CN108091396A - A kind of heart disease intelligent predicting and heart health information recommendation system and its method - Google Patents
A kind of heart disease intelligent predicting and heart health information recommendation system and its method Download PDFInfo
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- CN108091396A CN108091396A CN201711422437.4A CN201711422437A CN108091396A CN 108091396 A CN108091396 A CN 108091396A CN 201711422437 A CN201711422437 A CN 201711422437A CN 108091396 A CN108091396 A CN 108091396A
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- 208000019622 heart disease Diseases 0.000 title claims abstract description 51
- 230000005189 cardiac health Effects 0.000 title claims abstract description 21
- 238000000034 method Methods 0.000 title claims description 22
- 230000003130 cardiopathic effect Effects 0.000 claims abstract description 15
- 238000000605 extraction Methods 0.000 claims abstract description 12
- 238000004422 calculation algorithm Methods 0.000 claims description 26
- 208000024891 symptom Diseases 0.000 claims description 25
- 230000000747 cardiac effect Effects 0.000 claims description 11
- 238000004364 calculation method Methods 0.000 claims description 10
- 230000036541 health Effects 0.000 claims description 9
- 238000012545 processing Methods 0.000 claims description 7
- 239000000284 extract Substances 0.000 claims description 5
- 238000003066 decision tree Methods 0.000 claims description 4
- 238000007477 logistic regression Methods 0.000 claims description 4
- 238000007637 random forest analysis Methods 0.000 claims description 4
- 238000013528 artificial neural network Methods 0.000 claims description 3
- 238000012706 support-vector machine Methods 0.000 claims description 3
- 241000406668 Loxodonta cyclotis Species 0.000 abstract description 3
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 5
- 201000010099 disease Diseases 0.000 description 4
- 206010002383 Angina Pectoris Diseases 0.000 description 2
- 208000019901 Anxiety disease Diseases 0.000 description 2
- 230000036506 anxiety Effects 0.000 description 2
- 210000004369 blood Anatomy 0.000 description 2
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- 210000004204 blood vessel Anatomy 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 235000013399 edible fruits Nutrition 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 239000008103 glucose Substances 0.000 description 2
- 230000000116 mitigating effect Effects 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 210000002966 serum Anatomy 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 210000003462 vein Anatomy 0.000 description 2
- 208000017667 Chronic Disease Diseases 0.000 description 1
- 206010020772 Hypertension Diseases 0.000 description 1
- 230000036996 cardiovascular health Effects 0.000 description 1
- 230000005800 cardiovascular problem Effects 0.000 description 1
- 210000000748 cardiovascular system Anatomy 0.000 description 1
- 208000029078 coronary artery disease Diseases 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
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- 238000012360 testing method Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
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Abstract
The embodiment of the invention discloses a kind of heart disease intelligent predicting and heart health information recommendation system, which includes：Computing module suffers from cardiopathic probability for carrying out calculating prediction according to user's physiological parameter；Extraction module, for describing to carry out keyword extraction to the illness of user；Recommending module, for carrying out retrieval alleviation mode according to user's illness keyword and recommending user.In embodiments of the present invention, the cardiopathic prediction service of offer for the general public for lacking specialist medical knowledge and the recommendation service of heart health information are provided, allow user that can estimate the size for the possibility for suffering from heart in time, it is convenient to take measures in time, so as not to it is personal to patient when finding not in time and family brings white elephant.
Description
Technical field
The present invention relates to intelligent decision, technical field of information processing more particularly to a kind of heart disease intelligent predicting and hearts
Healthcare information commending system and its method.
Background technology
According to《American Journal of Cardiology》On portion it is complete entitled《The Health Status of Cardiovascular System of Chinese Adult》
(Status of Cardiovascular Health in Chinese Adults) research report shows that China has nearly four points
Three people there are cardiovascular problems, only 2% to reach complete health standards.Modern society's life rhythm is fast, operating pressure is big,
Cardiac is commonplace in the elderly even young people.Heart class disease mainly includes coronary heart disease, hypertension heart
Disease, rheumatic heart disease etc., it has the characteristics that, and incidence is high, death threats are big.It is counted according to world Heart Federation, heart class disease
Disease has gradually become " the first killer " for endangering human health, and such patient is often because the state of an illness or hair cannot be had found in time
It cannot be cured in time when sick and unfortunate death, if the related hidden danger of heart class disease can be found in time, accomplish to prevent trouble before it happens,
It is significant for heart patient.Angiocardiopathy is always to threaten the important illness of the people of the world's health.Heart disease category
In a kind of chronic disease, many people how to be allowed to carry out cardiopathic prediction and take relevant heart health measure, it can be with
Cardiopathic incidence is greatly reduced, reduces the loss of society and family..
For heart disease intelligent measurement, presently mainly cardiopathic whether there is is diagnosed using sorting algorithm, such as
The heart disease of Cleveland data sets based on UCI, which detects relevant algorithm, to be had:C4.5 decision Tree algorithms, native bayes
Algorithm, SVM algorithm, ANN algorithm also have logistic regression, random forest, use these Algorithm for Training Cleveland heart disease numbers
According to collection, obtained model can aid in doctor to carry out cardiopathic diagnosis, and the model that each of the above algorithm obtains can be equivalent to
One doctor, the accuracy of model can be considered as the confidence level of the doctor, and from the point of view of common sense, the diagnostic result of multiple doctors is than single
The diagnostic result of a doctor more makes patient convince.Presently, there are some medical auxiliary systems be all towards doctor, be not face
To ordinary populace.Presently, there are some medical auxiliary systems be all towards doctor, for aiding in the judgement of doctor, be not
Towards ordinary populace, it has not been convenient to which ordinary populace uses；And medical auxiliary system is also without the recommendation of related cardiac healthcare information；
Users when heart disease self-test is carried out, are detected using traditional medical means, do not facilitate non-physician professional
Ordinary user the system that can intelligently predict the probability size to suffer from a heart complaint；The model of the diagnosis of single algorithm is not as good as more
The result of a model comprehensive diagnos more allows user to convince.
The content of the invention
It is an object of the invention to overcome the deficiencies in the prior art, and the present invention provides a kind of heart disease intelligent predicting and the hearts
Dirty healthcare information commending system can reach timely hair by carrying out cardiopathic prediction and the recommendation of heart health information
Existing cardiopathic disease condition and the timely and effective purpose for preventing heart from deteriorating.
To solve the above-mentioned problems, the present invention proposes a kind of heart disease intelligent predicting and heart health information recommendation system
System, the system comprises：
Computing module suffers from cardiopathic probability for carrying out calculating prediction according to user's physiological parameter；
Extraction module, for describing to carry out keyword extraction to the illness of user；
Recommending module, for carrying out retrieval alleviation mode according to user's illness keyword and recommending user.
Preferably, recommending module includes：
Database Unit, for storing for cardiopathic related data and the alleviation method for this type illness；
Feedback unit recommends user for that will be directed to the related indication alleviation method of user.
Preferably, user's physiological parameter described in computing module is age, gender, pectoralgia type, vein pressure, every milliliter of blood
When serum weight in liquid, fasting blood-glucose, static ECG results, highest heart rate, movement whether under the ST caused by angina pectoris, movement
13 physiological parameters such as depreciation, peak value ST angles of inclination, main blood vessel number, heartbeat situation.
Preferably, computing module combines C4.5 decision Tree algorithms, NB Algorithm, algorithm of support vector machine, people
Six sorting algorithms such as artificial neural networks algorithm, logistic regression, random forest are trained heart disease prediction model.To this six
Sorting algorithm randomly selects k model, and k ∈ [3,6], we give the k model for selecting and to be numbered from 1, and number is i's
The accuracy rate of model is pi, the classification results of prediction are ri ri∈ { 0,1 }, works as riFor 0 when represent do not suffer from a heart complaint, be 1 when table
Show and have a heart disease, then carry out calculating the probability having a heart disease.The probability wherein having a heart disease is P, then according to formula meter
Calculate the concrete numerical value that probability is obtained.Its calculation formula is：
If the prediction result of k model is 0, that is, class vector r be zero to when, wherein class vector r
=(r1,r2,...,ri,...,rk), then by taxon feedback user：" health of heart "；Otherwise feedback user：" have certain
Probability has a heart disease ".
Preferably, extraction module describes the illness of itself according to user at text message progress word meaning similarity calculation
Reason obtains key vocabularies.Approximate word s in cardiac symptom vector s is such as found out from user's illness description text messagei, such as
Fruit has and siThe similar word of symptom, then being considered as user has siDescribed symptom extracts and the relevant illness word of heart disease
It converges.
Preferably, the core information of Database Unit mainly includes：Heart disease type, the corresponding symptom of different heart disease,
The mitigation scheme of different symptoms.
Correspondingly, the embodiment of the present invention additionally provides a kind of heart disease intelligent predicting and heart health information recommendation method,
This method includes：
User's physiological parameter is obtained, carries out calculating processing, obtains the probability that user has a heart disease；
It is carried out judging that prediction is handled according to result of calculation, when result is no, feedback user：" health of heart "；Work as result
To be then feedback user：" thering is certain probability to have a heart disease ", and carry out in next step；
According to description of the user to itself symptom, processing is extracted, obtains the key vocabularies similar to cardiac symptom；
Retrieval process is carried out according to the key vocabularies similar to cardiac symptom of acquisition, obtains the alleviation of relevant symptom
Mode and heart health information recommendation are to user.
In embodiments of the present invention, the cardiopathic prediction of offer for the general public for lacking specialist medical knowledge is provided
Service and the recommendation service of heart health information allow user that can estimate the size for the possibility for suffering from heart in time, convenient timely
It takes measures, in case and family personal to patient brings white elephant when finding not in time.
Description of the drawings
It in order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is attached drawing needed in technology description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention, for those of ordinary skill in the art, without creative efforts, can be with
Other attached drawings are obtained according to these attached drawings.
Fig. 1 is a kind of heart disease intelligent predicting of the embodiment of the present invention and the structure composition of heart health information recommendation system
Schematic diagram；
Fig. 2 is the flow signal of a kind of heart disease intelligent predicting and heart health information recommendation method of the embodiment of the present invention
Figure.
Specific embodiment
Below in conjunction with the attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art are obtained every other without creative efforts
Embodiment belongs to the scope of protection of the invention.
Fig. 1 is a kind of heart disease intelligent predicting of the embodiment of the present invention and the structure composition of heart health information recommendation system
Schematic diagram, as shown in Figure 1, the system includes：
Computing module suffers from cardiopathic probability for carrying out calculating prediction according to user's physiological parameter；
Extraction module, for describing to carry out keyword extraction to the illness of user；
Recommending module, for carrying out retrieval alleviation mode according to user's illness keyword and recommending user.
Recommending module further comprises：
Database Unit, for storing for cardiopathic related data and the alleviation method for this type illness；
Feedback unit recommends user for that will be directed to the related indication alleviation method of user.
In a particular embodiment, user's physiological parameter described in computing module for the age, gender, pectoralgia type, vein pressure,
When serum weight in every milliliter of blood, fasting blood-glucose, static ECG results, highest heart rate, movement whether angina pectoris, movement institute
13 physiological parameters such as the ST drop-out values of cause, peak value ST angles of inclination, main blood vessel number, heartbeat situation.
Further, computing module combine C4.5 decision Tree algorithms, NB Algorithm, algorithm of support vector machine,
Six sorting algorithms such as artificial neural network algorithm, logistic regression, random forest are trained heart disease prediction model.Wherein,
Each model can be equivalent to a doctor, and the accuracy rate of model is then equivalent to the medical skill height of doctor.Classify to this six
Algorithm randomly selects k model, and k ∈ [3,6], we give the k model for selecting and to be numbered from 1, the model that number is i
Accuracy rate be pi, the classification results of prediction are ri ri∈ { 0,1 }, works as riFor 0 when represent do not suffer from a heart complaint, be 1 when represent suffer from
There is heart disease, then carry out calculating the probability having a heart disease.The probability wherein having a heart disease is P, then is asked according to formula calculating
Go out the concrete numerical value of probability.Its calculation formula is：
If the prediction result of k model is 0, that is, class vector r be zero to when, wherein class vector r
=(r1,r2,...,ri,...,rk), then by taxon feedback user：" health of heart "；Otherwise feedback user：" have certain
Probability has a heart disease ".
Specifically, extraction module describes the illness of itself text message according to user and is opened by using Baidu NLP and AI
The API for being laid flat platform offer carries out word meaning similarity calculation processing, obtains key vocabularies.Such as from user's illness description text message
Find out approximate word s in cardiac symptom vector si, if there is and siThe similar word of symptom, then being considered as user has siIt is described
Symptom, that is, extract and the relevant illness vocabulary of heart disease.Such as user's illness describes text message and neutralizes " anxiety " word
The very high word of similarity, then being considered as user has " anxiety " this symptom and can extract the relevant illness vocabulary of heart disease.
Specifically, the core information of Database Unit mainly includes：Heart disease type, the corresponding symptom of different heart disease,
The mitigation scheme of different symptoms.
Correspondingly, the embodiment of the present invention additionally provides a kind of heart disease intelligent predicting and heart health information recommendation method,
As shown in Fig. 2, this method includes：
S1 obtains user's physiological parameter, carries out calculating processing, obtains the probability that user has a heart disease；
S2 carries out judging that prediction is handled according to result of calculation, when result is no, feedback user：" health of heart "；Work as knot
Fruit is is then feedback user：" thering is certain probability to have a heart disease ", and carry out in next step；
S3 according to description of the user to itself symptom, extracts processing, obtains the keyword similar to cardiac symptom
It converges；
S4 carries out retrieval process according to the key vocabularies similar to cardiac symptom of acquisition, obtains relevant symptom
Alleviation mode and heart health information recommendation are to user.
The flow processing of the embodiment of the method for the present invention can be found in the function of each function module in present system embodiment
Description, which is not described herein again.
In embodiments of the present invention, the cardiopathic prediction of offer for the general public for lacking specialist medical knowledge is provided
Service and the recommendation service of heart health information allow user that can estimate the size for the possibility for suffering from heart in time, convenient timely
It takes measures, in case and family personal to patient brings white elephant when finding not in time.
One of ordinary skill in the art will appreciate that all or part of step in the various methods of above-described embodiment is can
Relevant hardware to be instructed to complete by program, which can be stored in a computer readable storage medium, storage
Medium can include：Read-only memory (ROM, Read Only Memory), random access memory (RAM, Random
Access Memory), disk or CD etc..
In addition, a kind of heart disease intelligent predicting provided above to the embodiment of the present invention and heart health information recommendation system
System and its method are described in detail, and specific case used herein explains the principle of the present invention and embodiment
It states, the explanation of above example is only intended to help to understand method and its core concept of the invention；Meanwhile for this field
Those skilled in the art, thought according to the invention, in specific embodiments and applications there will be changes, to sum up institute
It states, this specification content should not be construed as limiting the invention.
Claims (4)
1. a kind of heart disease intelligent predicting and heart health information recommendation system, which is characterized in that the system comprises：
Computing module suffers from cardiopathic probability for carrying out calculating prediction according to user's physiological parameter；
Extraction module, for describing to carry out keyword extraction to the illness of user；
Recommending module, for carrying out retrieval alleviation mode according to user's illness keyword and recommending user.
2. a kind of heart disease intelligent predicting as described in claim 1 and heart health information recommendation system, which is characterized in that institute
It states computing module and combines C4.5 decision Tree algorithms, NB Algorithm, algorithm of support vector machine, artificial neural network calculation
Six sorting algorithms such as method, logistic regression, random forest are trained heart disease prediction model.It is random to six sorting algorithms
K model is chosen, k ∈ [3,6], we give the k model for selecting and to be numbered from 1, the accuracy rate for the model that number is i
For pi, the classification results of prediction are ri ri∈ { 0,1 }, works as riFor 0 when represent do not suffer from a heart complaint, be 1 when represent have a heart disease,
It then carries out calculating the probability having a heart disease.The probability wherein having a heart disease is P, then the tool of probability is obtained according to formula calculating
Body numerical value.Its calculation formula is：
<mrow>
<mi>P</mi>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<mi>k</mi>
</mfrac>
<msubsup>
<mi>&Sigma;</mi>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>k</mi>
</msubsup>
<msubsup>
<mi>p</mi>
<mi>i</mi>
<msub>
<mi>r</mi>
<mi>i</mi>
</msub>
</msubsup>
<msup>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>-</mo>
<msub>
<mi>p</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>-</mo>
<msub>
<mi>r</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
</msup>
</mrow>
If the prediction result of k model is 0, that is, class vector r be zero to when, wherein class vector r=(r1,
r2,...,ri,...,rk), then by taxon feedback user：" health of heart "；Otherwise feedback user：" there is certain probability to suffer from
There is heart disease ".
3. a kind of heart disease intelligent predicting as described in claim 1 and heart health information recommendation system, which is characterized in that institute
It states extraction module and describes text message progress word meaning similarity calculation extraction process to the illness of itself according to user, obtain crucial
Vocabulary.Approximate word s in cardiac symptom vector s is such as found out from user's illness description text messagei, if there is and siSymptom
Similar word, then being considered as user has siDescribed symptom extracts and the relevant illness vocabulary of heart disease.
4. a kind of heart disease intelligent predicting and heart health information recommendation method, this method include：
User's physiological parameter is obtained, carries out calculating processing, obtains the probability that user has a heart disease；
It is carried out judging that prediction is handled according to result of calculation, when result is no, feedback user：" health of heart "；When result is yes
Then feedback user：" thering is certain probability to have a heart disease ", and carry out in next step；
According to description of the user to itself symptom, processing is extracted, obtains the key vocabularies similar to cardiac symptom；
Retrieval process is carried out according to the key vocabularies similar to cardiac symptom, obtains the alleviation mode and heart of relevant symptom
Healthcare information recommends user.
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| CN110111887A (en) * | 2019-05-15 | 2019-08-09 | 清华大学 | Clinical aid decision-making method and device |
| CN110415821A (en) * | 2019-07-02 | 2019-11-05 | 山东大学 | A kind of health knowledge recommender system and its operation method based on human body physiological data |
| CN110634571A (en) * | 2019-09-20 | 2019-12-31 | 四川省人民医院 | Prognosis prediction system after liver transplantation |
| CN113243032A (en) * | 2018-12-21 | 2021-08-10 | 阿比奥梅德公司 | Finding adverse events using natural language processing |
| CN117334331A (en) * | 2023-10-25 | 2024-01-02 | 南京天路互联网科技有限公司 | Medical diagnosis system for health condition based on artificial intelligence |
| CN117894481A (en) * | 2024-03-15 | 2024-04-16 | 长春大学 | Bayesian super-parameter optimization gradient lifting tree heart disease prediction method and device |
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