CN115831370A - Kidney disease risk prediction system for multi-step detection and synchronous integration analysis - Google Patents
Kidney disease risk prediction system for multi-step detection and synchronous integration analysis Download PDFInfo
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Abstract
The invention relates to the technical field of data processing, in particular to a kidney disease risk prediction system for multi-step inspection synchronous integration analysis, which comprises: the control terminal is a main control end of the system and is used for sending out an execution command; the database is used for storing the data acquired by the acquisition module; the acquisition module is used for acquiring data information of the visiting user; the receiving module is used for receiving the data information of the treatment user acquired by the acquisition module and processed by the subordinate sub-modules of the acquisition module; the method and the system can acquire data used for kidney disease risk prediction from different sources, and can further select the application proportion of the acquired data according to the self condition of the visiting user after the data are acquired, so that the data used for predicting the kidney disease risk during the operation of the system is more simplified, and the kidney disease risk prediction result of the system for the visiting user is more accurate.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a kidney disease risk prediction system based on multi-step detection and synchronous integration analysis.
Background
The main clinical manifestations of kidney disease are proteinuria, hematuria, edema, hypertension, renal insufficiency, etc. Over the years, clinicians comprehensively analyze the disease history, physical examination and laboratory test of patients to summarize several clinical symptoms of glomerular diseases, such as acute nephritis syndrome, nephrotic syndrome, acute nephritis syndrome, chronic nephritis syndrome, etc., which are taken as the basis of clinical diagnosis and guide treatment, and play a positive role in diagnosing and treating renal diseases before the development of renal biopsy technology. The limitations of the diagnosis of clinical syndromes are evident, which must be combined with the histopathological diagnosis of the kidney in order to make possible the analysis of the pathophysiological mechanisms and etiologies of the disease and thus to guide the diagnosis and treatment.
Therefore, a technical means capable of predicting the kidney diseases does not exist at present, so that the kidney conditions of the patient cannot be captured quickly, the treatment of the patient is further influenced, and the optimal treatment time of the patient is easy to miss.
Disclosure of Invention
The invention provides a kidney disease risk prediction system for multi-step test synchronous integration analysis, which solves the technical problems in the background technology.
Technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme:
a multi-step assay synchronized integration analysis renal disease risk prediction system comprising:
the control terminal is a main control end of the system and is used for sending out an execution command;
the database is used for storing the data acquired by the acquisition module;
the acquisition module is used for acquiring data information of the visiting user;
the receiving module is used for receiving the data information of the treatment user acquired by the acquisition module and processed by the subordinate sub-modules of the acquisition module;
the cloud interaction platform is used for uploading and recording the kidney disease risk related data information;
the searching module is used for searching the same items of the data information of the patient-seeing user received by the receiving module and the data information related to the renal disease risk recorded in the cloud interactive platform;
the evaluation module is used for obtaining the same items searched by the search module and evaluating the current renal disease risk of the patient with reference to the same items;
and the evaluation module synchronously sends the operation result data to the database and stores the operation result data in the database.
Furthermore, when the acquisition module acquires the data information of the patient-seeing user, the database synchronously runs the newly-built folder to store the data information of the patient-seeing user acquired by the acquisition module;
the database stores the data information of the treatment user according to the receiving time sequence of the data information of the treatment user.
Furthermore, the acquisition module is provided with sub-modules at a lower level, including:
the setting unit is used for setting a source target of the acquisition module when acquiring the data information of the visiting user;
the selection unit is used for selecting the data content of the appointed data acquisition time period when the acquisition module acquires the data information of the visiting patient;
wherein, the data information collection source target set by the setting unit comprises: historical medical examination data of the medical treatment user, daily diet and work and rest data of the medical treatment user, and historical medical examination data of the medical treatment user's immediate relatives; when the setting unit sets the data information acquisition source targets, the selection source targets and the number of the source targets are set by a system end user independently, and the designated data acquisition time period applied by the selection unit when selecting the data content is manually set by the system end user during system initialization operation.
Furthermore, the acquisition module is provided with sub-modules at a lower level, and further comprises:
the proportion application unit is used for setting the application proportion of the acquisition module for acquiring the data information of the visiting user;
the specific gravity application unit sets the application specific gravity of the data information of the visiting user according to manual setting of a system end user, the application specific gravity is initially set to be 1/3 in a default mode, when the specific gravity application unit operates, whether the visiting user has a kidney problem is analyzed synchronously according to a data information acquisition source target under the state that the application specific gravity is 1/3, when the analysis result is yes, the visiting user daily diet and work and rest data, the visiting user direct family relatives historical physical examination data and the visiting user historical visiting data in the data information of the visiting user, and the application specific gravity of the visiting user historical physical examination data is 1/3, and when the analysis result is not, the visiting user historical visiting data, the visiting user historical physical examination data, the visiting user daily diet and work and rest data and the visiting user direct family relatives historical physical examination data in the data information of the visiting user are 1/3.
Furthermore, the medical staff or the doctor-seeing user accesses the cloud interactive platform through the wireless network, the medical staff and the doctor-seeing user upload the kidney disease risk related data information in real time after accessing the cloud interactive platform and uploading the kidney disease risk related data information in the cloud interactive platform, the doctor-seeing user uploads the kidney disease risk related data information and then places the kidney disease risk related data information in the cloud interactive platform, the medical staff reads the placed kidney disease risk related data information after uploading the kidney disease risk related data information in the cloud interactive platform, the kidney disease risk related data information uploaded by the medical staff is recorded in the cloud interactive platform after being read;
wherein the kidney disease risk related data information comprises: text data, medical examination, laboratory numerical data, and image data.
Furthermore, a sub-module is arranged at the lower stage of the cloud interaction platform, and comprises:
the monitoring unit is used for monitoring the internal memory occupied by the kidney disease risk related data information recorded in real time in the cloud interactive platform;
the reduction unit is used for deleting the data information related to the renal disease risk recorded in the cloud interactive platform;
the monitoring unit operates to calculate the memory occupied percentage of the kidney disease risk related data information in real time, the reduction unit is triggered to operate when the percentage reaches 98%, the reduction unit operates to delete the recorded kidney disease risk related data information, and the operation is stopped when the percentage is reduced to 90% or below.
Furthermore, when the reduction unit operates, activity analysis is performed on the kidney disease risk related data information recorded in the cloud interactive platform in real time, and when the reduction unit deletes the kidney disease risk related data information recorded in the cloud interactive platform, the kidney disease risk related data information with low activity is a priority deletion target.
Furthermore, the search module and the evaluation module are provided with sub-modules at a lower level, including:
the identification unit is used for identifying the data information acquisition source target of the visiting user corresponding to the same item;
the defining unit is used for defining the score of each visiting user data information source target;
when the evaluation module runs, the score of each diagnosis user data information source target defined by the definition unit is used for summing the scores of the obtained same items, and the larger the summed score is, the higher the current renal disease risk of the diagnosis user is.
Further, the definition unit defines the score of the destination of the data information source of the visiting user with the existing kidney problem as follows: the scores of the daily diet and rest data of the patient, the historical physical examination data of the immediate relatives of the patient are both 0.4, and the scores of the historical physical examination data of the patient and the historical physical examination data of the patient are both 1; the defined score for the visit user data information source objective without kidney problems is: the scores of the historical physical examination data of the visiting user and the historical physical examination data of the visiting user are both 0.4, and the scores of the daily diet and work and rest data of the visiting user and the historical physical examination data of the immediate relatives of the visiting user are both 1.
Furthermore, the control terminal is electrically connected with a database and a collection module through a medium, the lower stage of the collection module is electrically connected with a setting unit, a selecting unit and a proportion application unit through the medium, the collection module is electrically connected with a receiving module and a cloud interactive platform through the medium, the lower stage of the cloud interactive platform is electrically connected with a monitoring unit and a reduction unit through the medium, the cloud interactive platform is electrically connected with a search module and an evaluation module through the medium, and the lower stages of the search module and the evaluation module are electrically connected with a recognition unit and a definition unit through the medium.
Advantageous effects
Compared with the known public technology, the technical scheme provided by the invention has the following beneficial effects:
the invention provides a kidney disease risk prediction system with multi-step detection and synchronous integration analysis, which can collect data for kidney disease risk prediction from different sources in the operation process, and can further select the application proportion of the collected data according to the self condition of a patient after the data are collected, so that the data used for predicting the kidney disease risk during the operation of the system is more simplified, and the kidney disease risk prediction result of the patient is more accurate.
In the running process of the system, the data for evaluating the renal disease risk of the patient is recorded and stored in a cloud sharing mode, so that the data for evaluating the renal disease risk of the patient can be updated and optimized in real time, and the system can predict the renal disease risk of the patient more comprehensively and effectively.
When the system is in operation, evaluation is carried out in a score accumulation mode at the stage of carrying out renal disease risk evaluation on the visiting user, so that more visual numerical data reading is provided for the system end user, and the visiting user can quickly carry out relevant diagnosis such as renal disease prediction.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
FIG. 1 is a schematic diagram of a multi-step test-based kidney disease risk prediction system with simultaneous integration analysis;
the reference numerals in the drawings denote: 1. a control terminal; 2. a database; 3. an acquisition module; 31. a setting unit; 32. a selection unit; 33. a specific gravity application unit; 4. a receiving module; 5. a cloud interaction platform; 51. a monitoring unit; 52. a subtraction unit; 6. a search module; 7. an evaluation module; 71. an identification unit; 72. a unit is defined.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The present invention will be further described with reference to the following examples.
Example 1
The present embodiment of a kidney disease risk prediction system with multi-step test and simultaneous integration analysis, as shown in fig. 1, includes:
the control terminal 1 is a main control end of the system and is used for sending out an execution command;
the database 2 is used for storing the data acquired by the acquisition module 3;
the acquisition module 3 is used for acquiring data information of the visiting user;
the receiving module 4 is used for receiving the data information of the treatment user, which is acquired by the acquisition module 3 and processed by the subordinate sub-modules;
the cloud interaction platform 5 is used for uploading and recording the kidney disease risk related data information;
the searching module 6 is used for searching the same items of the data information of the visiting patient received by the receiving module 4 and the data information related to the renal disease risk recorded in the cloud interactive platform 5;
the evaluation module 7 is used for obtaining the same items searched by the search module 6 and evaluating the current renal disease risk of the patient with reference to the same items;
the evaluation module 7 synchronously sends the operation result data to the database 2 and stores the operation result data in the database 2.
In this embodiment, the control terminal 1 controls the acquisition module 3 to acquire data information of the visiting user, and stores the data acquired by the acquisition module 3 in real time through the database 2, the receiving module 4 operates the receiving module 3 to acquire the data information of the visiting user processed by the sub-module of the receiving module 3, and then the data information related to kidney disease risk is uploaded and recorded by the cloud interactive platform 5, the synchronous search module 6 searches the same items of the data information of the visiting user received by the receiving module 4 and the data information related to kidney disease risk recorded in the cloud interactive platform 5, and finally the evaluation module 7 operates the same items searched by the acquisition search module 6 to evaluate the current kidney disease risk of the visiting user with reference to the same items.
Example 2
In the specific implementation, on the basis of embodiment 1, this embodiment further specifically describes the kidney disease risk prediction system of the multi-step testing synchronous integration analysis in embodiment 1 with reference to fig. 1:
when the acquisition module 3 acquires the data information of the treatment user, the database 2 synchronously operates the newly-built folder to store the data information of the treatment user acquired by the acquisition module 3;
the database 2 stores the data information of the visiting user according to the receiving time sequence of the data information of the visiting user.
As shown in fig. 1, the lower stage of the collection module 3 is provided with sub-modules, including:
the setting unit 31 is used for setting a source target of the acquisition module 3 when acquiring the data information of the visiting user;
the selection unit 32 is used for selecting the data content of the appointed data acquisition time period when the acquisition module 3 acquires the data information of the visiting patient;
the data information acquisition source target set by the setting unit 31 includes: historical diagnosis data of the patient, historical physical examination data of the patient, daily diet and work and rest data of the patient, and historical physical examination data of the immediate relatives of the patient; when setting the data information acquisition source targets, the setting unit 31 sets the selection source targets and the number of the source targets by the user at the system end, and the designated data acquisition time interval applied when the selection unit 32 selects the data content is manually set by the user at the system end during the system initialization operation.
As shown in fig. 1, the lower stage of the collecting module 3 is provided with sub-modules, and further comprises:
the proportion application unit 33 is used for setting the application proportion of the data information of the patient acquired by the acquisition module 3;
the specific gravity application unit 33 sets the application specific gravity of the data information of the visiting user according to the manual setting of a system end user, the initial default of the application specific gravity is set to 1/3, when the specific gravity application unit 33 operates, whether the visiting user has a kidney problem is analyzed synchronously according to the data information acquisition source target under the state that the application specific gravity is 1/3, if the analysis result is yes, the daily diet and work and rest data of the visiting user, the historical physical examination data of the direct family relatives of the visiting user, and the application specific gravity of the historical physical examination data of the visiting user in the data information of the visiting user are 1/3, and if the analysis result is not, the historical visiting user visiting data, the historical physical examination data of the visiting user, the daily diet and work and rest data of the visiting user, and the application specific gravity of the direct family relatives of the visiting user are 1/3.
Through the setting of the subordinate sub-modules of the acquisition module 3, the effective management is effectively brought to the system operation when the data information of the visiting user is acquired, the total amount of the acquired data is reduced by further adopting a mode of setting the proportion of the acquired data, and the acquired data for the system operation is ensured to be more simplified.
Example 3
In the specific implementation, on the basis of embodiment 1, this embodiment further specifically describes the kidney disease risk prediction system of the multi-step testing synchronous integration analysis in embodiment 1 with reference to fig. 1:
medical personnel or a doctor visit the cloud interactive platform 5 through a wireless network, the medical personnel and the doctor visit the cloud interactive platform 5 and upload the kidney disease risk related data information in real time after visiting the cloud interactive platform 5 and uploading in the cloud interactive platform 5, the doctor uploads the kidney disease risk related data information and then places the kidney disease risk related data information in the cloud interactive platform 5, the medical personnel reads the placed kidney disease risk related data information after uploading in the cloud interactive platform 5, and records or deletes the kidney disease risk related data information after reading, and the kidney disease risk related data information uploaded by the medical personnel is recorded in the cloud interactive platform 5;
wherein the kidney disease risk related data information comprises: text data, medical examination, laboratory numerical data, and image data.
As shown in fig. 1, sub-modules are arranged at the lower stage of the cloud interactive platform 5, and include:
the monitoring unit 51 is configured to monitor that the data information related to the kidney disease risk recorded in the cloud interactive platform 5 in real time occupies a memory;
the reducing unit 52 is configured to delete the data information related to renal disease risk recorded in the cloud interactive platform 5;
the monitoring unit 51 operates to calculate the memory occupied percentage of the kidney disease risk related data information in real time, the reducing unit 52 is triggered to operate when the percentage reaches 98%, the reducing unit 52 operates to delete the recorded kidney disease risk related data information, and the operation is stopped when the percentage is reduced to 90% or below.
Through the setting of the subordinate sub-modules of the cloud interactive platform 5, a certain degree of management effect is brought to the cloud interactive platform 5, and the full load condition of the cloud interactive platform is avoided.
As shown in fig. 1, when the reducing unit 52 operates, activity analysis is performed on the kidney disease risk related data information recorded in the cloud interactive platform 5 in real time, and when the reducing unit 52 deletes the kidney disease risk related data information recorded in the cloud interactive platform 5, the kidney disease risk related data information with low activity is a priority deletion target.
As shown in fig. 1, the search module 6 and the evaluation module 7 are provided with sub-modules at the lower level, including:
the identification unit 71 is used for identifying the data information acquisition source target of the visiting user corresponding to the same item;
a defining unit 72, configured to define a score of each data information source target of the visiting user;
when the evaluation module 7 operates, the score of the data information source target of each visiting user defined by the definition unit 72 is used for summing the scores of the obtained same items, and the larger the summed score is, the higher the current risk of renal diseases of the visiting user is.
Through the arrangement of the identification unit 71 and the definition unit 72, a specific evaluation basis is brought to the kidney disease risk evaluation of the visiting user for the system operation.
As shown in fig. 1, the definition unit 72 defines the score of the data information source target of the visiting user with the existing kidney problem as follows: the scores of the daily diet and rest data of the patient, the historical physical examination data of the immediate relatives of the patient are both 0.4, and the scores of the historical physical examination data of the patient and the historical physical examination data of the patient are both 1; the defined score for the visit user data information source objective without kidney problems is: the scores of the historical physical examination data of the visiting user and the historical physical examination data of the visiting user are both 0.4, and the scores of the daily diet and work and rest data of the visiting user and the historical physical examination data of the immediate relatives of the visiting user are both 1.
As shown in fig. 1, the control terminal 1 is electrically connected to the database 2 and the collection module 3 through a medium, the lower stage of the collection module 3 is electrically connected to the setting unit 31, the selection unit 32 and the specific gravity application unit 33 through a medium, the collection module 3 is electrically connected to the receiving module 4 and the cloud interactive platform 5 through a medium, the lower stage of the cloud interactive platform 5 is electrically connected to the monitoring unit 51 and the reduction unit 52 through a medium, the cloud interactive platform 5 is electrically connected to the search module 6 and the evaluation module 7 through a medium, and the lower stages of the search module 6 and the evaluation module 7 are electrically connected to the identification unit 71 and the definition unit 72 through a medium.
In summary, in the above embodiment, the system can acquire data for kidney disease risk prediction from different sources during the operation process, and after the data is acquired, the application proportion of the acquired data can be further selected according to the self condition of the user, so that the data used for kidney disease risk prediction during the operation of the system is ensured to be more simplified, and the kidney disease risk prediction result of the user is more accurate; meanwhile, the system records and stores the data for evaluating the renal disease risk of the patient in a cloud sharing mode, so that the data for evaluating the renal disease risk of the patient can be updated and optimized in real time, and the system can predict the renal disease risk of the patient more comprehensively and effectively; in addition, when the system is in operation, evaluation is carried out in a score accumulation mode at the stage of carrying out renal disease risk evaluation on the visiting user, so that more visual numerical data reading is provided for the system end user, and the visiting user can quickly carry out relevant diagnosis such as renal disease prediction.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (10)
1. A multi-step test synchronized integration analysis renal disease risk prediction system, comprising:
the control terminal (1) is a main control end of the system and is used for sending out an execution command;
the database (2) is used for storing the data acquired by the acquisition module (3);
the acquisition module (3) is used for acquiring data information of the treatment user;
the receiving module (4) is used for receiving the data information of the visiting user, which is acquired by the acquisition module (3) and processed by the subordinate sub-modules of the acquisition module;
the cloud interaction platform (5) is used for uploading and recording the kidney disease risk related data information;
the searching module (6) is used for searching the same items of the data information of the visiting patient received by the receiving module (4) and the data information related to the renal disease risk recorded in the cloud interactive platform (5);
the evaluation module (7) is used for acquiring the same items searched by the search module (6) and evaluating the current renal disease risk of the visiting user by referring to the same items;
the evaluation module (7) synchronously sends the operation result data to the database (2) and stores the operation result data in the database (2).
2. The kidney disease risk prediction system based on multi-step examination and synchronous integration analysis as claimed in claim 1, wherein when the acquisition module (3) acquires the data information of the visiting patient, the database (2) synchronously runs the newly-built folder to store the data information of the visiting patient acquired by the acquisition module (3);
the database (2) stores the data information of the treatment user according to the receiving time sequence of the data information of the treatment user.
3. The system for predicting renal disease risk by multi-step test-synchronized integration analysis according to claim 1, wherein the acquisition module (3) is provided with sub-modules at the lower stage, comprising:
the setting unit (31) is used for setting a source target of the acquisition module (3) when acquiring the data information of the visiting user;
the selection unit (32) is used for selecting the data content of the appointed data acquisition time period when the acquisition module (3) acquires the data information of the visiting patient;
wherein, the data information acquisition source target set by the setting unit (31) comprises: historical medical examination data of the medical treatment user, daily diet and work and rest data of the medical treatment user, and historical medical examination data of the medical treatment user's immediate relatives; when setting data information acquisition source targets, the setting unit (31) sets the number of selected source targets and source targets by a system end user, and the designated data acquisition time period applied when the selection unit (32) selects data contents is manually set by the system end user during system initialization operation.
4. The multi-step examination-synchronized integration-analysis renal disease risk prediction system according to claim 1, wherein the acquisition module (3) is provided with sub-modules at the lower stage, further comprising:
the proportion application unit (33) is used for setting the application proportion of the acquisition module (3) for acquiring the data information of the treatment user;
the specific gravity application unit (33) sets the application specific gravity of the data information of the visiting user according to manual setting of a system end user, the application specific gravity is initially set to be 1/3 by default, when the specific gravity application unit (33) operates, the application specific gravity is in a state of 1/3, whether the visiting user has a kidney problem is analyzed synchronously according to a data information acquisition source target, if the analysis result is yes, the application specific gravity of the historical physical examination data of the visiting user is 1/3, and if the analysis result is no, the historical visiting user visiting data, the historical physical examination data of the visiting user, the daily diet and work data of the visiting user and the historical physical examination data of the visiting user in the data information of the visiting user are 1/3.
5. The kidney disease risk prediction system based on multi-step inspection and synchronous integration analysis as claimed in claim 1, wherein a medical worker or a doctor visits the cloud interactive platform (5) through a wireless network, the medical worker and the doctor upload kidney disease risk related data information in real time after visiting the cloud interactive platform (5) and logging on the cloud interactive platform (5), the doctor uploads the kidney disease risk related data information, the kidney disease risk related data information is placed on the cloud interactive platform (5), the medical worker reads the placed kidney disease risk related data information after logging on the cloud interactive platform (5), the kidney disease risk related data information is recorded or deleted after reading, and the kidney disease risk related data information uploaded by the medical worker is recorded on the cloud interactive platform (5);
wherein the kidney disease risk related data information comprises: text data, medical examination, laboratory numerical data, and image data.
6. The kidney disease risk prediction system based on multi-step examination and synchronous integration analysis as claimed in claim 1, wherein the cloud interactive platform (5) is provided with sub-modules at the lower stage, and comprises:
the monitoring unit (51) is used for monitoring the internal memory occupied by the kidney disease risk related data information recorded in the cloud interactive platform (5) in real time;
the reduction unit (52) is used for deleting the data information related to the renal disease risk recorded in the cloud interactive platform (5);
the monitoring unit (51) operates to calculate the memory occupied percentage of the kidney disease risk related data information in real time, the reducing unit (52) is triggered to operate when the percentage reaches 98%, the reducing unit (52) operates to delete the recorded kidney disease risk related data information, and the operation is stopped when the percentage is reduced to 90% or below.
7. The kidney disease risk prediction system based on multi-step examination and synchronous integration analysis as claimed in claim 6, wherein when the reduction unit (52) operates, activity analysis is performed on the kidney disease risk related data information recorded in the cloud interactive platform (5) in real time, and when the reduction unit (52) deletes the kidney disease risk related data information recorded in the cloud interactive platform (5), the kidney disease risk related data information with low activity is a priority deletion target.
8. The system for predicting renal disease risk based on multi-step examination-synchronized integration analysis according to claim 1, wherein the search module (6) and the evaluation module (7) are provided with sub-modules at a lower level, comprising:
the identification unit (71) is used for identifying the data information acquisition source target of the visiting user corresponding to the same item;
a definition unit (72) for defining the score of each visit user data information source target;
when the evaluation module (7) runs, the score of each data information source target of the visiting user defined by the definition unit (72) is used for carrying out score summation on the obtained same items, wherein the larger the total score is, the higher the current renal disease risk of the visiting user is.
9. The system according to claim 8, wherein the definition unit (72) defines the scores of the data information source targets of the visiting users with existing kidney problems as follows: the scores of the daily diet and rest data of the patient, the historical physical examination data of the immediate relatives of the patient are both 0.4, and the scores of the historical physical examination data of the patient and the historical physical examination data of the patient are both 1; the defined score for the visit user data information source objective without kidney problems is: the scores of the historical physical examination data of the visiting user and the historical physical examination data of the visiting user are both 0.4, and the scores of the daily diet and work and rest data of the visiting user and the historical physical examination data of the immediate relatives of the visiting user are both 1.
10. The kidney disease risk prediction system based on multi-step examination, synchronous integration and analysis according to claim 1, wherein the control terminal (1) is electrically connected with the database (2) and the collection module (3) through a medium, the collection module (3) is electrically connected with the setting unit (31), the selection unit (32) and the proportion application unit (33) through a medium, the collection module (3) is electrically connected with the receiving module (4) and the cloud interaction platform (5) through a medium, the cloud interaction platform (5) is electrically connected with the monitoring unit (51) and the reduction unit (52) through a medium, the cloud interaction platform (5) is electrically connected with the search module (6) and the evaluation module (7) through a medium, and the search module (6) and the evaluation module (7) are electrically connected with the identification unit (71) and the definition unit (72) through a medium.
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