's result for more meeting patient demand is really provided.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,
The specific work process of device and unit, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In several embodiments provided by the present invention, it should be understood that disclosed system, device and method can be with
It realizes by another way.For example, the apparatus embodiments described above are merely exemplary, for example, the unit
It divides, only a kind of logical function partition, there may be another division manner in actual implementation, for example, multiple units or group
Part can be combined or can be integrated into another system, or some features can be ignored or not executed.Another point, it is shown
Or the mutual coupling, direct-coupling or communication connection discussed can be through some interfaces, device or unit it is indirect
Coupling or communication connection can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of hardware adds SFU software functional unit.
The above-mentioned integrated unit being realized in the form of SFU software functional unit can store and computer-readable deposit at one
In storage media.Above-mentioned SFU software functional unit is stored in a storage medium, including some instructions are used so that a computer
It is each that device (can be personal computer, server or network equipment etc.) or processor (Processor) execute the present invention
The part steps of a embodiment the method.And storage medium above-mentioned includes: USB flash disk, mobile hard disk, read-only memory (Read-
Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic or disk etc. it is various
It can store the medium of program code.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Within mind and principle, any modification, equivalent substitution, improvement and etc. done be should be included within the scope of the present invention.
Claims (10)
1. a kind of medical bootstrap technique, which is characterized in that the medical bootstrap technique includes:
Obtain the first illness description information and the personal patient information of patient；
Using disease type analysis model to the first illness description information carry out big data processing, analyzed as a result, its
In, the analysis result includes candidate disease type corresponding with the first illness description information；
It detects in the candidate disease type with the presence or absence of the specified disease type for meeting preset condition；
If the specified disease type for existing in the candidate disease type and meeting preset condition is detected, by the specified disease class
Type is determined as target disease type；
It is generated according to the target disease type and the personal patient information and recommends diagnosis information, and export the recommendation just
Examine information.
2. the method according to claim 1, wherein the medical bootstrap technique further include:
If the specified disease type for meeting preset condition is not detected from the candidate disease type, export for prompting
Input the prompt information of the second illness description information.
3. the method according to claim 1, wherein with the presence or absence of full in the detection candidate disease type
The specified disease type of sufficient preset condition includes:
The probability of illness of each candidate disease type is obtained from the analysis result；
Whether the probability of illness for detecting each candidate disease type meets threshold value, obtains testing result；
The candidate disease type that probability of illness in the testing result meets threshold value is determined as the specified disease type.
4. according to the method described in claim 3, it is characterized in that, when detecting the presence of at least two fingers for meeting preset condition
It is described to detect the specified disease type for existing in the candidate disease type and meeting preset condition when determining disease type, by institute
It states specified disease type and is determined as target disease type, comprising:
The size for comparing the probability of illness of the specified disease type, obtains comparison result；
By the maximum specified disease type of probability of illness in comparison result, it is determined as target disease type.
5. according to the method described in claim 3, it is characterized in that, when detecting the presence of at least two fingers for meeting preset condition
It is described to detect the specified disease type for existing in the candidate disease type and meeting preset condition when determining disease type, by institute
It states specified disease type and is determined as target disease type, comprising:
The display information of each specified disease type of output；
Obtain the operation information that the patient is directed to the display information, and the specified disease that will be indicated in the operation information
Sick type is determined as the target disease type.
6. method according to any one of claims 1 to 5, which is characterized in that in the detection candidate disease type
In with the presence or absence of after meeting the specified disease type of preset condition, the method also includes:
Obtain the corresponding medical evaluation information of the target disease type；
It is generated according to the medical evaluation information and the personal patient information and recommends diagnosis information, and export the recommendation just
Examine information.
7. according to the method described in claim 6, it is characterized in that, corresponding medical in the acquisition target disease type
After evaluation information, the method also includes:
Obtain the weight configuration information of the medical evaluation information Yu the personal patient information；
It is generated according to the weight configuration information, the medical evaluation information and the personal patient information and recommends medical letter
Breath, and export the recommendation diagnosis information.
8. the method according to claim 1, wherein the first illness description information for obtaining patient and trouble
Person's personal information, comprising:
The the first illness description information and the personal patient information for acquiring the patient correspond to voice messaging；
The voice messaging is identified, to obtain the first illness description information；And
The personal patient information corresponding with the voice messaging is obtained from default personal patient information's database,.
9. a kind of medical guide device, which is characterized in that the medical guide device includes:
Acquiring unit, for obtain patient the first illness description information and the personal patient information；
Processing unit is obtained for carrying out big data processing to the first illness description information using disease type analysis model
To analysis result, wherein the analysis result includes candidate disease type corresponding with the first illness description information；
Detection unit, for detecting in the candidate disease type with the presence or absence of the specified disease type for meeting preset condition；
Determination unit, if for detecting the specified disease type for existing in the candidate disease type and meeting preset condition, it will
The specified disease type is determined as target disease type；
Recommendation unit recommends diagnosis information for generating according to the target disease type and the personal patient information, and
Export the recommendation diagnosis information.
10. a kind of computer equipment, including memory, processor and storage are in the memory and can be in the processor
The computer program of upper operation, which is characterized in that the processor realized when executing the computer program as claim 1 to
8 described in any item methods.
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