CN112270968A - Database-based drug disease matching method - Google Patents
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- 229940079593 drug Drugs 0.000 title claims description 165
- 230000000694 effects Effects 0.000 claims abstract description 53
- 229940126585 therapeutic drug Drugs 0.000 claims description 32
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- 238000003745 diagnosis Methods 0.000 claims description 15
- 230000003993 interaction Effects 0.000 claims description 11
- 238000004891 communication Methods 0.000 claims description 9
- 208000024891 symptom Diseases 0.000 claims description 9
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- 230000001225 therapeutic effect Effects 0.000 claims description 6
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- 230000004083 survival effect Effects 0.000 claims description 3
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- 208000030453 Drug-Related Side Effects and Adverse reaction Diseases 0.000 description 1
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Abstract
According to the medicine disease matching method based on the database, the disease name of a medicine to be treated is input, the matching database matches corresponding disease data from the disease information database according to the disease name, medicine data corresponding to the disease data are obtained, the matching database obtains the required treatment medicine from the medicine information database according to the medicine data and generates a treatment scheme, side effects of the medicine and complications of the disease need to be considered in the process of generating the treatment scheme, and the treatment scheme is more practical.
Description
Technical Field
The invention belongs to the technical field of medicine matching, and particularly relates to a database-based medicine disease matching method.
Background
The medicine directly acts on human body, the correct use can achieve the purpose of medication, and the wrong use not only has no effect on treatment, but also can possibly harm the health of the user who uses the medicine. Due to the particularity and complexity of the use of the medicine, the ordinary patients do not have the ability to use the medicine correctly, and the service of providing medication guidance by professional pharmacists is a very necessary measure for guaranteeing the medication safety. However, the pharmaceutical service resources in China are very deficient at present, and particularly in basic medical institutions and retail drug stores, the requirements of safe medication of patients cannot be met by the number of pharmacists and professional service capacity of the pharmacists.
Therefore, by using an informatization technology and combining professional data and business of pharmacy, an intelligent system for guiding the medication of a patient is developed, and the pharmacy staff is assisted to provide personalized medication guidance for the patient, so that the limitation of professional resources of medical institutions of different levels and retail pharmacies can be broken, professional data and business experience can be shared, the working efficiency of the pharmacy staff can be greatly improved, the problem of insufficient resources of pharmacists can be effectively relieved, and the accessibility of the pharmacy service of the patient can be realized.
Through retrieval: the invention has the following patent: a method, system and device for intelligent medication guidance (application No. 201510038947.6, filing date 2015.01.26), the method of which comprises: extracting the content of medication guidance and related element information in the medicine use information by establishing a medication guidance related multidimensional attribute item dictionary, and processing each piece of medication guidance related information by applying a multidimensional attribute item dictionary unit to generate a medication guidance and related element database; setting priority levels of various medication guidance information under different use conditions according to importance levels of medication guidance contents, disease treatment and adverse drug reactions of different patients and different diseases when different medicines are used; and finally, intelligently matching and comparing the medication related information of the patient with the medication guide and related element database, and sequencing the extracted medication guide information to generate a patient medication guide information list. By implementing the intelligent medication guidance method, the system and the equipment, information technology and equipment can be applied to provide medication guidance for patients. However, the application has the disadvantages that the mechanical matching can only be carried out according to the existing treatment relation between the medicines and the diseases, the matched effect is not good enough, and a comprehensive treatment scheme is not difficult to provide for patients.
Disclosure of Invention
1. Technical problem to be solved by the invention
The invention aims to solve the problems that the effect of the existing medicine disease matching is not good enough and a comprehensive treatment scheme is not provided for patients.
2. Technical scheme
In order to achieve the purpose, the technical scheme provided by the invention is as follows:
the invention discloses a database-based medicine disease matching method, which comprises the steps of inputting a disease name of a medicine to be treated, matching corresponding disease data from a disease information database by a matching database according to the disease name, obtaining medicine data corresponding to the disease data, obtaining the required medicine from the medicine information database by the matching database according to the medicine data, and generating a treatment scheme.
Preferably, the method is performed using a drug disease matching database as follows:
the system comprises a drug information database, wherein the drug information database is used for storing all drug information data, the drug information database comprises a basic drug database and an extended drug database, the basic drug database stores basic information of drugs, and the extended drug database stores extended information of the drugs;
the matching database is used for storing relevant data of the drug treatment diseases, and the matching database generates a treatment scheme of the drug treatment diseases according to the relevant data;
the disease information database is used for storing information data of all diseases, and comprises a basic disease database and an extended disease database, wherein the basic disease database stores related information of diseases, and the extended disease database stores related information of diseases;
the matching database is respectively in communication connection with the medicine information database and the disease information database, the matching database is also in communication connection with an interaction module, and the interaction module is used for inputting and outputting data and searching and calling the data.
Preferably, the extended drug database comprises a similar drug database and a similar molecular compound database, and the similar drug database is used for storing different drug-related data of the same drug effect; the same type of molecular compound database is used for storing molecular structure data of the medicines and correlation data of different medicines with the same type of molecular structures;
the extended disease database comprises a similar disease database and a concurrent disease database, wherein the similar disease database is used for storing different disease data of type symptoms, and the concurrent disease database is used for storing concurrent disease data associated with diseases;
the matching database comprises an actual matching database and a theoretical matching database, the actual matching database comprises a medicine matching database and a doctor diagnosis database, the medicine matching database stores corresponding matching data of existing known medicines and diseases, the doctor diagnosis database stores collected diagnosis and treatment schemes of doctors for the diseases, and the theoretical matching database stores corresponding matching data of medicines and diseases in the research and development or experimental stage;
the system also comprises a scoring module in communication connection, wherein the scoring module comprises a period scoring unit, a price scoring unit and a curative effect scoring unit, the period scoring unit stores treatment period data of the drug treatment diseases and outputs corresponding period scores according to the period time of the treatment scheme output by the matching database; the price scoring unit stores price data of the medicine and outputs corresponding price scores according to the treatment schemes output by the matching database, and the curative effect scoring unit stores medicine curative effect data and outputs corresponding curative effect scores according to the treatment schemes output by the matching database;
the matching database further comprises a feasibility evaluation module for determining the feasibility of drug treatment of a disease, the feasibility evaluation module comprising a side effect evaluation unit and a sequelae evaluation unit.
Preferably, the matching database performs the confirmation of the disease to be analyzed according to the data stored in the disease information database, specifically, the disease information of the drug to be searched is input according to the interaction module, the disease information may be a disease or a name of the disease, when the disease information is a disease, the disease name and the data related to the disease are stored as the first disease data for subsequent operation after the corresponding disease name is found by comparing with the disease information database 300, and if the disease information is a disease name, the data related to the disease and the name of the disease are directly stored as the first disease data for subsequent operation.
Preferably, the subsequent operation is to match the first disease data with the expanded disease database to obtain a concurrent disease corresponding to the disease, and obtain occurrence probability and symptoms of the concurrent disease, and when the probability of the concurrent disease is greater than 70%, merge the disease name and related data with the probability greater than 70% with the first disease data into second disease data; the matching database acquires the drug data from the drug information database according to the first disease data and/or the second disease data, selects the first disease data as the disease to be analyzed when only the first disease data exists, and preferably selects the second disease data as the disease to be analyzed when the first disease data and the second disease data exist simultaneously.
Preferably, when the matching database obtains the drug data from the drug information database, the existing known drug data related to the disease to be analyzed and the drug data related to the diagnosis and treatment plan of the disease to be analyzed by the doctor are respectively obtained from the actual matching database and the theoretical matching database of the matching database, and the first therapeutic drug data is obtained by merging the drug data with the first therapeutic drug data when the drug data related to the disease to be analyzed at the development or experiment stage is stored in the theoretical matching database, the first therapeutic drug data or the second therapeutic drug data obtained by the matching database is retrieved from the drug information database, when the drug information database first obtains the basic drug data corresponding to the first therapeutic drug data or the second therapeutic drug data from the basic drug database, and when the second therapeutic drug data exists, the second therapeutic drug data is preferred, the extended drug data matched with the basic drug information is acquired from the extended drug database, the basic drug data and the extended drug data are combined into third therapeutic drug data, and the matching database generates a therapeutic scheme according to the third therapeutic drug data.
Preferably, the method further includes the step of calculating by the scoring module according to the scores respectively output by the period scoring unit, the price scoring unit and the curative effect scoring unit to obtain corresponding medical scheme scores, wherein the score output by the period scoring unit is T, the score output by the price scoring unit is P, the score output by the curative effect scoring unit is D, the score output by the scoring module is S, S is 0.3T +0.2P +0.5D, and when S is greater than 2.5, T is greater than 2, P is greater than 1, and D is simultaneously satisfied, the therapeutic drug and the therapeutic scheme are feasible.
Preferably, the score T output by the cycle scoring unit is specifically five grades of 1 score, 2 score, 3 score, 4 score and 5 score, and the treatment cycle T1 calculated by the cycle scoring unit according to the treatment scheme generated by the matching database is compared with the average survival time T2 of the patient with the disease;
Preferably, the scores P output by the price scoring unit are specifically five grades of 1 score, 2 score, 3 score, 4 score and 5 score, and the treatment cost P1 calculated by the price scoring unit according to the treatment scheme generated by the matching database is compared with the per-person bearable cost interval;
when P1 is more than 100 ten thousand, P is 1;
when 100 is more than or equal to P1 and more than 60 ten thousand, P is 2;
when the P1 is more than 20 ten thousand at 60, P is 3;
when 20 is more than or equal to P1 and more than 10 ten thousand, P is 4;
when 10 ten thousand is more than or equal to P1, P is 5.
Preferably, the score D output by the curative effect scoring unit is specifically five grades of 1 score, 2 score, 3 score, 4 score and 5 score, and the score D output by the curative effect scoring unit is specifically a comprehensive score of an average cure rate score a of the scheme and an average occurrence rate score B of side effects or sequelae of the scheme, wherein the average cure rate is a, and the average occurrence rate of the side effects or the sequelae is B;
when a is more than 80%, A is 5;
when 80% or more and a is more than 60%, A is 4;
when 60% or more and a is more than 40%, A is 3;
when 40% or more and a is more than 20%, A is 2;
when 20% is more than or equal to a, A is 1;
when B > 80%, B ═ 1;
when B is more than 60% and more than 80%, B is 2;
when B is more than 40% and more than 60%, B is 3;
when B is more than 20% and more than 40%, B is 4;
when the content is more than or equal to 10 percent, B is 5;
D=0.65A+0.35B。
3. advantageous effects
Compared with the prior art, the technical scheme provided by the invention has the following beneficial effects:
according to the medicine disease matching method based on the database, the disease name of a medicine to be treated is input, the matching database matches corresponding disease data from the disease information database according to the disease name, medicine data corresponding to the disease data are obtained, the matching database obtains the required treatment medicine from the medicine information database according to the medicine data and generates a treatment scheme, side effects of the medicine and complications of the disease need to be considered in the process of generating the treatment scheme, and the treatment scheme is more practical.
Drawings
FIG. 1 is a schematic diagram of the structure of a drug disease matching database according to the present embodiment;
the reference numerals in the schematic drawings illustrate:
100. a drug information database; 110. a base drug database; 120. expanding a drug database; 121. a database of similar drugs; 122. a database of homogeneous molecular compounds; 200. matching the database; 210. an actual matching database; 211. a drug matching database; 212. a doctor's diagnosis database; 220. a theoretical matching database; 230. a feasibility evaluation module; 231. a side effect evaluation unit; 232. a sequela evaluation unit; 300. a database of disease information; 310. a base disease database; 320. expanding a disease database; 321. a similar disease database; 322. a concurrent disease database; 400. a scoring module; 410. a period scoring unit; 420. a price scoring unit; 430. a efficacy scoring unit; 500. and an interaction module.
Detailed Description
In order to facilitate an understanding of the invention, the invention will now be described more fully hereinafter with reference to the accompanying drawings, in which several embodiments of the invention are shown, but which may be embodied in many different forms and are not limited to the embodiments described herein, but rather are provided for the purpose of providing a more thorough disclosure of the invention.
It will be understood that when an element is referred to as being "secured to" another element, it can be directly on the other element or intervening elements may also be present; when an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present; the terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs; the terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention; as used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
Example 1
Referring to fig. 1, in the database-based drug disease matching method of this embodiment, a disease name for which a therapeutic drug needs to be acquired is input, the matching database matches corresponding disease data from the disease information database according to the disease name, and acquires drug data corresponding to the disease data, and the matching database acquires the required therapeutic drug from the drug information database according to the drug data and generates a treatment plan.
The method is carried out by adopting a drug disease matching database as follows:
the drug information database 100 is used for storing all drug information data, the drug information database 100 comprises a basic drug database 110 and an extended drug database 120, the basic drug database 110 stores basic information of drugs, and the extended drug database 120 stores extended information of drugs;
a matching database 200, wherein the matching database 200 is used for storing relevant data of drug treatment diseases, and the matching database 200 generates treatment schemes of the drug treatment diseases according to the relevant data;
a disease information database 300, wherein the disease information database 300 is used for storing information data of all diseases, including symptoms, concurrent symptoms, names, alternative names and the like of the diseases, corresponding to the diseases, the disease information database 300 includes a basic disease database 310 and an extended disease database 320, the basic disease database 310 stores relevant information of the diseases, the extended disease database 320 stores relevant information of the diseases, and the relevant information of the diseases mainly includes the diseases and the concurrent diseases possibly caused by the diseases;
the matching database 200 is respectively connected with the medicine information database 100 and the disease information database 300 in a communication manner, the matching database 200 is further connected with an interaction module 400 in a communication manner, and the interaction module 400 is used for inputting and outputting data and searching and calling the data.
The interaction module 400 inputs disease information of a medicine to be searched, the disease information may be a symptom or a specific disease name for diagnosis, the matching database 200 confirms a disease to be analyzed according to data stored in the disease information database 300, and after the disease is confirmed, the medicine information related to the disease to be analyzed is retrieved from the medicine information database 100 and a treatment plan is generated.
Wherein the extended drug database 120 comprises a similar drug database 121 and a similar molecular compound database 122, and the similar drug database 121 is used for storing different drug-related data of the same drug effect; the homogeneous molecular compound database 122 is used for storing molecular structure data of drugs and correlation data of different drugs with the same type of molecular structure.
The extended disease database 320 includes a similar disease database 321 for storing different disease data for the type symptom and a concurrent disease database 322 for storing concurrent disease data associated with the disease.
The matching database 200 comprises an actual matching database 210 and a theoretical matching database 220, the actual matching database 210 comprises a medicine matching database 211 and a doctor diagnosis database 212, the medicine matching database 211 stores the corresponding matching data of the existing known medicines and diseases, including information of medicine efficacy, cost, cure period, side effects and the like, the doctor diagnosis database 212 stores the collected medicine data related to the diagnosis and treatment scheme of the doctor on the diseases and the use scheme of all medicines, and the theoretical matching database 220 stores the corresponding matching data of the medicines and the diseases in the research and development or experimental stage, including information of medicine efficacy, cost, cure period, side effects and the like.
The matching database 200 determines a disease to be analyzed according to data stored in the disease information database 300, specifically, the disease information of a drug to be searched is input according to the interaction module 400, the disease information may be a disease or a name of the disease, when the disease information is a disease, the disease name and the data related to the disease are stored as first disease data for subsequent operation after the corresponding disease name is found by comparing with the disease information database 300, and if the disease information is a disease name, the disease name and the data related to the disease are directly stored as the first disease data for subsequent operation. The subsequent operation is to match the first disease data with the extended disease database 320 to obtain the concurrent disease corresponding to the disease, and obtain the occurrence probability and symptoms of the concurrent disease, and when the probability of the concurrent disease is greater than 70%, merge the disease name and related data with the probability greater than 70% with the first disease data into the second disease data. The matching database 200 acquires the drug data from the drug information database 100 based on the first disease data and/or the second disease data, selects the first disease data as the disease to be analyzed when only the first disease data exists, and preferably selects the second disease data as the disease to be analyzed when the first disease data and the second disease data exist simultaneously.
When the matching database 200 obtains the drug data from the drug information database 100, the existing known drug data related to the disease to be analyzed and the drug data related to the diagnosis and treatment plan of the disease to be analyzed by the doctor are respectively obtained from the actual matching database 210 and the theoretical matching database 220 of the matching database 200, the first therapeutic drug data is obtained by combining the drug data, when the drug data related to the disease to be analyzed at the development or experiment stage is stored in the theoretical matching database 220, the first therapeutic drug data or the second therapeutic drug data taken by the matching database 200 is retrieved from the drug information database 100, when the drug information database 100 first retrieves the basic drug data corresponding to the first therapeutic drug data or the second therapeutic drug data from the basic drug database 110, when the second therapeutic drug data exists, the second therapeutic drug data is preferred, the extended drug data matched with the basic drug information is acquired from the extended drug database 120, the basic drug data and the extended drug data are combined into third therapeutic drug data, the matching database 200 generates a plurality of treatment schemes according to the third therapeutic drug data, and as the third therapeutic drug data include all the drug information related to the disease to be analyzed, the matching database 200 generates a plurality of treatment schemes according to all the drug information in the third therapeutic drug data and the use schemes of all the drugs in the doctor diagnosis database 212.
The expanded drug data is different drugs which have the same drug action with the drug of the basic drug data and are stored in the similar drug database 121 and/or different drugs which have the same type of molecular structure with the drug of the basic drug data and are stored in the similar molecular compound database 122, and the expanded drug data is secondarily judged to screen out the expanded drug data which has the same drug action with the basic drug data.
The disease treatment system further comprises a scoring module 400 connected in a communication mode, wherein the scoring module 400 comprises a period scoring unit 410, a price scoring unit 420 and a curative effect scoring unit 430, the period scoring unit 410 stores treatment period data of the drug treatment diseases and outputs corresponding period scores according to the period time of the treatment scheme output by the matching database 200; the price scoring unit 420 stores price data of the drug and outputs a corresponding price score according to the treatment scheme output from the matching database 200, and the curative effect scoring unit 430 stores drug curative effect data and corresponding side effect data and outputs a corresponding curative effect score according to the treatment scheme output from the matching database 200.
The matching database 200 further includes a feasibility evaluation module 230, the feasibility evaluation module 230 is used for determining the feasibility of the drug for treating the disease, the feasibility evaluation module 230 includes a side effect evaluation unit 231 and a sequelae evaluation unit 232, the side effect evaluation unit 231 stores the side effect or sequelae data and the average occurrence rate of the side effect or sequelae of the drug in the drug information database 100, and the sequelae evaluation unit 232 stores the average occurrence probability of the complications of the disease in the disease information database 300.
The curative effect scoring unit 430 further obtains the concurrent disease corresponding to the disease in the sequelae evaluating unit 232 and obtains the average occurrence probability of the concurrent disease, the curative effect scoring unit 430 further obtains the side effect data corresponding to the drug in the side effect evaluating unit 231 and obtains the probability of occurrence of the side effect, and the average occurrence probability of the concurrent disease and the probability of occurrence of the side effect are selected as the average occurrence rate of the side effect or the sequelae with high probability.
The scoring module 400 calculates scores respectively output by the period scoring unit 410, the price scoring unit 420 and the curative effect scoring unit 430 to obtain corresponding medical scheme scores, wherein the score output by the period scoring unit 410 is T, the score output by the price scoring unit 420 is P, the score output by the curative effect scoring unit 430 is D, the score output by the scoring module 400 is S, S is 0.3T +0.2P +0.5D, and when S is greater than 2.5, T is greater than 2, P is greater than 1, and D is simultaneously satisfied, the medicine and the therapeutic scheme are feasible.
The score T output by the cycle scoring unit 410 is specifically five grades of 1 score, 2 score, 3 score, 4 score and 5 score, and the treatment cycle T1 calculated by the cycle scoring unit 410 according to the treatment scheme generated by the matching database 200 is compared with the average survival time T2 of the patient with the disease;
The scores P output by the price scoring unit 420 are specifically five grades of 1 score, 2 score, 3 score, 4 score and 5 score, and the treatment cost P1 calculated by the price scoring unit 420 according to the treatment scheme generated by the matching database 200 is compared with the per-capita bearable cost interval;
when P1 is more than 100 ten thousand, P is 1;
when 100 is more than or equal to P1 and more than 60 ten thousand, P is 2;
when the P1 is more than 20 ten thousand at 60, P is 3;
when 20 is more than or equal to P1 and more than 10 ten thousand, P is 4;
when 10 ten thousand is more than or equal to P1, P is 5.
The score D output by the curative effect scoring unit 430 is specifically five grades of 1 score, 2 score, 3 score, 4 score and 5 score, the score D output by the curative effect scoring unit 430 is specifically a comprehensive score of an average cure rate score A of the scheme and an average occurrence rate score B of side effects or sequelae of the scheme, wherein the average cure rate is a, and the average occurrence rate of the side effects or the sequelae is B;
when a is more than 80%, A is 5;
when 80% or more and a is more than 60%, A is 4;
when 60% or more and a is more than 40%, A is 3;
when 40% or more and a is more than 20%, A is 2;
when 20% is more than or equal to a, A is 1;
when B > 80%, B ═ 1;
when B is more than 60% and more than 80%, B is 2;
when B is more than 40% and more than 60%, B is 3;
when B is more than 20% and more than 40%, B is 4;
when the content is more than or equal to 10 percent, B is 5;
D=0.65A+0.35B。
when the matching database 200 generates multiple treatment protocols, the scoring module 400 needs to score each protocol separately and rank the protocols according to the score of S, T, P, D4.
The above-mentioned embodiments only express a certain implementation mode of the present invention, and the description thereof is specific and detailed, but not construed as limiting the scope of the present invention; it should be noted that, for those skilled in the art, without departing from the concept of the present invention, several variations and modifications can be made, which are within the protection scope of the present invention; therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A database-based drug disease matching method is characterized in that: the disease name of the therapeutic drug to be acquired is input, the matching database (200) matches corresponding disease data from the disease information database (300) according to the disease name, drug data corresponding to the disease data is acquired, and the matching database (200) acquires the required therapeutic drug from the drug information database (100) according to the drug data and generates a therapeutic scheme.
2. The database-based drug disease matching method according to claim 1, wherein the method is performed using the following drug disease matching database:
the drug information database (100) is used for storing all drug information data, the drug information database (100) comprises a basic drug database (110) and an extended drug database (120), the basic drug database (110) stores basic information of drugs, and the extended drug database (120) stores extended information of the drugs;
a matching database (200), wherein the matching database (200) is used for storing relevant data of the drug treatment diseases, and the matching database (200) generates treatment schemes of the drug treatment diseases according to the relevant data;
a disease information database (300), wherein the disease information database (300) is used for storing information data of all diseases, the disease information database (300) comprises a basic disease database (310) and an extended disease database (320), the basic disease database (310) stores relevant information of the diseases, and the extended disease database (320) stores relevant information of the diseases;
the matching database (200) is respectively in communication connection with the medicine information database (100) and the disease information database (300), the matching database (200) is also in communication connection with an interaction module (400), and the interaction module (400) is used for inputting and outputting data and searching and calling the data.
3. The database-based drug disease matching method of claim 2, wherein: the extended drug database (120) comprises a homogeneous drug database (121) and a homogeneous molecular compound database (122), wherein the homogeneous drug database (121) is used for storing different drug-related data of the same drug effect; the homogeneous molecular compound database (122) is used for storing molecular structure data of the medicines and correlation data of different medicines with the same type of molecular structures;
the extended disease database (320) comprises a similar disease database (321) and a concurrent disease database (322), the similar disease database (321) is used for storing different disease data of type symptoms, and the concurrent disease database (322) is used for storing concurrent disease data associated with diseases;
the matching database (200) comprises an actual matching database (210) and a theoretical matching database (220), the actual matching database (210) comprises a medicine matching database (211) and a doctor diagnosis database (212), the medicine matching database (211) stores corresponding matching data of existing known medicines and diseases, the doctor diagnosis database (212) stores collected diagnosis and treatment schemes of doctors for diseases, and the theoretical matching database (220) stores corresponding matching data of medicines and diseases in the development or experiment stage;
the disease treatment system is characterized by further comprising a scoring module (400) in communication connection, wherein the scoring module (400) comprises a period scoring unit (410), a price scoring unit (420) and a curative effect scoring unit (430), the period scoring unit (410) stores treatment period data of the drug treatment disease and outputs corresponding period scoring according to the period time of the treatment scheme output by the matching database (200); the price scoring unit (420) stores price data of the medicines and outputs corresponding price scores according to the treatment schemes output by the matching database (200), and the curative effect scoring unit (430) stores medicine curative effect data and outputs corresponding curative effect scores according to the treatment schemes output by the matching database (200);
the matching database (200) further comprises a feasibility evaluation module (230), the feasibility evaluation module (230) being configured to determine a feasibility of a drug for treating a disease, the feasibility evaluation module (230) comprising a side effect evaluation unit (231) and a sequelae evaluation unit (232).
4. The database-based drug disease matching method of claim 3, wherein: the matching database (200) confirms the disease to be analyzed according to the data stored in the disease information database (300), specifically, the disease information of the medicine to be searched is input according to the interaction module (400), the disease information can be a disease or a disease name, when the disease information is a disease, the disease name and the data related to the disease are stored as first disease data for subsequent operation after the corresponding disease name is found by comparison with the disease information database 300, and if the disease information is a disease name, the data related to the disease name and the disease are directly stored as the first disease data for subsequent operation.
5. The database-based drug disease matching method of claim 4, wherein: the subsequent operation is to match the first disease data with an expanded disease database (320) to obtain a concurrent disease corresponding to the disease, obtain the occurrence probability and symptoms of the concurrent disease, and merge the disease name and related data with the probability of more than 70% with the first disease data into second disease data when the probability of the concurrent disease is more than 70%; the matching database (200) acquires drug data from the drug information database (100) according to the first disease data and/or the second disease data, selects the first disease data as a disease to be analyzed when only the first disease data exists, and preferably selects the second disease data as a disease to be analyzed when the first disease data and the second disease data exist simultaneously.
6. The database-based drug disease matching method of claim 5, wherein: when the matching database (200) acquires the drug data from the drug information database (100), the existing known drug data related to the disease to be analyzed and the drug data related to the diagnosis and treatment plan of the disease to be analyzed are respectively acquired from the actual matching database (210) and the theoretical matching database (220) of the matching database (200) to obtain first therapeutic drug data, when the drug data related to the disease to be analyzed in the research and development or experiment stage are stored in the theoretical matching database (220), the first therapeutic drug data or the second therapeutic drug data acquired from the matching database (200) are retrieved from the drug information database (100) to obtain second therapeutic drug data, and when the drug information database (100) first retrieves the basic drug number corresponding to the first therapeutic drug data or the second therapeutic drug data from the basic drug database (110) According to the second treatment medicine data, the second treatment medicine data is preferably selected when the second treatment medicine data exists, the extended medicine data matched with the basic medicine information is obtained from the extended medicine database (120), the basic medicine data and the extended medicine data are combined into third treatment medicine data, and the matching database (200) generates a treatment scheme according to the third treatment medicine data.
7. The database-based drug disease matching method of claim 6, wherein: the method further comprises a scoring module (400) for calculating according to scores respectively output by the period scoring unit (410), the price scoring unit (420) and the curative effect scoring unit (430) to obtain corresponding medical scheme scores, wherein the score output by the period scoring unit (410) is T, the score output by the price scoring unit (420) is P, the score output by the curative effect scoring unit (430) is D, the score output by the scoring module (400) is S, S is 0.3T +0.2P +0.5D, and when S is greater than 2.5, T is greater than 2, P is greater than 1, and D is greater than 3, the therapeutic medicine and the therapeutic scheme are feasible.
8. The database-based drug disease matching method of claim 7, wherein: the scores T output by the cycle scoring unit (410) are specifically five grades of 1 score, 2 score, 3 score, 4 score and 5 score, and the treatment cycle T1 calculated by the cycle scoring unit (410) according to the treatment scheme generated by the matching database (200) is compared with the average survival time T2 of the patient with the disease;
9. The database-based drug disease matching method of claim 7, wherein: the scores P output by the price scoring unit (420) are specifically five grades of 1 score, 2 score, 3 score, 4 score and 5 score, and the treatment cost P1 calculated by the price scoring unit (420) according to the treatment scheme generated by the matching database (200) is compared with the per-person bearable cost interval;
when P1 is more than 100 ten thousand, P is 1;
when 100 is more than or equal to P1 and more than 60 ten thousand, P is 2;
when the P1 is more than 20 ten thousand at 60, P is 3;
when 20 is more than or equal to P1 and more than 10 ten thousand, P is 4;
when 10 ten thousand is more than or equal to P1, P is 5.
10. The database-based drug disease matching method of claim 7, wherein: the score D output by the curative effect scoring unit (430) is specifically five grades of 1 score, 2 score, 3 score, 4 score and 5 score, the score D output by the curative effect scoring unit (430) is specifically a comprehensive score of an average cure rate score A of the scheme and an average occurrence rate score B of side effects or sequelae of the scheme, wherein the average cure rate is a, and the average occurrence rate of the side effects or the sequelae is B;
when a is more than 80%, A is 5;
when 80% or more and a is more than 60%, A is 4;
when 60% or more and a is more than 40%, A is 3;
when 40% or more and a is more than 20%, A is 2;
when 20% is more than or equal to a, A is 1;
when B > 80%, B ═ 1;
when B is more than 60% and more than 80%, B is 2;
when B is more than 40% and more than 60%, B is 3;
when B is more than 20% and more than 40%, B is 4;
when the content is more than or equal to 10 percent, B is 5;
D=0.65A+0.35B。
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Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104200069A (en) * | 2014-08-13 | 2014-12-10 | 周晋 | Drug use recommendation system and method based on symptom analysis and machine learning |
CN104615753A (en) * | 2015-02-13 | 2015-05-13 | 杜雨阳 | Method and system of acquiring application relations between drugs and diseases |
CN107591189A (en) * | 2017-08-29 | 2018-01-16 | 科大智能科技股份有限公司 | A kind of commending system based on OTC medicines |
CN108062556A (en) * | 2017-11-10 | 2018-05-22 | 广东药科大学 | A kind of drug-disease relationship recognition methods, system and device |
CN108447536A (en) * | 2018-03-19 | 2018-08-24 | 杭州逸曜信息技术有限公司 | Medication information processing method based on genius morbi and disease degree information |
CN108959856A (en) * | 2018-06-29 | 2018-12-07 | 迈凯基因科技有限公司 | A kind of variation of disease gene and drug interpret multiple database interactive system and method |
CN109241257A (en) * | 2018-08-20 | 2019-01-18 | 重庆柚瓣家科技有限公司 | A kind of the wisdom question answering system and its method of knowledge based map |
CN110021367A (en) * | 2018-10-16 | 2019-07-16 | 中国人民解放军军事科学院军事医学研究院 | Drug integrated information database building method and system based on drug and target information |
JP2019159700A (en) * | 2018-03-12 | 2019-09-19 | 日本調剤株式会社 | Medicine information management support device |
CN110428910A (en) * | 2019-06-18 | 2019-11-08 | 浙江大学 | Clinical application indication analysis system, method, computer equipment and storage medium |
CN111048173A (en) * | 2019-12-19 | 2020-04-21 | 博奥生物集团有限公司 | Medication data pushing method and device |
CN111312359A (en) * | 2020-02-03 | 2020-06-19 | 广东省第二人民医院(广东省卫生应急医院) | Intelligent recommendation method and device for medication scheme |
-
2020
- 2020-11-16 CN CN202011278798.8A patent/CN112270968A/en active Pending
Patent Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104200069A (en) * | 2014-08-13 | 2014-12-10 | 周晋 | Drug use recommendation system and method based on symptom analysis and machine learning |
CN104615753A (en) * | 2015-02-13 | 2015-05-13 | 杜雨阳 | Method and system of acquiring application relations between drugs and diseases |
CN107591189A (en) * | 2017-08-29 | 2018-01-16 | 科大智能科技股份有限公司 | A kind of commending system based on OTC medicines |
CN108062556A (en) * | 2017-11-10 | 2018-05-22 | 广东药科大学 | A kind of drug-disease relationship recognition methods, system and device |
JP2019159700A (en) * | 2018-03-12 | 2019-09-19 | 日本調剤株式会社 | Medicine information management support device |
CN108447536A (en) * | 2018-03-19 | 2018-08-24 | 杭州逸曜信息技术有限公司 | Medication information processing method based on genius morbi and disease degree information |
CN108959856A (en) * | 2018-06-29 | 2018-12-07 | 迈凯基因科技有限公司 | A kind of variation of disease gene and drug interpret multiple database interactive system and method |
CN109241257A (en) * | 2018-08-20 | 2019-01-18 | 重庆柚瓣家科技有限公司 | A kind of the wisdom question answering system and its method of knowledge based map |
CN110021367A (en) * | 2018-10-16 | 2019-07-16 | 中国人民解放军军事科学院军事医学研究院 | Drug integrated information database building method and system based on drug and target information |
CN110428910A (en) * | 2019-06-18 | 2019-11-08 | 浙江大学 | Clinical application indication analysis system, method, computer equipment and storage medium |
CN111048173A (en) * | 2019-12-19 | 2020-04-21 | 博奥生物集团有限公司 | Medication data pushing method and device |
CN111312359A (en) * | 2020-02-03 | 2020-06-19 | 广东省第二人民医院(广东省卫生应急医院) | Intelligent recommendation method and device for medication scheme |
Non-Patent Citations (1)
Title |
---|
时村聪代: "华盛顿大学开发使基因靶向药物与疾病相关基因匹配的数据库", 生物产业技术, no. 003, pages 53 - 54 * |
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