CN107273671A - It is a kind of to realize the method and system that medical performance quantifies - Google Patents
It is a kind of to realize the method and system that medical performance quantifies Download PDFInfo
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Abstract
The method and system that medical performance quantifies is realized it is an object of the invention to provide a kind of, makes the quantization to medical performance more convenient also more objective.It the described method comprises the following steps：S1, set up specialized dictionary；S2, key value dictionaries are set up, assignment is carried out to the professional word in specialized dictionary；S3, using foundation specialized dictionary to medical cases carry out participle, and using key value dictionaries to medical cases progress assignment scoring；S4, the scoring progress of the medical cases of each section office collected and ranking.Compared with prior art, the advantage of this hair is effectively to quantify medical performance using medical big data, and quantized result is more accurate and objective；Quantizing process is more brief, more efficient；It is easy to the administrative service division of various big hospital and relevant unit to manage operation.
Description
Technical field
This invention relates generally to medical data processing method, and more specifically it relates to one kind realizes medical performance amount
The method system of change.
Background technology
Chinese Hospitals Informatization Development has been subjected to the course in more than 20 years, from be conceived to the HIS of flow and accounting management to
It is now widely used for recording electronic medical record system (EMR), laboratory system (LIS), the radiology system of clinical process and conclusion
(RIS), the numb system (OAS) of image system (PACS), nursing system (NIS), hand, numerous clinical systems are with structuring or non-structural
Change form have recorded all kinds of clinical datas, clinical data classification and the corresponding relation of hospital clinical information system (CIS).However,
Because the clinical data scale of construction is huge, accumulating rate is fast but wherein key link information content is limited, and many key messages need multi-source
Relationship is adjudicated, at present for for medical performance quantization also in the artificial evaluation stage, lack automation and relatively objective
Machine comment system.
The difficult point of Analysis of Medical Treatment Data, the description for essentially consisting in medical terms is changeful.Same item information is due to record
Person's custom is different, also not quite identical in expression way, for example：For the expression of family history, in " admission records ", have
It is recorded as：" family history：Hypertension, diabetes ", what is had is recorded as：" deny following family history：Hypertension, diabetes ", multiclass
Expression needs post-processing to be same expression way：Patient's identification number+family history code+result.
Therefore, when carrying out extensive semantic analysis, if not setting up standard semantic storehouse does reference, real meaning is realized
On big data analysis be highly difficult, let alone realize medical performance quantify.
The content of the invention
The problem of in order to solve to lack in the prior art based on medical big data to quantify to medical performance, the present invention
Purpose be to provide it is a kind of realize medical performance quantify method, make the quantization to medical performance more convenient also more objective.
Another technical scheme of the present invention provides a kind of system for realizing medical performance quantization.
To achieve these goals, a technical scheme of the invention provides a kind of side for realizing medical performance quantization
Method, comprises the following steps：
S1, set up specialized dictionary；
S2, key-value dictionaries are set up, assignment is carried out to the professional word in specialized dictionary；
S3, using foundation specialized dictionary to medical cases carry out participle, and using key-value dictionaries to medical cases
Carry out assignment scoring；
S4, the scoring progress of the medical cases of each section office collected and ranking.
Further, the S1 include it is following step by step：
S11, according to the medical vocabulary in the entry item typing part of medical record to set up basic specialized dictionary；
S12, using specialized dictionary, existing magnanimity medical cases are carried out with participle analysis, and count word frequency, frequency is high
, the professional selected ci poem of top n not in specialized dictionary go out, specialized dictionary is included into after classification；
S13, repetition S12 are more or less the same in P1 up to the word frequency not being included between the professional word of specialized dictionary, and 0≤P1≤
1, specialized dictionary is to complete to set up.
Further, the S2 include it is following step by step：
S21, professional word is classified, and weight assignment, inhomogeneity are carried out to different types of professional word in classification
The professional word weighted of type, the assignment scope of the weight is 0-1；
S22a, the professional word X to being assigned in medical casesi, numerical value assignment is carried out by following equation：
V=(1- | Vx-Vav|/Vav)*100,
Wherein, V is institute predicate XiActual assignment in method,
VxIt is institute predicate XiAssignment in medical cases,
VavIt is institute predicate XiAverage assignment in existing medical cases；
S22b, the professional word Y to not being assigned in medical casesi, the experience progress summed up by each medical field
Numerical value assignment, the professional word YiAssignment scope be -100 to 100；
S23, the weight assignment according to professional word and numerical value assignment calculate a final assignment of the word, and the assignment is equal to power
The product of reassignment and numerical value assignment.
Further, S3 include it is following step by step：
S31, according to specialized dictionary participle is carried out to the medical cases, and according to key-value dictionaries in the medical case
Example in and the professional word in specialized dictionary carries out assignment respectively；
S32, to professional word distinguish assignment after, the assignment for belonging to same kind of professional word in specialized dictionary is folded
Plus, when the result of superposition is more than threshold value Bh or less than threshold value Bl, the stack result is recorded and the medical cases are entered
Line flag, is then adjusted to Bh or Bl, 0≤Bh, Bl≤Bh by stack result correspondence.
Further, S4 include it is following step by step：
S41, each medical cases scoring to each section office carry out collecting superposition respectively, according to the medical case of each section office
The stack result ranking of example scoring；
The medical cases number that S42, the appearance to each section office are marked carries out collecting superposition respectively, according to mark number pair
S41 obtains ranking and is adjusted.
Another technical scheme of the present invention provides a kind of system for realizing medical performance quantization, it is characterised in that bag
Include with lower module：
Specialized dictionary module, the professional word for handling and storing medical field；
Key-value dictionary modules, for carrying out assignment to the professional word in specialized dictionary；
Case assignment module；For carrying out participle to medical cases using the specialized dictionary set up, and utilize key-value
Dictionary carries out assignment scoring to medical cases；
Summarizing module；For the medical cases scoring progress of each section office to be collected and ranking.
Further, the specialized dictionary module includes following submodule：
Professional word sub-module stored, professional word and professional word point for storing the entry item for coming from medical record
The professional word obtained after analysis submodule analyzing and processing magnanimity medical cases；
Professional word analyzes submodule, for carrying out participle analysis to existing magnanimity medical cases, and word frequency is counted, by frequency
The professional selected ci poem of high, not in professional word sub-module stored top n goes out, and professional word sub-module stored is included into after classification, until
The word frequency not being included between the professional word of professional word sub-module stored is more or less the same in P1,0≤P1≤1.
Further, the key-value dictionary modules include following submodule：
Classified weight assignment submodule, for classifying to professional word, and in classification to different types of professional word
Progress weight assignment, different types of professional word weighted, the assignment scope of the weight is 0-1；
Numerical value assignment submodule, for carrying out numerical value assignment to professional word,
To the professional word X being assigned in medical casesi, numerical value assignment is carried out by following equation：
V=(1- | Vx-Vav|/Vav)*100,
Wherein, V is institute predicate XiActual assignment in method,
VxIt is institute predicate XiAssignment in medical cases,
VavIt is institute predicate XiAverage assignment in existing medical cases,
To the professional word Y not being assigned in medical casesi, the experience progress numerical value tax summed up by each medical field
Value, the professional word YiAssignment scope be -100 to 100；
Comprehensive assignment submodule, for the weight assignment and numerical value assignment submodule obtained according to classified weight assignment submodule
The numerical value assignment that block is obtained calculates a final assignment of professional word, and the assignment is equal to the product of weight assignment and numerical value assignment.
Further, the case assignment module includes following submodule：
Case participle assignment submodule, for carrying out participle according to specialized dictionary to the medical cases, and according to key-
Value dictionaries carry out assignment respectively to the professional word in the medical cases and in specialized dictionary；
Case integrated treatment submodule, for the case after the processing of case participle assignment submodule to be carried out into integrated treatment,
The assignment that same kind of professional word in specialized dictionary will be belonged to is overlapped, when the result of superposition exceedes threshold value Bh or is less than
During threshold value Bl, the stack result is recorded and the medical cases are marked, be then adjusted to stack result correspondence
Bh or Bl, 0≤Bh, Bl≤Bh.
Further, the summarizing module includes following submodule：
Assignment is superimposed submodule, carries out collecting superposition, and root respectively for each medical cases scoring to each section office
The stack result ranking scored according to the medical cases of each section office；
Ranking adjusts submodule, carries out collecting respectively for the medical cases number that the appearance to each section office is marked folded
Plus, and be adjusted according to marking number to obtain ranking to assignment superposition submodule.
The advantage of the method and system of the present invention for realizing medical performance quantization compared with prior art is：
1) effectively medical performance can be quantified using medical big data, quantized result is more accurate and objective；
2) due to hardware platform can be coordinated to handle magnanimity medical cases, quantizing process is more brief, more efficient；
3) after each assignment and threshold value wherein is determined, this method and system need not have medical professionalism background
People run or operate, be easy to the administration of various big hospital and relevant unit.
Brief description of the drawings
Fig. 1 is according to the exemplary flow disclosed by the invention for realizing method one embodiment that medical performance quantifies
Figure；
Fig. 2 is according to the exemplary structural frames disclosed by the invention for realizing system one embodiment that medical performance quantifies
Figure；
Embodiment
Embodiments of the invention are described below in detail.The embodiment is exemplary, is only used for explaining the present invention, without
Limitation of the present invention can be considered as.In order to avoid unnecessarily obscuring the embodiment, this part is to known in some this areas
Technology, i.e., technology that it would have been obvious for a person skilled in the art, is not described in detail.
Present document relates to N value be that the performances such as the calculating of hardware platform according to where setting up specialized dictionary are determined
Fixed, the performance of hardware platform is better, and N value can be bigger.Find in certain embodiments for middle-size and small-size commerce services
For operational performance, effect is preferable between 10 and 20 for N values.It is readily apparent that for the analysis of magnanimity medical data, N's
Value is bigger, and S12 numbers of repetition are fewer, and the time for therefrom setting up specialized dictionary is also just shorter.
According to statistical significance, present document relates to the general values of P1 be 5%.But also can according to actual conditions adjust P1 with
Ensure the operability and accuracy when handling magnanimity Analysis of Medical Treatment Data for the method and system that the present invention is provided.
Bh and Bl value can be adjusted according to actual conditions, with more precise marking abnormal (scoring very high or very low)
Case.In certain embodiments, Bh values 70-95, Bl values (- 60)-(- 35) effect is preferable, Bh values 80-85, Bl value
(- 50)-(- 40) effect is more preferable.
Embodiment 1
A kind of to realize the method that medical performance quantifies, this method comprises the following steps：
S1, set up specialized dictionary:
S11, according to the medical vocabulary in the entry item typing part of medical record to set up basic specialized dictionary；
S12, using specialized dictionary, existing magnanimity medical cases are carried out with participle analysis, and count word frequency, frequency is high
, the professional selected ci poem of top n not in specialized dictionary go out, specialized dictionary is included into after classification；
S13, repetition S12 are more or less the same in P1 up to the word frequency not being included between the professional word of specialized dictionary, and 0≤P1≤
1, specialized dictionary is to complete to set up；
S2, key-value dictionaries are set up, assignment is carried out to the professional word in specialized dictionary：
S21, professional word is classified, and weight assignment, inhomogeneity are carried out to different types of professional word in classification
The professional word weighted of type, the assignment scope of the weight is 0-1；
S22a, the professional word X to being assigned in medical casesi, numerical value assignment is carried out by following equation：
V=(1- | Vx-Vav|/Vav)*100,
Wherein, V is institute predicate XiActual assignment in method,
VxIt is institute predicate XiAssignment in medical cases,
VavIt is institute predicate XiAverage assignment in existing medical cases；
S22b, the professional word Y to not being assigned in medical casesi, the experience progress summed up by each medical field
Numerical value assignment, the professional word YiAssignment scope be -100 to 100；
S23, the weight assignment according to professional word and numerical value assignment calculate a final assignment of the word, and the assignment is equal to power
The product of reassignment and numerical value assignment；
S3, using foundation specialized dictionary to medical cases carry out participle, and using key-value dictionaries to medical cases
Carry out assignment scoring：
S31, according to specialized dictionary participle is carried out to the medical cases, and according to key-value dictionaries in the medical case
Example in and the professional word in specialized dictionary carries out assignment respectively；
S32, to professional word distinguish assignment after, the assignment for belonging to same kind of professional word in specialized dictionary is folded
Plus, when the result of superposition is more than threshold value Bh or less than threshold value Bl, the stack result is recorded and the medical cases are entered
Line flag, is then adjusted to Bh or Bl, 0≤Bh, Bl≤Bh by stack result correspondence；
S4, the scoring progress of the medical cases of each section office collected and ranking：
S41, each medical cases scoring to each section office carry out collecting superposition respectively, according to the medical case of each section office
The stack result ranking of example scoring；
The medical cases number that S42, the appearance to each section office are marked carries out collecting superposition respectively, according to mark number pair
S41 obtains ranking and is adjusted.
Below for the example classified in a S21 step to medical speciality word, some are appeared in into medical oncology case
High frequency specialty word is divided into following 6 classifications, and gives different weight assignments respectively.
Therapeutic evaluation -0.3：Curative effect can, to no effect, stable disease, the state of an illness gets nowhere, and sb.'s illness took a turn for the worse, tumor regression, swell
Knurl is obviously reduced, and symptom greatly improves, and is alleviated, and symptom disappears, tumor disappearance, metastases；
Treat side reaction -0.2：Tolerance can, unknown, no side reaction, slight side reaction, moderate side reaction is serious secondary anti-
Should, severe side reaction；
Treatment spends -0.2：It is total to spend MxMember.
Historical therapeutic scheme -0.05：New Scheme, traditional scheme；
Treatment cycle -0.2：Treatment cycle LxMy god.
Other -0.05：Family members are satisfied with, Patients' satisfaction, and family members are unsatisfied with, and patient is unsatisfied with, and changes the place of examination；
According to above-mentioned classification, to being led in a S22 step of attending an imperial examination to each professional root according to above-mentioned formula or medical oncology
The experience that domain is summed up carries out the example of numerical value assignment.
Curative effect can 80, to no effect 0, stable disease 30, the state of an illness gets nowhere 20, sb.'s illness took a turn for the worse -50, tumor regression 65, tumour
80 are obviously reduced, symptom greatly improves 90, alleviate 40, symptom disappearance 95, tumor disappearance 95, metastases -85；
Tolerance can 70, unknown -10, no side reaction 90, slight side reaction 50, moderate side reaction 20, serious side reaction -30,
Severe side reaction -50；
It is total spend M=(1- | Mx-Mav|/Mav* 100) first, wherein M is the actual assignment of " total to spend " in method,
MavIt is the average assignment of " total to spend " in existing medical cases；
New Scheme 100, traditional scheme 0；
Treatment cycle L=(1- | Lx-Lav|/Lav* 100) day, wherein L are the actual tax of " treatment cycle " in method
Value, MavIt is the average assignment of " total to spend " in existing medical cases；
Family members are satisfied with 30, Patients' satisfaction 50, and family members dissatisfied -10, and patient dissatisfied -30, change the place of examination -50.
The final assignment of the above-mentioned professional word enumerated can be obtained according to step S23：
Curative effect can 24, to no effect 0, stable disease 9, the state of an illness gets nowhere 6, sb.'s illness took a turn for the worse -15, tumor regression 19.5, tumour
24 are obviously reduced, symptom greatly improves 27, alleviate 12, symptom disappearance 28.5, tumor disappearance 28.5, metastases -25.5；
Tolerance can 14, unknown -2, no side reaction 18, slight side reaction 10, moderate side reaction 4, serious side reaction -12, weight
Spend side reaction -10；
It is total to spend 0.2M；
New Scheme 5, traditional scheme 0；
Treatment cycle 0.2L；
Family members are satisfied with 1.5, Patients' satisfaction 2.5, and family members dissatisfied -0.5, and patient dissatisfied -1.5, change the place of examination -2.5.
Embodiment 2
As shown in Fig. 2 a kind of realize the system 1 that medical performance quantifies, it is characterised in that including with lower module：
Specialized dictionary module 100, the professional word for storing and handling medical field, including following submodule：
Professional word sub-module stored 110, professional word and specialty for storing the entry item for coming from medical record
The professional word obtained after word analysis submodule analyzing and processing magnanimity medical cases,
Professional word analyzes submodule 120, for carrying out participle analysis to existing magnanimity medical cases, and counts word frequency, will
Frequency is high, the professional selected ci poem of top n not in professional word sub-module stored goes out, and professional word sub-module stored is included into after classification,
Until the word frequency not being included between the professional word of professional word sub-module stored is more or less the same in 0≤P1≤1；
Key-value dictionary modules 200, for carrying out assignment, including following submodule to the professional word in specialized dictionary：
Classified weight assignment submodule 210, for classifying to professional word, and in classification to different types of specialty
Word progress weight assignment, different types of professional word weighted, the assignment scope of the weight is 0-1,
Numerical value assignment submodule 220, for carrying out numerical value assignment to professional word,
To the professional word X being assigned in medical casesi, numerical value assignment is carried out by following equation：
V=(1- | Vx-Vav|/Vav)*100,
Wherein, V is institute predicate XiActual assignment in method,
VxIt is institute predicate XiAssignment in medical cases,
VavIt is institute predicate XiAverage assignment in existing medical cases,
To the professional word Y not being assigned in medical casesi, the experience progress numerical value tax summed up by each medical field
Value, the professional word YiAssignment scope be -100 to 100,
Comprehensive assignment submodule 230, for the weight assignment and numerical value assignment obtained according to classified weight assignment submodule
Numerical value assignment that submodule is obtained calculates a final assignment of professional word, and the assignment is equal to multiplying for weight assignment and numerical value assignment
Product；
Case assignment module 300；For carrying out participle to medical cases using the specialized dictionary set up, and utilize key-
Value dictionaries carry out assignment scoring, including following submodule to medical cases：
Case participle assignment submodule 310, for carrying out participle according to specialized dictionary to the medical cases, and according to key-
Value dictionaries carry out assignment respectively to the professional word in the medical cases and in specialized dictionary,
Case integrated treatment submodule 320, for the case after the processing of case participle assignment submodule to be carried out into General Office
Reason, the assignment that will belong to same kind of professional word in specialized dictionary is overlapped, when the result of superposition exceed threshold value Bh or
During less than threshold value Bl, the stack result is recorded and the medical cases are marked, then by stack result correspondence
It is adjusted to H or Bl, 0≤Bh, Bl≤Bh；
Summarizing module 400；For the medical cases scoring progress of each section office to be collected and ranking, including following submodule
Block：
Assignment is superimposed submodule 410, carries out collecting superposition respectively for each medical cases scoring to each section office, and
The stack result ranking scored according to the medical cases of each section office,
Ranking adjusts submodule 420, collects respectively for the medical cases number that the appearance to each section office is marked
Superposition, and be adjusted according to marking number to obtain ranking to assignment superposition submodule.
Through the above description of the embodiments, those skilled in the art can be understood that the present invention can be by
Software adds the mode of required general hardware platform to realize, naturally it is also possible to by hardware, or the combination of the two is implemented.
Understood based on such, the part that technical scheme substantially contributes to prior art in other words can be with software
The form of product is embodied, and the software module or computer software product can be stored in a storage medium, if including
Dry instruction is to cause a computer equipment (can be personal computer, server, or network equipment etc.) to perform this hair
Method described in each bright embodiment.Storage medium can be random access memory (RAM), internal memory, read-only storage (ROM), electricity
Well known in programming ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or technical field
Any other form of storage medium.
Claims (10)
1. a kind of realize the method that medical performance quantifies, this method comprises the following steps：
S1, set up specialized dictionary；
S2, key-value dictionaries are set up, assignment is carried out to the professional word in specialized dictionary；
S3, using foundation specialized dictionary to medical cases carry out participle, and using key-value dictionaries to medical cases progress
Assignment scores；
S4, the scoring progress of the medical cases of each section office collected and ranking.
2. according to claim 1 realize the method that medical performance quantifies, it is characterised in that：The S1 includes following substep
Suddenly：
S11, according to the medical vocabulary in the entry item typing part of medical record to set up basic specialized dictionary；
S12, using specialized dictionary, existing magnanimity medical cases are carried out with participle analysis, and count word frequency, frequency is high, no
The professional selected ci poem of top n in specialized dictionary goes out, and specialized dictionary is included into after classification；
S13, repetition S12 are more or less the same in P1 up to the word frequency not being included between the professional word of specialized dictionary, 0≤P1≤1, specially
Industry dictionary is to complete to set up.
3. according to claim 1 realize the method that medical performance quantifies, it is characterised in that：The S2 includes following substep
Suddenly：
S21, professional word is classified, and weight assignment is carried out to different types of professional word in classification, it is different types of
Professional word weighted, the assignment scope of the weight is 0-1；
S22a, the professional word X to being assigned in medical casesi, numerical value assignment is carried out by following equation：
V=(1- | Vx-Vav|/Vav)*100,
Wherein, V is institute predicate XiActual assignment in method,
VxIt is institute predicate XiAssignment in medical cases,
VavIt is institute predicate XiAverage assignment in existing medical cases；
S22b, the professional word Y to not being assigned in medical casesi, the experience progress numerical value tax summed up by each medical field
Value, the professional word YiAssignment scope be -100 to 100；
S23, the weight assignment according to professional word and numerical value assignment calculate a final assignment of the word, and the assignment is assigned equal to weight
The product of value and numerical value assignment.
4. according to claim 1 realize the method that medical performance quantifies, it is characterised in that：The S3 includes following substep
Suddenly：
S31, according to specialized dictionary participle is carried out to the medical cases, and according to key-value dictionaries in the medical cases
And the professional word in specialized dictionary carries out assignment respectively；
S32, to professional word distinguish assignment after, the assignment for belonging to same kind of professional word in specialized dictionary is overlapped,
When the result of superposition is more than threshold value Bh or less than threshold value Bl, the stack result is recorded and rower is entered to the medical cases
Note, is then adjusted to Bh or Bl, 0≤Bh, Bl≤Bh by stack result correspondence.
5. according to claim 4 realize the method that medical performance quantifies, it is characterised in that：The S4 includes following substep
Suddenly：
S41, each medical cases scoring to each section office carry out collecting superposition respectively, are commented according to the medical cases of each section office
The stack result ranking divided；
The medical cases number that S42, the appearance to each section office are marked carries out collecting superposition respectively, according to mark number to S41
Ranking is obtained to be adjusted.
6. a kind of realize the system that medical performance quantifies, it is characterised in that including with lower module：
Specialized dictionary module, the professional word for handling and storing medical field；
Key-value dictionary modules, for carrying out assignment to the professional word in specialized dictionary；
Case assignment module；For medical cases to be carried out with participle using the specialized dictionary set up, and utilize key-value dictionaries
Assignment scoring is carried out to medical cases；
Summarizing module；For the medical cases scoring progress of each section office to be collected and ranking.
7. system according to claim 6, it is characterised in that the specialized dictionary module includes following submodule：
Professional word sub-module stored, professional word and professional word analysis for storing the entry item for coming from medical record
The professional word obtained after module analysis processing magnanimity medical cases；
Professional word analyzes submodule, for existing magnanimity medical cases to be carried out with participle analysis, and counts word frequency, and frequency is high
, the professional selected ci poem of top n not in professional word sub-module stored go out, professional word sub-module stored is included into after classification, until not
The word frequency being included between the professional word of professional word sub-module stored is more or less the same in P1,0≤P1≤1≤1.
8. system according to claim 6, it is characterised in that the key-value dictionary modules include following submodule：
Classified weight assignment submodule, is carried out for classifying to professional word, and in classification to different types of professional word
Weight assignment, different types of professional word weighted, the assignment scope of the weight is 0-1；
Numerical value assignment submodule, for carrying out numerical value assignment to professional word,
To the professional word X being assigned in medical casesi, numerical value assignment is carried out by following equation：
V=(1- | Vx-Vav|/Vav)*100,
Wherein, V is institute predicate XiActual assignment in method,
VxIt is institute predicate XiAssignment in medical cases,
VavIt is institute predicate XiAverage assignment in existing medical cases,
To the professional word Y not being assigned in medical casesi, the experience progress numerical value assignment summed up by each medical field, institute
State professional word YiAssignment scope be -100 to 100；
Comprehensive assignment submodule, weight assignment and numerical value assignment submodule for being obtained according to classified weight assignment submodule are obtained
The numerical value assignment arrived calculates a final assignment of professional word, and the assignment is equal to the product of weight assignment and numerical value assignment.
9. system according to claim 6, it is characterised in that the case assignment module includes following submodule：
Case participle assignment submodule, for carrying out participle according to specialized dictionary to the medical cases, and according to key-value words
Allusion quotation carries out assignment respectively to the professional word in the medical cases and in specialized dictionary；
Case integrated treatment submodule, will for the case after the processing of case participle assignment submodule to be carried out into integrated treatment
The assignment for belonging to same kind of professional word in specialized dictionary is overlapped, when the result of superposition exceedes threshold value Bh or less than threshold value
During Bl, the stack result is recorded and the medical cases are marked, then by the stack result correspondence be adjusted to Bh or
Bl, 0≤Bh, Bl≤Bh.
10. system according to claim 9, it is characterised in that the summarizing module includes following submodule：
Assignment is superimposed submodule, carries out collecting superposition respectively for each medical cases scoring to each section office, and according to every
The stack result ranking of the medical cases scoring of individual section office；
Ranking adjusts submodule, carries out collecting superposition respectively for the medical cases number that the appearance to each section office is marked, and
Ranking is obtained according to mark number to assignment superposition submodule to be adjusted.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108595657A (en) * | 2018-04-28 | 2018-09-28 | 成都智信电子技术有限公司 | The tables of data classification map method and apparatus of HIS systems |
| CN112768078A (en) * | 2021-01-07 | 2021-05-07 | 联仁健康医疗大数据科技股份有限公司 | Diagnosis and treatment sharing method and system, electronic equipment and storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080162469A1 (en) * | 2006-12-27 | 2008-07-03 | Hajime Terayoko | Content register device, content register method and content register program |
| CN103745424A (en) * | 2014-02-14 | 2014-04-23 | 上海市东方医院（同济大学附属东方医院） | Hospital comprehensive performance information processing system and method |
| CN106598944A (en) * | 2016-11-25 | 2017-04-26 | 中国民航大学 | Civil aviation security public opinion emotion analysis method |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080162469A1 (en) * | 2006-12-27 | 2008-07-03 | Hajime Terayoko | Content register device, content register method and content register program |
| CN103745424A (en) * | 2014-02-14 | 2014-04-23 | 上海市东方医院（同济大学附属东方医院） | Hospital comprehensive performance information processing system and method |
| CN106598944A (en) * | 2016-11-25 | 2017-04-26 | 中国民航大学 | Civil aviation security public opinion emotion analysis method |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108595657A (en) * | 2018-04-28 | 2018-09-28 | 成都智信电子技术有限公司 | The tables of data classification map method and apparatus of HIS systems |
| CN108595657B (en) * | 2018-04-28 | 2020-10-09 | 成都智信电子技术有限公司 | Data table classification mapping method and device of HIS (hardware-in-the-system) |
| CN112768078A (en) * | 2021-01-07 | 2021-05-07 | 联仁健康医疗大数据科技股份有限公司 | Diagnosis and treatment sharing method and system, electronic equipment and storage medium |
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| CN107273671B (en) | 2018-03-30 |
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