CN111863283A - Medical health big data platform - Google Patents
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- CN111863283A CN111863283A CN202010691177.6A CN202010691177A CN111863283A CN 111863283 A CN111863283 A CN 111863283A CN 202010691177 A CN202010691177 A CN 202010691177A CN 111863283 A CN111863283 A CN 111863283A
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Abstract
The invention relates to the technical field of medical big data, and provides a medical health big data platform which comprises a server, a user side and a doctor side, wherein the server is used for analyzing basic illness state information provided by the user side by combining data of a medical information sharing platform and utilizing an application algorithm of big data to generate medical advice information which accords with patients at the user side; the user side is in communication connection with the server and is used for receiving the basic information of the illness state input by the patient and receiving and displaying the medical advice information generated by the server; the doctor end is in communication connection with the server and used for receiving and displaying the medical suggestion information generated by the server, so that the combination of big data and medical health is fully realized, the advantage of big data analysis is fully applied in the field of medical health, and powerful help is provided for medical health.
Description
Technical Field
The invention belongs to the technical field of medical big data, and particularly relates to a medical health big data platform.
Background
Big data refers to a complex set of data that is difficult to store, manage, and process efficiently and economically by traditional data management systems. Big data is generally measured in PB units and contains structured, semi-structured, unstructured data, which presents a significant challenge to data collection, transportation, encryption, storage, analysis, and visualization. Compared to the conventional data, the big data contains 5V characteristics: volume (large data size), Variety (data types are numerous), Velocity (data is generated very fast), Veracity (analysis results depend on data accuracy), Value (big data generally contains very important Value). Big data brings challenges to storing, managing, and processing data, and also brings opportunities to explore new values in data. Various industries have utilized big data improvement businesses such as financial, retail, life sciences, environmental research.
The healthcare industry is currently facing significant challenges, the most significant of which include: sharply increased medical expenditures, chronic disease problems with aging population, shortage of medical personnel, medical fraud, and the like. At present, the application range of big data is narrow, and the application advantage of the big data is not fully exerted.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a medical health big data platform, and aims to solve the problems that the application range of big data is narrow and the application advantages of the big data are not fully exerted in the prior art.
The technical scheme provided by the invention is as follows: a medical health big data platform comprises a server, a user side and a doctor side, wherein:
the server is used for analyzing the basic illness state information provided by the user terminal by combining the data of the medical information sharing platform and utilizing an application algorithm of big data to generate medical advice information which accords with the patient at the user terminal, wherein the medical advice information comprises illness state information, hospitalizing information, treatment scheme information, medication reminding information and doctor advice information;
the user side is in communication connection with the server and is used for receiving the basic information of the illness state input by the patient and receiving and displaying the medical advice information generated by the server;
The doctor end is in communication connection with the server and used for receiving and displaying the medical suggestion information generated by the server.
As an improved scheme, the medical information sharing platform comprises an electronic case system platform, a laboratory experiment data system platform, a medical image archiving system platform and a clinical decision system platform;
the electronic case history system platform is used for storing the electronic case history corresponding to the patient who has a doctor in the past;
the laboratory experiment data system platform is used for storing data related to laboratory medical experiment results;
the medical image archiving system platform is used for storing medical image materials corresponding to patients who have a medical visit in the past;
the clinical decision system platform is used for storing clinical decision content.
As an improved solution, the server includes:
the disease condition information analysis module is used for generating disease condition information by combining the medical information sharing platform and utilizing an application algorithm of big data for the basic disease condition information provided by the user side;
the medical information analysis module is used for analyzing the illness state information acquired by the illness state information analysis module by combining with the medical information sharing platform to generate medical information corresponding to the user-side patient, and the medical information comprises medical time, medical doctor information and medical care items;
The treatment scheme information analysis module is used for generating treatment scheme information of the patient by combining the clinical decision system platform and the disease condition information analysis module;
the medicine taking reminding information analysis module is used for generating medicine taking information of the patient by combining the illness state information and the treatment scheme information;
and the doctor suggestion information analysis module is used for generating doctor suggestion information according to the illness state information and the treatment scheme information.
As an improved scheme, the disease condition information analysis module specifically includes:
the patient basic information acquisition module is used for establishing communication connection with a user terminal and acquiring the patient basic information input on the user terminal, wherein the patient basic information comprises patient identity information and illness state description information, and the illness state description information comprises illness state content, morbidity time and medication situation;
the patient basic information judging module is connected with the patient basic information acquiring module and the electronic case system platform and used for judging whether the patient has medical diagnosis history or not from the electronic case system platform according to the patient basic information acquired by the patient basic information acquiring module;
the first judgment processing module is connected with the patient basic information judgment module, the clinical decision system platform and the laboratory experiment data system platform and is used for generating patient condition information according to the clinical decision system platform, the laboratory experiment data system platform and the learning data of the previous big data learning algorithm when the patient basic information judgment module judges that the patient corresponding to the user side has no medical diagnosis history;
And the second judgment processing module is connected with the patient basic information judgment module, the electronic case system platform and the medical image archiving system platform and is used for calling the electronic case matched with the patient identity information in the electronic case system platform, calling the medical image matched with the patient identity information in the medical image archiving system platform and analyzing the called electronic case and medical image to generate new patient condition information when the patient basic information judgment module judges that the patient corresponding to the user side has medical diagnosis history.
As an improved scheme, the medical information analysis module specifically includes:
the hospitalizing time generation module is connected with the disease condition information analysis module and the clinical decision system platform and used for obtaining disease condition information according to the disease condition information analysis module and generating hospitalizing time according to the clinical decision system platform;
the medical doctor information acquisition module is connected with the disease condition information analysis module and is used for acquiring corresponding information of a medical doctor room and the medical doctor according to the medical time generated by the medical time generation module and the disease condition information acquired by the disease condition information analysis module;
And the medical care item generating module is connected with the disease condition information analyzing module and used for generating medical care item information according to the disease condition information acquired by the disease condition information analyzing module, wherein the medical care item information comprises fasting or not information and family accompanying information.
As an improved scheme, the basic information of the disease condition comprises disease condition information, electrocardiogram data, blood oxygen concentration, respiration, blood pressure, body temperature, pulse and exercise amount.
As an improved scheme, the electrocardio data, the blood oxygen concentration, the respiration, the blood pressure, the body temperature, the pulse and the exercise amount are obtained through electronic equipment which is connected with the user side in a matching mode.
As an improved scheme, the big data application algorithm comprises an association rule learning algorithm, a classification algorithm, a cluster analysis algorithm, a data fusion algorithm, a machine learning algorithm, a natural language processing algorithm, a regression algorithm, a signal processing algorithm, a simulation algorithm and a visualization algorithm.
In the embodiment of the invention, the medical health big data platform comprises a server, a user side and a doctor side, wherein: the server is used for analyzing the basic illness state information provided by the user side by combining the data of the medical information sharing platform and utilizing an application algorithm of big data to generate medical advice information which accords with patients at the user side; the user side is in communication connection with the server and is used for receiving the basic information of the illness state input by the patient and receiving and displaying the medical advice information generated by the server; the doctor end is in communication connection with the server and used for receiving and displaying the medical suggestion information generated by the server, so that the combination of big data and medical health is fully realized, the advantage of big data analysis is fully applied in the field of medical health, and powerful help is provided for medical health.
Drawings
In order to more clearly illustrate the detailed description of the invention or the technical solutions in the prior art, the drawings that are needed in the detailed description of the invention or the prior art will be briefly described below. Throughout the drawings, like elements or portions are generally identified by like reference numerals. In the drawings, elements or portions are not necessarily drawn to scale.
FIG. 1 is a schematic structural diagram of a medical health big data platform provided by the present invention;
FIG. 2 is a block diagram of a server provided by the present invention;
FIG. 3 is a block diagram of a disease information analysis module according to the present invention;
fig. 4 is a block diagram of the medical information analysis module provided in the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The following examples are merely for illustrating the technical solutions of the present invention more clearly, and therefore are only examples, and the protection scope of the present invention is not limited thereby.
Fig. 1 shows a schematic structural diagram of a medical health big data platform provided by the present invention, and for convenience of explanation, only the parts related to the embodiment of the present invention are shown in the diagram.
The medical health big data platform comprises a server, a user side and a doctor side, wherein:
the server is used for analyzing basic illness state information provided by the user terminal by combining data of the medical information sharing platform and utilizing an application algorithm of big data to generate medical advice information which accords with patients at the user terminal, wherein the medical advice information comprises illness state information, hospitalization information, treatment scheme information, medication reminding information and doctor advice information, and the basic illness state information comprises illness state information, electrocardiogram data, blood oxygen concentration, respiration, blood pressure, body temperature, pulse and exercise amount;
the user side is in communication connection with the server and is used for receiving the basic information of the illness state input by the patient and receiving and displaying the medical advice information generated by the server;
the doctor end is in communication connection with the server and used for receiving and displaying the medical suggestion information generated by the server.
In this embodiment, although the server, the user side, and the doctor side are all common terminal devices or hosts, the core idea of the program algorithm and the design concept running inside the server is to provide a specific implementation for the combination of big data analysis and medical health, and the specific implementation is given as follows:
The medical information sharing platform comprises an electronic case system platform, a laboratory experiment data system platform, a medical image archiving system platform and a clinical decision system platform;
the electronic case history system platform is used for storing the electronic case history corresponding to the patient who has a doctor in the past;
the laboratory experiment data system platform is used for storing data related to laboratory medical experiment results;
the medical image archiving system platform is used for storing medical image materials corresponding to patients who have a medical visit in the past;
the clinical decision system platform is used for storing clinical decision content.
The system platforms provide data assistance for the medical health big data and serve as a basis for follow-up big data analysis. In the embodiment of the present invention, as shown in fig. 2, the server includes:
the disease condition information analysis module is used for generating disease condition information by combining the medical information sharing platform and utilizing an application algorithm of big data for the basic disease condition information provided by the user side;
the medical information analysis module is used for analyzing the illness state information acquired by the illness state information analysis module by combining with the medical information sharing platform to generate medical information corresponding to the user-side patient, and the medical information comprises medical time, medical doctor information and medical care items;
The treatment scheme information analysis module is used for generating treatment scheme information of the patient by combining the clinical decision system platform and the disease condition information analysis module;
the medicine taking reminding information analysis module is used for generating medicine taking information of the patient by combining the illness state information and the treatment scheme information;
and the doctor suggestion information analysis module is used for generating doctor suggestion information according to the illness state information and the treatment scheme information.
In this embodiment, the server is the core of the medical health big data platform, and it runs the main big data running algorithm, for example: an association rule learning algorithm, a classification algorithm, a cluster analysis algorithm, a data fusion algorithm, a machine learning algorithm, a natural language processing algorithm, a regression algorithm, a signal processing algorithm, a simulation algorithm and a visualization algorithm; these algorithms enable the analysis of medical health big data, where:
association rule learning is to mine interesting relationships between variables, such as finding goods often bought together in retail sales for promotion; the classification is to effectively identify new data by training an existing data set, such as predicting the purchasing behavior of a user; the cluster analysis is to divide the whole data set into a plurality of small-scale data sets according to the data similarity degree; data fusion is the integrated analysis of information from multiple data sources to generate new, more accurate, continuous and valuable information; machine learning is a general term for a class of algorithms, and concerns about designing algorithms to automatically recognize complex patterns in data; natural language processing concerns the association of computers with natural language to help computers recognize human language; regression is a set of statistical algorithms used to judge the relationship between dependent variables and independent variables to aid in prediction. Signal processing is a set of techniques used to identify, analyze, and process signals; emulation is a technique that simulates the behavior of a complex system, often used for prediction; visualization is the processing of data into images, icons, animations to help humans to understand data intuitively.
As shown in fig. 3, the disease information analysis module specifically includes:
the patient basic information acquisition module is used for establishing communication connection with a user terminal and acquiring the patient basic information input on the user terminal, wherein the patient basic information comprises patient identity information and illness state description information, and the illness state description information comprises illness state content, morbidity time and medication situation;
the patient basic information judging module is connected with the patient basic information acquiring module and the electronic case system platform and used for judging whether the patient has medical diagnosis history or not from the electronic case system platform according to the patient basic information acquired by the patient basic information acquiring module;
the first judgment processing module is connected with the patient basic information judgment module, the clinical decision system platform and the laboratory experiment data system platform and is used for generating patient condition information according to the clinical decision system platform, the laboratory experiment data system platform and the learning data of the previous big data learning algorithm when the patient basic information judgment module judges that the patient corresponding to the user side has no medical diagnosis history;
and the second judgment processing module is connected with the patient basic information judgment module, the electronic case system platform and the medical image archiving system platform and is used for calling the electronic case matched with the patient identity information in the electronic case system platform, calling the medical image matched with the patient identity information in the medical image archiving system platform and analyzing the called electronic case and medical image to generate new patient condition information when the patient basic information judgment module judges that the patient corresponding to the user side has medical diagnosis history.
In this embodiment, the patient condition information of the patient is determined by analyzing the patient condition basic information sent by the user side, wherein the determining process is a process of big data analysis, learning and application of each subsystem, so that the patient condition information basically matching with the patient condition is generated at one end of the server as a preliminary judgment to provide reference for the doctor and the patient.
In the embodiment of the present invention, as shown in fig. 4, the medical information analysis module specifically includes:
the hospitalizing time generation module is connected with the disease condition information analysis module and the clinical decision system platform and used for obtaining disease condition information according to the disease condition information analysis module and generating hospitalizing time according to the clinical decision system platform;
the medical doctor information acquisition module is connected with the disease condition information analysis module and is used for acquiring corresponding information of a medical doctor room and the medical doctor according to the medical time generated by the medical time generation module and the disease condition information acquired by the disease condition information analysis module;
and the medical care item generating module is connected with the disease condition information analyzing module and used for generating medical care item information according to the disease condition information acquired by the disease condition information analyzing module, wherein the medical care item information comprises fasting or not information and family accompanying information.
In this embodiment, through the determination of the above-mentioned medical condition information, if the patient needs to seek medical advice, the patient is provided with relevant information about the medical advice, such as the push of content information including medical advice time, medical advice office and doctor, and medical advice notes.
In the embodiment of the present invention, the electrocardiographic data, the blood oxygen concentration, the respiration, the blood pressure, the body temperature, the pulse and the exercise amount are obtained through the electronic device in matching connection with the user terminal, wherein the electronic device includes the currently common intelligent wearable devices such as a sphygmomanometer, an electronic bracelet, etc. and professional medical testing equipment, which is not limited herein, and the intelligent wearable device is taken as an example for description:
(1) designing a personal data collection system on the intelligent wearable device, and periodically collecting user data including information such as position, acceleration, temperature, heartbeat and the like;
(2) the position information should be as accurate as possible in view of the need to provide contact information;
(3) the user can set the data to be collected and the frequency and duration of data collection;
(4) given that medical researchers may not have programming experience, the configuration should be simple.
In the embodiment of the present invention, the user side is used as a personal information data collection system, which may adopt an iEpi system, and the iEpi system includes 2 parts: a data collection part (HealthLogger) and an auxiliary processing part. Wherein, HealthLogger consists of 5 modules.
A task manager: the health logger tasks include uploading data, transmitting data, reading sensors. The tasks are scheduled in a continuous mode and a periodic mode, wherein the period and the duration of the periodic tasks need to be set. The task manager also schedules other services.
Data flow and filter: the data stream provides a standard interface for accessing Android sensor APIs and other data, and the filter helps the user to cull out unwanted data.
Data logging and data caching: the data log stores the collected data, and the data cache provides a temporary storage function for the data log.
A data transmitter: the data transmitter is a general file uploader used by the other components of health logger to upload data to the server.
iEpian: is a simple script provided by HealthLogger and is used for providing a function for controlling a data acquisition mode for a medical researcher without programming experience.
Wherein the design of the data collector can be done without programming experience. HealthLogiger also provides a Bluetooth interface to assist the user in collecting data provided by other devices, such as weight information and diet information. When the user data is collected, the user data is stored in an Apache server in a file form, and the iEpi periodically checks a new file, decrypts and analyzes the data, and then stores the data in a database according to the user and data acquisition period. Because the position information provided by the GPS is inaccurate when the iEpi positioning device is indoors, in order to improve the accuracy of the position information, the iEpi positioning device adopts a SaskEPS algorithm to improve the calculation accuracy of the indoor position by utilizing the position and the signal strength of the access point.
In the embodiment of the present invention, in the communication framework established among the server, the user side and the doctor side, the following content services can be provided: providing a multifunctional health network community, which specifically comprises the following steps:
a medical health network portal facing patients is designed to provide services for patients, family members of the patients, nurses and doctors. The patients can use the medical health network community to exchange treatment experience and disease information and learn medical knowledge so as to better understand the conditions of the patients and control the development of the conditions of the patients; the family members of the patient can know the disease of the patient, discuss the treatment experience and read educational books by using the medical health network community so as to provide better care; nurses need to quickly establish knowledge about the disease to guide the patient to actively respond to the treatment. The medical health network community also provides the following functions: physicians need to quickly gain access to relevant tools and resources in the face of unfamiliar diseases; part of the medical health network community provides anonymous electronic health records from which medical researchers can mine information.
In order to meet the various needs, besides providing simple medical health community functions, the system also comprises the following 4 parts:
Personalized patient intelligence tool: mining electronic patient cases and patient blogs by using a data mining method to find the relationship between life style, treatment and curative effect and provide preventive suggestions for patients;
a disease management tool: recording diabetes parameters (blood sugar, blood pressure, glycosylated hemoglobin and the like), nutrition, exercise amount and dosage of a patient, and forming a visual report to help a user manage own conditions;
the social function is as follows: the functions of sharing experience and emotion of the user, providing answer questions, searching emotion support and the like are provided.
And (4) an educational function: providing credible medical articles, research reports, health recipes and the like, and providing a knowledge search engine for users.
In the embodiment of the invention, the medical health big data platform comprises a server, a user side and a doctor side, wherein: the server is used for analyzing the basic illness state information provided by the user side by combining the data of the medical information sharing platform and utilizing an application algorithm of big data to generate medical advice information which accords with patients at the user side; the user side is in communication connection with the server and is used for receiving the basic information of the illness state input by the patient and receiving and displaying the medical advice information generated by the server; the doctor end is in communication connection with the server and used for receiving and displaying the medical suggestion information generated by the server, so that the combination of big data and medical health is fully realized, the advantage of big data analysis is fully applied in the field of medical health, and powerful help is provided for medical health.
The above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (8)
1. The utility model provides a big data platform of medical health which characterized in that, includes server, user end and doctor's end, wherein:
the server is used for analyzing the basic illness state information provided by the user terminal by combining the data of the medical information sharing platform and utilizing an application algorithm of big data to generate medical advice information which accords with the patient at the user terminal, wherein the medical advice information comprises illness state information, hospitalizing information, treatment scheme information, medication reminding information and doctor advice information;
the user side is in communication connection with the server and is used for receiving the basic information of the illness state input by the patient and receiving and displaying the medical advice information generated by the server;
The doctor end is in communication connection with the server and used for receiving and displaying the medical suggestion information generated by the server.
2. The medical health big data platform of claim 1, wherein the medical information common platform comprises an electronic case system platform, a laboratory experiment data system platform, a medical image archiving system platform, and a clinical decision system platform;
the electronic case history system platform is used for storing the electronic case history corresponding to the patient who has a doctor in the past;
the laboratory experiment data system platform is used for storing data related to laboratory medical experiment results;
the medical image archiving system platform is used for storing medical image materials corresponding to patients who have a medical visit in the past;
the clinical decision system platform is used for storing clinical decision content.
3. The healthcare big data platform of claim 2, wherein the server comprises:
the disease condition information analysis module is used for generating disease condition information by combining the medical information sharing platform and utilizing an application algorithm of big data for the basic disease condition information provided by the user side;
the medical information analysis module is used for analyzing the illness state information acquired by the illness state information analysis module by combining with the medical information sharing platform to generate medical information corresponding to the user-side patient, and the medical information comprises medical time, medical doctor information and medical care items;
The treatment scheme information analysis module is used for generating treatment scheme information of the patient by combining the clinical decision system platform and the disease condition information analysis module;
the medicine taking reminding information analysis module is used for generating medicine taking information of the patient by combining the illness state information and the treatment scheme information;
and the doctor suggestion information analysis module is used for generating doctor suggestion information according to the illness state information and the treatment scheme information.
4. The medical health big data platform according to claim 2, wherein the condition information analysis module specifically comprises:
the patient basic information acquisition module is used for establishing communication connection with a user terminal and acquiring the patient basic information input on the user terminal, wherein the patient basic information comprises patient identity information and illness state description information, and the illness state description information comprises illness state content, morbidity time and medication situation;
the patient basic information judging module is connected with the patient basic information acquiring module and the electronic case system platform and used for judging whether the patient has medical diagnosis history or not from the electronic case system platform according to the patient basic information acquired by the patient basic information acquiring module;
The first judgment processing module is connected with the patient basic information judgment module, the clinical decision system platform and the laboratory experiment data system platform and is used for generating patient condition information according to the clinical decision system platform, the laboratory experiment data system platform and the learning data of the previous big data learning algorithm when the patient basic information judgment module judges that the patient corresponding to the user side has no medical diagnosis history;
and the second judgment processing module is connected with the patient basic information judgment module, the electronic case system platform and the medical image archiving system platform and is used for calling the electronic case matched with the patient identity information in the electronic case system platform, calling the medical image matched with the patient identity information in the medical image archiving system platform and analyzing the called electronic case and medical image to generate new patient condition information when the patient basic information judgment module judges that the patient corresponding to the user side has medical diagnosis history.
5. The medical health big data platform according to claim 2, wherein the hospitalization information analysis module specifically comprises:
The hospitalizing time generation module is connected with the disease condition information analysis module and the clinical decision system platform and used for obtaining disease condition information according to the disease condition information analysis module and generating hospitalizing time according to the clinical decision system platform;
the medical doctor information acquisition module is connected with the disease condition information analysis module and is used for acquiring corresponding information of a medical doctor room and the medical doctor according to the medical time generated by the medical time generation module and the disease condition information acquired by the disease condition information analysis module;
and the medical care item generating module is connected with the disease condition information analyzing module and used for generating medical care item information according to the disease condition information acquired by the disease condition information analyzing module, wherein the medical care item information comprises fasting or not information and family accompanying information.
6. The medical health big data platform of claim 2, wherein the basic information of the disease condition comprises information of disease condition, electrocardiographic data, blood oxygen concentration, respiration, blood pressure, body temperature, pulse and exercise amount.
7. The medical health big data platform of claim 6, wherein the electrocardiographic data, blood oxygen concentration, respiration, blood pressure, body temperature, pulse and amount of exercise are obtained through an electronic device in matching connection with the user terminal.
8. The medical health big data platform according to claim 6, wherein the big data application algorithm comprises association rule learning algorithm, classification algorithm, cluster analysis algorithm, data fusion algorithm, machine learning algorithm, natural language processing algorithm, regression algorithm, signal processing algorithm, simulation algorithm, and visualization algorithm.
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| CN113161016A (en) * | 2020-12-31 | 2021-07-23 | 上海明品医学数据科技有限公司 | Intelligent medical service system, method and storage medium |
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| CN113161016A (en) * | 2020-12-31 | 2021-07-23 | 上海明品医学数据科技有限公司 | Intelligent medical service system, method and storage medium |
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