1. A method for visually programming an expression of a medical microserver, the method comprising:

responding to the identification step of the target medical text, and acquiring basic medical information and floating medical information of the target medical text;

determining a key strategy starting sequence and a key strategy visualization sequence of the target medical text in response to the verification indication of the target medical text;

in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level for the target medical text, programming the key policy initiation sequence based on the floating medical information;

visualizing the target medical text in response to the programmed key strategy initiation sequence being less than or equal to the key strategy visualization sequence.

2. The method of claim 1, wherein the programming the critical policy initiation sequence based on the floating medical information comprises:

acquiring more than or equal to one to-be-processed medical text message of more than or equal to one information item in the floating medical information, wherein the more than or equal to one to-be-processed medical text message is respectively used for marking the medical text of the more than or equal to one information item which is being corrected;

in response to the fact that the medical text information to be processed is not larger than or equal to one, trimming the key strategy starting sequence;

feeding back the target medical text in response to the fact that one to-be-processed medical text message in the to-be-processed medical text messages exists;

wherein said tailoring said key policy initiation sequence comprises:

for one information item in the information items which are more than or equal to one information item, acquiring the to-be-processed medical text information of the one information item as a medical text label of the target medical text;

programming the key strategy starting sequence to a medical text content set which is larger than the best matching display of the one information item, wherein the medical text content set which is displayed by the best matching is used for representing the best matching value in the key strategy visualization sequence which displays the medical text which takes the one information item;

in response to the programmed key strategy starting sequence and the key strategy visualization sequence meeting the target similarity level of the target medical text, trimming the key strategy starting sequence based on a beating medical text set, wherein the beating medical text set is used for labeling the medical text which is executed initially but is not visualized completely;

feeding back the target medical text in response to the programmed key strategy starting sequence and the key strategy visualization sequence not meeting the target similarity level of the target medical text;

the beating medical text set comprises a first medical text set and a second medical text set, wherein the first medical text set is used for labeling a medical text in a visualization state or a verification passing state, and the second medical text set is used for labeling a medical text in a running state; the tailoring the key policy initiation sequence based on a beating medical text set comprises:

programming the key strategy initiation sequence to be greater than a best matching key strategy visualization sequence in the first medical text set;

in response to the programmed key strategy initiation sequence being less than or equal to the key strategy visualization sequence, trimming the key strategy visualization sequence of the medical texts in the second set of medical texts to be less than the programmed key strategy initiation sequence;

feeding back the target medical text in response to the programmed key strategy initiation sequence being greater than the key strategy visualization sequence.

3. The method of claim 2, wherein after trimming the key strategy visualization sequence of the medical texts in the second set of medical texts to be less than the programmed key strategy start sequence, the method further comprises:

feeding back one of the medical texts in the second medical text set in response to the key strategy starting sequence of the one of the medical texts being larger than the trimmed key strategy visualization sequence.

4. The method of claim 1, wherein in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level for the target medical text, prior to programming the key policy initiation sequence based on the floating medical information, the method further comprises:

responding to the fact that the target similarity level is in a binary mode, and acquiring a target medical text of the target medical text;

in response to that the key strategy visualization sequence of the target medical text is smaller than the key strategy starting sequence of the target medical text or the key strategy starting sequence of the target medical text is larger than the key strategy visualization sequence of the target medical text, acquiring an updated latest completed medical text content set to which the target medical text belongs;

determining that the target similarity level is satisfied in response to the key strategy visualization sequence of the target medical text being greater than or equal to the set of recently completed medical text content.

5. The method of claim 1, wherein in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level for the target medical text, prior to programming the key policy initiation sequence based on the floating medical information, the method further comprises:

responding to the fact that the target similarity level is forbidden and the target medical text is a writing medical text, and obtaining a target writing medical text of the target medical text;

responding to that the key strategy visualization sequence of the target medical text is smaller than the key strategy starting sequence of the target writing medical text, or the key strategy starting sequence of the target medical text is larger than the key strategy visualization sequence of the target writing medical text, and acquiring that the target of the target writing medical text only displays the medical text;

responding to that the key strategy starting sequence of the target only displaying the medical text is larger than the key strategy starting sequence of the target writing medical text, and acquiring an updated latest completed medical text content set to which the target medical text belongs;

determining that the target similarity level is satisfied in response to the key strategy visualization sequence of the target medical text being greater than or equal to the set of recently completed medical text content.

6. The method of claim 1, wherein in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level for the target medical text, prior to programming the key policy initiation sequence based on the floating medical information, the method further comprises:

responding to the target similarity level is linearized and the target medical text is a writing medical text, and acquiring a target writing medical text of the target medical text;

responding to the verification that the target medical text and the target writing medical text pass a binary system mode, and acquiring a target display-only medical text of the target writing medical text;

responding to that the key strategy starting sequence of the target only displaying the medical text is larger than the key strategy starting sequence of the target writing medical text, and acquiring an updated latest completed medical text content set to which the target medical text belongs;

determining that the target similarity level is satisfied in response to the key strategy visualization sequence of the target medical text being greater than or equal to the set of recently completed medical text content.

7. The method of claim 1, wherein in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level for the target medical text, prior to programming the key policy initiation sequence based on the floating medical information, the method further comprises:

responding to the arrangement mode of the target similarity level, and acquiring a target medical text of the target medical text;

in response to the target medical text and the target medical text passing binary verification, determining a first medical text belonging to the same update as the target medical text;

in response to the key strategy visualization sequence of the target medical text being smaller than the key strategy initiation sequence of the first medical text, obtaining the updated latest completed medical text content set;

determining that the target similarity level is met in response to the key strategy visualization sequence of the target medical text being greater than or equal to the set of recently completed medical text content; if the target medical text and the first medical text have a result relationship, trimming a key strategy starting sequence of the result medical text in the result relationship to be larger than a key strategy visualization sequence of a reason medical text.

8. The method of claim 1, wherein in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level for the target medical text, prior to programming the key policy initiation sequence based on the floating medical information, the method further comprises:

responding to the fact that the target similarity level is in a binary mode, and acquiring a target medical text of the target medical text;

in response to the target medical text and the target medical text passing binary verification, determining a first medical text belonging to the same update as the target medical text;

determining that the target similarity level is satisfied in response to the key policy visualization sequence of the target medical text being less than the key policy initiation sequence of the first medical text and the key policy initiation sequence being less than or equal to the key policy visualization sequence.

9. The method of claim 1, wherein in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level for the target medical text, prior to programming the key policy initiation sequence based on the floating medical information, the method further comprises:

responding to the target similarity grade as a result, repeatedly displaying, and acquiring a result medical text which has a result relation with the target medical text and takes the target medical text as a reason;

and trimming the key strategy starting sequence of the result medical text to be larger than the key strategy visualization sequence of the target medical text, and determining that the target similarity grade is met.

10. A system for visual programming of expressions of a medical microserver, comprising a processor and a memory in communication with each other, the processor being configured to read a computer program from the memory and execute the computer program to perform the method of any one of claims 1 to 9.

Background

With the continuous progress of visual programming technology, the visual operation is tried to be realized by taking the programming idea of 'what you see is what you get' as a principle, namely, the result can be seen at any time, and the program is synchronized with the adjustment of the result. There are significant drawbacks in the efficiency of visual programming and the performance of information-base systems.

Disclosure of Invention

In view of this, the present application provides a method and a system for performing visual programming on an expression of a medical microserver.

In a first aspect, a method for visually programming an expression of a medical microserver is provided, the method comprising:

responding to the identification step of the target medical text, and acquiring basic medical information and floating medical information of the target medical text;

determining a key strategy starting sequence and a key strategy visualization sequence of the target medical text in response to the verification indication of the target medical text;

in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level for the target medical text, programming the key policy initiation sequence based on the floating medical information;

visualizing the target medical text in response to the programmed key strategy initiation sequence being less than or equal to the key strategy visualization sequence.

Further, the programming the critical policy initiation sequence based on the floating medical information comprises:

acquiring more than or equal to one to-be-processed medical text message of more than or equal to one information item in the floating medical information, wherein the more than or equal to one to-be-processed medical text message is respectively used for marking the medical text of the more than or equal to one information item which is being corrected;

in response to the fact that the medical text information to be processed is not larger than or equal to one, trimming the key strategy starting sequence;

feeding back the target medical text in response to the fact that one to-be-processed medical text message in the to-be-processed medical text messages exists;

wherein said tailoring said key policy initiation sequence comprises:

for one information item in the information items which are more than or equal to one information item, acquiring the to-be-processed medical text information of the one information item as a medical text label of the target medical text;

programming the key strategy starting sequence to a medical text content set which is larger than the best matching display of the one information item, wherein the medical text content set which is displayed by the best matching is used for representing the best matching value in the key strategy visualization sequence which displays the medical text which takes the one information item;

in response to the programmed key strategy starting sequence and the key strategy visualization sequence meeting the target similarity level of the target medical text, trimming the key strategy starting sequence based on a beating medical text set, wherein the beating medical text set is used for labeling the medical text which is executed initially but is not visualized completely;

feeding back the target medical text in response to the programmed key strategy starting sequence and the key strategy visualization sequence not meeting the target similarity level of the target medical text;

the beating medical text set comprises a first medical text set and a second medical text set, wherein the first medical text set is used for labeling a medical text in a visualization state or a verification passing state, and the second medical text set is used for labeling a medical text in a running state; the tailoring the key policy initiation sequence based on a beating medical text set comprises:

programming the key strategy initiation sequence to be greater than a best matching key strategy visualization sequence in the first medical text set;

in response to the programmed key strategy initiation sequence being less than or equal to the key strategy visualization sequence, trimming the key strategy visualization sequence of the medical texts in the second set of medical texts to be less than the programmed key strategy initiation sequence;

feeding back the target medical text in response to the programmed key strategy initiation sequence being greater than the key strategy visualization sequence.

Further, after trimming the key strategy visualization sequence of the medical texts in the second medical text set to be smaller than the programmed key strategy starting sequence, the method further comprises:

feeding back one of the medical texts in the second medical text set in response to the key strategy starting sequence of the one of the medical texts being larger than the trimmed key strategy visualization sequence.

Further, in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level for the target medical text, before programming the key policy initiation sequence based on the floating medical information, the method further comprises:

responding to the fact that the target similarity level is in a binary mode, and acquiring a target medical text of the target medical text;

in response to that the key strategy visualization sequence of the target medical text is smaller than the key strategy starting sequence of the target medical text or the key strategy starting sequence of the target medical text is larger than the key strategy visualization sequence of the target medical text, acquiring an updated latest completed medical text content set to which the target medical text belongs;

determining that the target similarity level is satisfied in response to the key strategy visualization sequence of the target medical text being greater than or equal to the set of recently completed medical text content.

Further, in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level for the target medical text, before programming the key policy initiation sequence based on the floating medical information, the method further comprises:

responding to the fact that the target similarity level is forbidden and the target medical text is a writing medical text, and obtaining a target writing medical text of the target medical text;

responding to that the key strategy visualization sequence of the target medical text is smaller than the key strategy starting sequence of the target writing medical text, or the key strategy starting sequence of the target medical text is larger than the key strategy visualization sequence of the target writing medical text, and acquiring that the target of the target writing medical text only displays the medical text;

responding to that the key strategy starting sequence of the target only displaying the medical text is larger than the key strategy starting sequence of the target writing medical text, and acquiring an updated latest completed medical text content set to which the target medical text belongs;

determining that the target similarity level is satisfied in response to the key strategy visualization sequence of the target medical text being greater than or equal to the set of recently completed medical text content.

Further, in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level for the target medical text, before programming the key policy initiation sequence based on the floating medical information, the method further comprises:

responding to the target similarity level is linearized and the target medical text is a writing medical text, and acquiring a target writing medical text of the target medical text;

responding to the verification that the target medical text and the target writing medical text pass a binary system mode, and acquiring a target display-only medical text of the target writing medical text;

responding to that the key strategy starting sequence of the target only displaying the medical text is larger than the key strategy starting sequence of the target writing medical text, and acquiring an updated latest completed medical text content set to which the target medical text belongs;

determining that the target similarity level is satisfied in response to the key strategy visualization sequence of the target medical text being greater than or equal to the set of recently completed medical text content.

Further, in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level for the target medical text, before programming the key policy initiation sequence based on the floating medical information, the method further comprises:

responding to the arrangement mode of the target similarity level, and acquiring a target medical text of the target medical text;

in response to the target medical text and the target medical text passing binary verification, determining a first medical text belonging to the same update as the target medical text;

in response to the key strategy visualization sequence of the target medical text being smaller than the key strategy initiation sequence of the first medical text, obtaining the updated latest completed medical text content set;

determining that the target similarity level is met in response to the key strategy visualization sequence of the target medical text being greater than or equal to the set of recently completed medical text content; if the target medical text and the first medical text have a result relationship, trimming a key strategy starting sequence of the result medical text in the result relationship to be larger than a key strategy visualization sequence of a reason medical text.

Further, in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level for the target medical text, before programming the key policy initiation sequence based on the floating medical information, the method further comprises:

responding to the fact that the target similarity level is in a binary mode, and acquiring a target medical text of the target medical text;

in response to the target medical text and the target medical text passing binary verification, determining a first medical text belonging to the same update as the target medical text;

determining that the target similarity level is satisfied in response to the key policy visualization sequence of the target medical text being less than the key policy initiation sequence of the first medical text and the key policy initiation sequence being less than or equal to the key policy visualization sequence.

Further, in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level for the target medical text, before programming the key policy initiation sequence based on the floating medical information, the method further comprises:

responding to the target similarity grade as a result, repeatedly displaying, and acquiring a result medical text which has a result relation with the target medical text and takes the target medical text as a reason;

and trimming the key strategy starting sequence of the result medical text to be larger than the key strategy visualization sequence of the target medical text, and determining that the target similarity grade is met.

In a second aspect, a system for visually programming an expression of a medical microserver is provided, comprising a processor and a memory in communication with each other, the processor being configured to read a computer program from the memory and execute the computer program to implement the method described above.

The method and the system for performing visual programming on the expression of the medical micro-server, which are provided by the embodiment of the application, acquire the identification set of the target medical text, in the verification stage, whether the target medical text meets the target similarity level of the target medical text is verified according to the key strategy starting sequence and the key strategy visualization sequence of the target medical text, and dynamically programming the key strategy starting sequence based on a preset strategy, so that the finally programmed key strategy starting sequence and the key strategy visual sequence can not generate the information exception which is not allowed by the target similarity grade of the key strategy starting sequence and the key strategy visual sequence under the legal condition, and further, the target medical texts are visualized, so that different medical texts in the whole system correspond to different target similarity levels, the accuracy of medical information programming is greatly improved, and the efficiency of performing visualization programming on the expressions of the medical microserver and the performance of the information base system are improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.

Fig. 1 is a flowchart of a method for visually programming an expression of a medical microserver according to an embodiment of the present application.

Fig. 2 is a block diagram of an apparatus for visually programming an expression of a medical microserver according to an embodiment of the present disclosure.

Fig. 3 is an architecture diagram of a system for visually programming an expression of a medical microserver according to an embodiment of the present application.

Detailed Description

In order to better understand the technical solutions, the technical solutions of the present application are described in detail below with reference to the drawings and specific embodiments, and it should be understood that the specific features in the embodiments and examples of the present application are detailed descriptions of the technical solutions of the present application, and are not limitations of the technical solutions of the present application, and the technical features in the embodiments and examples of the present application may be combined with each other without conflict.

Referring to fig. 1, a method for visually programming an expression of a medical microserver is shown, which may include the technical solutions described in the following steps 100-400.

And 100, responding to the identification step of the target medical text, and acquiring basic medical information and floating medical information of the target medical text.

Illustratively, the target medical text represents the collected relevant medical information.

Further, the basic medical information indicates that each medical information has similar medical information.

Further, the floating medical information indicates that each medical information has dissimilar medical information.

Step 200, responding to the verification indication of the target medical text, and determining a key strategy starting sequence and a key strategy visualization sequence of the target medical text.

Illustratively, the check indication represents an instruction issued by the check.

Step 300, in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level of the target medical text, programming the key policy initiation sequence based on the floating medical information.

Illustratively, the key strategies represent important key medical features.

Step 400, visualizing the target medical text in response to the programmed key strategy initiation sequence being less than or equal to the key strategy visualization sequence.

It is understood that, when the technical solutions described in the above steps 100-400 are performed, the identification set of the target medical text is obtained, in the verification stage, whether the target medical text meets the target similarity level of the target medical text is verified according to the key strategy starting sequence and the key strategy visualization sequence of the target medical text, and dynamically programming the key strategy starting sequence based on a preset strategy, so that the finally programmed key strategy starting sequence and the key strategy visual sequence can not generate the information exception which is not allowed by the target similarity grade of the key strategy starting sequence and the key strategy visual sequence under the legal condition, and further, the target medical texts are visualized, so that different medical texts in the whole system correspond to different target similarity levels, the accuracy of medical information programming is greatly improved, and the efficiency of performing visualization programming on the expressions of the medical microserver and the performance of the information base system are improved.

In an alternative embodiment, the inventor finds that when the key policy starting sequence is programmed based on the floating medical information, there is a problem that the medical text is inaccurate, so that it is difficult to accurately program the key policy starting sequence based on the floating medical information, and in order to improve the above technical problem, the step of programming the key policy starting sequence based on the floating medical information described in step 200 may specifically include the technical solutions described in the following step q 1-step q 3.

And q1, acquiring more than or equal to one to-be-processed medical text message of more than or equal to one information item in the floating medical messages, wherein the more than or equal to one to-be-processed medical text message is respectively used for marking that the more than or equal to one information item is being corrected.

And step q2, in response to the fact that the medical text information which is greater than or equal to one to be processed does not exist, trimming the key strategy starting sequence.

And q3, responding to the existence of one of the medical text messages to be processed which is greater than or equal to one medical text message to be processed, and feeding back the target medical text.

It can be understood that when the technical solution described in the above step q 1-step q3 is executed, the problem of inaccurate medical texts is avoided when the key policy start sequence is programmed based on the floating medical information, so that the key policy start sequence can be accurately programmed based on the floating medical information.

In an alternative embodiment, the inventor finds that, when trimming the key strategy start sequence, there is a problem that the best matching displayed medical text content set of one information item is inaccurate, so that it is difficult to trim the key strategy start sequence accurately, and in order to improve the above technical problem, the step of trimming the key strategy start sequence described in step q2 may specifically include the technical solutions described in the following step q2a 1-step q2a 4.

And q2a1, for one of the information items which is greater than or equal to one of the information items, acquiring the to-be-processed medical text information of the one of the information items as the medical text label of the target medical text.

Step q2a2, programming the key strategy start sequence to a medical text content set which is larger than the best match display of the one information item, wherein the medical text content set which is the best match display is used for representing the best match value in the key strategy visualization sequence which displays the medical text which takes the one information item.

And step q2a3, in response to the programmed key strategy starting sequence and the key strategy visualization sequence meeting the target similarity level of the target medical text, trimming the key strategy starting sequence based on a beating medical text set, wherein the beating medical text set is used for labeling the medical text which is executed initially but is not visualized completely.

And q2a4, feeding back the target medical text in response to the programmed key strategy starting sequence and the key strategy visualization sequence not meeting the target similarity level of the target medical text.

It can be understood that when the technical solution described in the above step q2a 1-step q2a4 is executed, the problem of inaccurate medical text content set of the best match display of one information item is avoided when trimming the key strategy start sequence, so that the key strategy start sequence can be accurately trimmed.

In an alternative embodiment, the inventors have found that the set of beating medical texts comprises a first set of medical texts for labeling medical texts in a visualization state or a verification pass state and a second set of medical texts for labeling medical texts in a running state; in order to improve the technical problem, the jumping medical text set described in step q2a3 includes a first medical text set and a second medical text set, the first medical text set is used for labeling the medical text in the visualization state or the verification passing state, and the second medical text set is used for labeling the medical text in the running state; the step of modifying the key strategy starting sequence based on the beating medical text set may specifically include the technical solutions described in the following steps w 1-w 3.

Step w1, programming the key strategy start sequence to be larger than the best matching key strategy visualization sequence in the first medical text set.

Step w2, in response to the programmed key strategy start sequence being less than or equal to the key strategy visualization sequence, trimming the key strategy visualization sequence of the medical texts in the second medical text set to be less than the programmed key strategy start sequence.

And step w3, feeding back the target medical text in response to the programmed key strategy starting sequence being larger than the key strategy visualization sequence.

It is understood that when the technical solution described in the above steps w 1-w 3 is executed, the pulsating medical text set includes a first medical text set and a second medical text set, the first medical text set is used for labeling the medical text in the visualization state or the verification passing state, and the second medical text set is used for labeling the medical text in the running state; when the key strategy starting sequence is trimmed based on the beating medical text set, the problem that the key strategy visualization sequence is inaccurate is avoided, so that the key strategy starting sequence can be trimmed accurately.

Based on the above basis, after the key policy visualization sequence of the medical texts in the second medical text set is trimmed to be smaller than the programmed key policy initiation sequence, the following technical solution described in step e1 may be further included.

Step e1, in response to the starting sequence of the key strategy of one of the medical texts in the second medical text set being greater than the trimmed visualization sequence of the key strategy, feeding back the one of the medical texts.

It can be understood that, when the technical solution described in step e1 is executed, the accuracy of feeding back one of the medical texts is improved by responding to a key strategy starting sequence of one of the medical texts in the second medical text set accurately, which is greater than the trimmed key strategy visualization sequence.

Based on the above basis, in response to the key policy initiation sequence and the key policy visualization sequence satisfying the target similarity level of the target medical text, the following technical solutions described in steps r 1-r 3 may be further included before programming the key policy initiation sequence based on the floating medical information.

And r1, responding to the binary mode of the target similarity level, and acquiring a target medical text of the target medical text.

And r2, responding to the fact that the key strategy visualization sequence of the target medical text is smaller than the key strategy starting sequence of the target medical text or the key strategy starting sequence of the target medical text is larger than the key strategy visualization sequence of the target medical text, and acquiring an updated latest completed medical text content set to which the target medical text belongs.

Step r3, determining that the target similarity level is met in response to the key strategy visualization sequence of the target medical text being greater than or equal to the set of recently completed medical text content.

It can be understood that when the technical solutions described in the above steps r 1-r 3 are executed, the accuracy of meeting the target similarity level is improved by accurately acquiring the target medical text of the target medical text.

Based on the above basis, in response to the key policy initiation sequence and the key policy visualization sequence satisfying the target similarity level of the target medical text, the following technical solutions described in steps t1 to t4 may be further included before programming the key policy initiation sequence based on the floating medical information.

And step t1, in response to the target similarity level being forbidden and the target medical text being a writing medical text, acquiring a target writing medical text of the target medical text.

And t2, in response to that the key strategy visualization sequence of the target medical text is smaller than the key strategy starting sequence of the target writing medical text or that the key strategy starting sequence of the target medical text is larger than the key strategy visualization sequence of the target writing medical text, acquiring the target display-only medical text of the target writing medical text.

And step t3, responding to that the key strategy starting sequence of the target only displaying the medical text is larger than the key strategy starting sequence of the target writing the medical text, and acquiring the updated latest completed medical text content set to which the target medical text belongs.

Step t4, in response to the key strategy visualization sequence of the target medical text being greater than or equal to the set of recently completed medical text content, determining that the target similarity rating is satisfied.

It can be understood that, when the technical solutions described in the above steps t 1-t 4 are executed, the updated latest completed medical text content set to which the target medical text belongs can be accurately obtained by accurately obtaining the target writing medical text of the target medical text.

Based on the above basis, in response to the key policy initiation sequence and the key policy visualization sequence satisfying the target similarity level of the target medical text, the following technical solutions described in steps u 1-u 4 may be further included before the key policy initiation sequence is programmed based on the floating medical information.

And u1, responding to the target similarity level being linearized and the target medical text being a medical writing text, and acquiring a target medical writing text of the target medical text.

And u2, responding to the fact that the target medical text and the target writing medical text are verified in a binary mode, and acquiring the target display-only medical text of the target writing medical text.

And step u3, responding to the fact that the key strategy starting sequence of the target only displaying the medical text is larger than the key strategy starting sequence of the target writing the medical text, and acquiring the updated latest completed medical text content set to which the target medical text belongs.

Step u4, determining that the target similarity rating is met in response to the key strategy visualization sequence of the target medical text being greater than or equal to the set of recently completed medical text content.

It can be understood that when the technical solutions described in the above steps u 1-u 4 are executed, the target similarity degree can be accurately determined to be satisfied by improving the precision of writing the medical text by the target of the target medical text.

Based on the above basis, in response to the key policy initiation sequence and the key policy visualization sequence satisfying the target similarity level of the target medical text, the technical solution described in the following steps a 1-a 4 may be further included before programming the key policy initiation sequence based on the floating medical information.

Step a1, in response to the target similarity level being the arrangement mode, acquiring the target medical text of the target medical text.

Step a2, in response to the target medical text and the target medical text passing binary verification, determining a first medical text belonging to the same update as the target medical text.

Step a3, in response to the key strategy visualization sequence of the target medical text being smaller than the key strategy starting sequence of the first medical text, obtaining the updated latest completed medical text content set.

Step a4, in response to the key strategy visualization sequence of the target medical text being greater than or equal to the set of recently completed medical text content, determining that the target similarity rating is satisfied.

For example, if the target medical text and the first medical text have a result relationship, the key strategy starting sequence of the result medical text in the result relationship is trimmed to be larger than the key strategy visualization sequence of the reason medical text.

It can be understood that when the technical solutions described in the above steps a 1-a 4 are executed, the target medical texts of the target medical texts can be accurately obtained through the arrangement manner, so as to improve the completeness of determining the target similarity level.

Based on the above basis, in response to the key policy initiation sequence and the key policy visualization sequence satisfying the target similarity level of the target medical text, the following technical solutions described in steps s 1-s 3 may be further included before programming the key policy initiation sequence based on the floating medical information.

And step s1, in response to the target similarity level being in a binary mode, acquiring a target medical text of the target medical text.

Step s2, in response to the target medical text and the target medical text passing binary verification, determining a first medical text belonging to the same update as the target medical text.

Step s3, in response to the key strategy visualization sequence of the target medical text being less than the key strategy initiation sequence of the first medical text and the key strategy initiation sequence being less than or equal to the key strategy visualization sequence, determining that the target similarity level is met.

It is understood that, when the technical solutions described in the above steps s 1-s 3 are performed, the first medical text belonging to the same update as the target medical text can be accurately determined in response to the target medical text and the target medical text being verified in a binary manner. Thereby improving the accuracy of determining the level satisfying the target similarity.

Based on the above basis, in response to the key policy initiation sequence and the key policy visualization sequence satisfying the target similarity level of the target medical text, the following technical solutions described in step d1 and step d2 may be further included before programming the key policy initiation sequence based on the floating medical information.

And d1, responding to the target similarity grade as a result which can be repeatedly displayed, and acquiring a result medical text which has a result relation with the target medical text and is caused by the target medical text.

Step d2, trimming the key strategy starting sequence of the result medical text to be larger than the key strategy visualization sequence of the target medical text, and determining that the target similarity level is met.

It can be understood that, when the technical solutions described in the above steps d1 and d2 are executed, the accuracy of determining that the target similarity level is satisfied is improved by accurately acquiring the result medical text having a result relationship with the target medical text and having the target medical text as a cause.

Based on the above basis, in response to that the key policy initiation sequence and the key policy visualization sequence satisfy the target similarity level of the target medical text, before programming the key policy initiation sequence based on the floating medical information, the following technical solution described in step f1 may be further included.

Step f1, in response to the target similarity level being repeatedly displayable, displayed visualized or identified not visualized, determining that the target similarity level is satisfied.

It can be understood that when the technical solution described in the above step f1 is executed, it is precisely determined that the target similarity level is satisfied, thereby improving the accuracy of the key strategy starting sequence.

On the basis of the above, please refer to fig. 2 in combination, there is provided an apparatus 200 for visually programming an expression of a medical microserver, applied to a data processing terminal, the apparatus comprising:

a medical text acquisition module 210, configured to, in response to the identification step of the target medical text, acquire basic medical information and floating medical information of the target medical text;

a medical text determination module 220, configured to determine a key policy initiation sequence and a key policy visualization sequence of the target medical text in response to the verification indication of the target medical text;

a medical information response module 230, configured to program the key policy initiation sequence based on the floating medical information in response to the key policy initiation sequence and the key policy visualization sequence satisfying a target similarity level of the target medical text;

a text visualization module 240 configured to visualize the target medical text in response to the programmed key strategy initiation sequence being less than or equal to the key strategy visualization sequence.

On the basis of the above, please refer to fig. 3, which shows a system 300 for visualizing programming an expression of a medical microserver, comprising a processor 310 and a memory 320, which are communicated with each other, wherein the processor 310 is configured to read a computer program from the memory 320 and execute the computer program to implement the above method.

On the basis of the above, there is also provided a computer-readable storage medium on which a computer program is stored, which when executed implements the above-described method.

In summary, based on the above scheme, an identification set of a target medical text is obtained, in a verification stage, whether the target medical text meets the target similarity level of the target medical text is verified according to a key strategy starting sequence and a key strategy visualization sequence of the target medical text, and the key strategy starting sequence is dynamically programmed based on a predetermined strategy, so that the finally programmed key strategy starting sequence and key strategy visualization sequence can not generate information abnormality which is not allowed by the target similarity level of the target medical text under a legal condition, and further the target medical text is visualized, different medical texts in the whole system can be enabled to correspond to different target similarity levels, the accuracy of medical information programming is greatly improved, and the efficiency of performing visual programming on an expression of a medical micro-server and the performance of an information base system are improved.

It should be appreciated that the system and its modules shown above may be implemented in a variety of ways. For example, in some embodiments, the system and its modules may be implemented in hardware, software, or a combination of software and hardware. Wherein the hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory for execution by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the methods and systems described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided, for example, on a carrier medium such as a diskette, CD-or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules of the present application may be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, for example, or by a combination of the above hardware circuits and software (e.g., firmware).

It is to be noted that different embodiments may produce different advantages, and in different embodiments, any one or combination of the above advantages may be produced, or any other advantages may be obtained.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be considered merely illustrative and not restrictive of the broad application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present application and thus fall within the spirit and scope of the exemplary embodiments of the present application.

Also, this application uses specific language to describe embodiments of the application. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the present application is included in at least one embodiment of the present application. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the present application may be combined as appropriate.

Moreover, those skilled in the art will appreciate that aspects of the present application may be illustrated and described in terms of several patentable species or situations, including any new and useful combination of processes, machines, manufacture, or materials, or any new and useful improvement thereon. Accordingly, various aspects of the present application may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the present application may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media.

The computer storage medium may comprise a propagated data signal with the computer program code embodied therewith, for example, on baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, etc., or any suitable combination. A computer storage medium may be any computer-readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer storage medium may be propagated over any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or any combination of the preceding.

Computer program code required for the operation of various portions of the present application may be written in any one or more programming languages, including an object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C + +, C #, VB.NET, Python, and the like, a conventional programming language such as C, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, a dynamic programming language such as Python, Ruby, and Groovy, or other programming languages, and the like. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any network format, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or in a cloud computing environment, or as a service, such as a software as a service (SaaS).

Additionally, the order in which elements and sequences of the processes described herein are processed, the use of alphanumeric characters, or the use of other designations, is not intended to limit the order of the processes and methods described herein, unless explicitly claimed. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.

Similarly, it should be noted that in the preceding description of embodiments of the application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to require more features than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the numbers allow for adaptive variation. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximations that may vary depending upon the desired properties of the individual embodiments. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.

The entire contents of each patent, patent application publication, and other material cited in this application, such as articles, books, specifications, publications, documents, and the like, are hereby incorporated by reference into this application. Except where the application is filed in a manner inconsistent or contrary to the present disclosure, and except where the claim is filed in its broadest scope (whether present or later appended to the application) as well. It is noted that the descriptions, definitions and/or use of terms in this application shall control if they are inconsistent or contrary to the statements and/or uses of the present application in the material attached to this application.

Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present application. Other variations are also possible within the scope of the present application. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the present application can be viewed as being consistent with the teachings of the present application. Accordingly, the embodiments of the present application are not limited to only those embodiments explicitly described and depicted herein.

The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.