CN113178254A - Intelligent medical data analysis method and device based on 5G and computer equipment - Google Patents
Intelligent medical data analysis method and device based on 5G and computer equipment Download PDFInfo
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Abstract
The invention provides a 5G-based intelligent medical data analysis method, a device and computer equipment, wherein the method comprises the steps of obtaining intelligent medical data from a sharing platform through a 5G technology to obtain initial data, wherein the initial data comprises data obtained by medical equipment detection, physical examination data and medical treatment information; preprocessing initial data to obtain intermediate data, wherein the intermediate data comprises personal information and image information; and inputting the intermediate data into an analysis model to analyze health information to obtain an analysis result, wherein the health information refers to information related to the focus, the analysis model is obtained by using a plurality of medical images with labels of whether the focus exists and position information labels of the focus when the focus exists as a sample set training deep learning network, and the analysis result comprises the position information of whether the focus exists and the position information of the focus when the focus exists. Compared with the prior art, the method has high analysis efficiency and high accuracy, and is beneficial to subsequent health monitoring.
Description
Technical Field
The invention relates to the technical field of intelligent medical treatment, in particular to a 5G-based intelligent medical data analysis method and device and computer equipment.
Background
With the continuous development of scientific technology, big data and cloud computing are generally applied to various industries, great convenience is brought to the life of people, the healthy big data are new terms appearing with digital wave and information modernization in recent years, the purpose of the big data is to perform specialized processing and recycling on the healthy data, and the big data has positive significance on physical condition monitoring, disease prevention, health trend analysis and prediction.
Medical data is closely related to health monitoring, medical data of hospitals are not shared, the efficiency is low when the medical data are obtained, most of the medical data are analyzed by experienced doctors, the analyzed results are uploaded to a cloud server, the upper and lower limit standards and the suggested standards given to health signs are used for managing and predicting health conditions according to historical curves of the data, rigid clinical guidelines, health guidelines and the like, the disease risks and the health conditions of users cannot be truly reflected, even the future risk trends of the users aiming at diseases cannot be reflected, the analysis results are likely to have low accuracy due to errors of experience problems of analysts, and further subsequent health monitoring is affected.
Therefore, it is necessary to design a new method, which has high analysis efficiency and high accuracy, and is beneficial to the subsequent health monitoring.
Disclosure of Invention
In a first aspect, the invention provides a 5G-based intelligent medical data analysis method, which includes:
step 110, acquiring intelligent medical data from a sharing platform through a 5G technology to obtain initial data, wherein the initial data comprises data obtained by medical equipment detection, physical examination data and medical treatment information;
step 120, preprocessing the initial data to obtain intermediate data, wherein the intermediate data comprises personal information and image information;
and step 130, inputting the intermediate data into an analysis model to analyze health information, wherein the health information refers to information related to the focus, the analysis model is obtained by using a plurality of medical images with labels of whether the focus exists and position information labels of the focus when the focus exists as a sample set training deep learning network, and the analysis result comprises the position information of the focus when the focus exists and the label of whether the focus exists.
Further, in one implementation, the step 120 includes:
step 121, collecting the initial data;
step 122, extracting information from the initial data by adopting an optical character recognition method to obtain personal information, wherein the personal information comprises weight, height, blood type and age;
and step 123, screening the image information in the initial data to obtain intermediate data.
Further, in an implementation manner, the step 130 is followed by:
step 240, determining a human health condition according to the analysis result and the personal information, wherein the human health condition comprises a disease stage and subsequent health condition changes;
the step 240 includes: step 241, determining the stage of the focus according to the analysis result;
step 242, extracting keywords according to the analysis result, the stage of the focus and the personal information to obtain key features, wherein the key features comprise the type of the focus, the stage of the focus, the sex and the age of the person;
and 243, screening out the corresponding human health condition from a preset mapping table in the database according to the key characteristics.
Further, in an implementation manner, the step 130 is followed by:
step 350, adjusting the health condition of the human body to form a monitoring result;
and 360, feeding back the monitoring result to a terminal, and displaying the monitoring result on the terminal.
In a second aspect, the present invention provides a 5G-based intelligent medical data analysis apparatus for executing the 5G-based intelligent medical data analysis method, the apparatus comprising: a data acquisition unit 301, a preprocessing unit 302, and an analysis unit 303;
the data acquisition unit 301 is configured to acquire the smart medical data from the sharing platform through a 5G technology to obtain initial data;
the preprocessing unit 302 is configured to preprocess the initial data to obtain intermediate data;
the analysis unit 303 is configured to input the intermediate data into an analysis model to perform health information analysis, so as to obtain an analysis result.
Further, in one implementation, the preprocessing unit 302 includes a gathering subunit 3021, an extracting subunit 3022, and a screening subunit 3023;
the collecting subunit 3021 is configured to collect the initial data;
the extracting subunit 3022 is configured to perform information extraction on the initial data to obtain personal information;
the screening subunit 3023 is configured to screen image information in the initial data to obtain intermediate data.
Further, in one implementation, the apparatus further includes: a situation determination unit 304, configured to determine a health situation of the human body according to the analysis result and the personal information;
the situation determination unit 304 includes a stage determination subunit 3041, a feature extraction subunit 3042, and a situation screening subunit 3043;
the stage determining subunit 3041, configured to determine a stage where the lesion is located according to the analysis result;
the feature extraction subunit 3042 is configured to perform keyword extraction according to the analysis result, the stage of the focus, and the personal information to obtain a key feature;
the situation screening subunit 3043 is configured to screen out a corresponding human health situation from a preset mapping table in the database according to the key feature.
Further, in one implementation, the apparatus further includes: an adjustment unit 305 and a feedback unit 306;
the adjusting unit 305 is configured to adjust the health condition of the human body to form a monitoring result;
the feedback unit 306 is configured to feed back the monitoring result to the terminal, and display the monitoring result on the terminal.
In a third aspect, the invention provides a computer device for operating on any one of the 5G-based intelligent medical data analysis devices;
the computer device comprises a processor 502, a memory and a network interface 505 connected by a system bus 501, wherein the memory comprises a non-volatile storage medium 503 and an internal memory 504;
the non-volatile storage medium 503 may store an operating system 5031 and computer programs 5032;
the computer programs 5032 include program instructions that, when executed, cause the processor 502 to perform a 5G-based intelligent medical data analysis method;
the processor 502 is used for providing computing and control capability, and supporting the operation of the whole computer device;
the internal memory 504 provides an environment for running the computer program 5032 in the non-volatile storage medium 503, and when the computer program 5032 is executed by the processor 502, the processor 502 can be enabled to execute a 5G-based intelligent medical data analysis method;
the network interface 505 is used for network communication with other devices;
the processor 502 is configured to run the computer program 5032 stored in the memory, and to perform the following steps:
acquiring intelligent medical data from a sharing platform through a 5G technology to obtain initial data; preprocessing the initial data to obtain intermediate data; inputting the intermediate data into an analysis model for health information analysis to obtain an analysis result;
wherein, the analysis model is obtained by training a deep learning network by using a plurality of medical images with labels of whether the focus exists and position information labels of the focus when the focus exists as a sample set;
the analysis result includes information on whether a lesion is present and a location of the lesion when the lesion is present;
when the processor 502 implements the step of preprocessing the initial data to obtain intermediate data, the following steps are specifically implemented:
collecting the initial data; extracting information from the initial data to obtain personal information; screening image information in the initial data to obtain intermediate data;
or, after the step of inputting the intermediate data into the analysis model for health information analysis to obtain an analysis result, the processor 502 further implements the following steps:
determining the health condition of the human body according to the analysis result and the personal information;
or, when the processor 502 implements the step of determining the human health condition according to the analysis result and the personal information, the following steps are specifically implemented:
determining the stage of the focus according to the analysis result; extracting key words according to the analysis result, the stage of the focus and the personal information to obtain key features; screening out corresponding human health conditions from a preset mapping table in a database according to the key features;
alternatively, after the step of determining the health condition of the human body according to the analysis result and the personal information is implemented, the processor 502 further implements the following steps:
adjusting the health condition of a human body to form a monitoring result; and feeding back the monitoring result to a terminal, and displaying the monitoring result at the terminal.
Compared with the prior art, the 5G-based intelligent medical data analysis method, the device and the computer equipment provided by the invention have the advantages of high analysis efficiency and high accuracy, and are beneficial to subsequent health monitoring.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
Fig. 1 is a schematic view of an application scenario of a 5G-based intelligent medical data analysis method according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart illustrating a 5G-based intelligent medical data analysis method according to an embodiment of the present invention;
FIG. 3 is a schematic sub-flowchart of a 5G-based intelligent medical data analysis method according to an embodiment of the present invention;
FIG. 4 is a schematic flow chart illustrating a 5G-based intelligent medical data analysis method according to another embodiment of the present invention;
FIG. 5 is a schematic sub-flowchart of a 5G-based intelligent medical data analysis method according to another embodiment of the present invention;
FIG. 6 is a schematic flow chart illustrating a 5G-based intelligent medical data analysis method according to another embodiment of the present invention;
FIG. 7 is a schematic block diagram of a 5G-based intelligent medical data analysis device according to an embodiment of the present invention;
FIG. 8 is a schematic block diagram of a preprocessing unit of a 5G-based intelligent medical data analysis device according to an embodiment of the present invention;
FIG. 9 is a schematic block diagram of a 5G-based intelligent medical data analysis device according to another embodiment of the present invention;
FIG. 10 is a block diagram of a health status determination unit of a 5G-based intelligent medical data analysis device according to another embodiment of the invention;
FIG. 11 is a schematic block diagram of a 5G-based intelligent medical data analysis device according to another embodiment of the present invention;
FIG. 12 is a schematic block diagram of a computer device provided by an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Referring to fig. 1 and fig. 2, fig. 1 is a schematic view of an application scenario of a 5G-based intelligent medical data analysis method according to an embodiment of the present invention. Fig. 2 is a schematic flowchart of a 5G-based intelligent medical data analysis method according to an embodiment of the present invention. The intelligent medical data analysis method based on 5G is applied to a monitored server. This server carries out data interaction with shared platform and terminal, and the hospital, physical examination center and various medical equipment all can adopt the 5G technique to upload to shared platform the wisdom medical data that detect, acquire these medical data by the server through the 5G technique after, adopt degree of depth study and big data analysis technique to carry out the analysis to obtain the control condition, be convenient for subsequent health monitoring, and with monitor result send to the terminal, supply terminal holders such as doctor to look over.
Fig. 2 is a schematic flow chart of a 5G-based intelligent medical data analysis method according to an embodiment of the present invention. As shown in fig. 2, the method includes the following steps S110 to S130.
And S110, acquiring intelligent medical data from the shared platform through a 5G technology to obtain initial data.
In the present embodiment, the initial data includes data detected from the medical device, physical examination data, and medical visit information.
Specifically, the 5G technology is used for acquiring the intelligent medical data by using the unique marking information of the identity information of the patient, such as the identification number, and the like, so that the data acquisition efficiency can be improved, and the data analysis efficiency can be further improved.
And S120, preprocessing the initial data to obtain intermediate data.
In the present embodiment, the intermediate data refers to processed data obtained by classifying the personal information and the image information separately.
In an embodiment, referring to fig. 3, the step S120 may include steps S121 to S123.
And S121, collecting the initial data.
In this embodiment, all the initial data is downloaded and aggregated into a newly built database for subsequent information extraction.
And S122, extracting information from the initial data to obtain personal information.
In this embodiment, the personal information includes weight, height, blood type, age, and the like. The initial data is used for extracting the personal information by adopting an Optical Character Recognition (OCR) technology, and if the OCR can only recognize the personal information, the personal information can be distinguished from the image information so as to facilitate the subsequent feature analysis on the image information.
And S123, screening the image information in the initial data to obtain intermediate data.
In this embodiment, image information needs to be separately screened out to analyze by using the LSTM recurrent neural network to increase the accuracy of the analysis, and image information is screened by using the LSTM recurrent neural network, which belongs to the prior art and is not described herein again. Specifically, in this embodiment, the LSTM image classification processing technique may refer to the following linked contents: https:// blog.csdn.net/qq _ 36187544/article/details/90700119.
And S130, inputting the intermediate data into an analysis model for health information analysis to obtain an analysis result.
In the present embodiment, the health information refers to information related to a lesion, and the analysis result includes information on whether or not a lesion exists and a location of the lesion when the lesion exists.
In this embodiment, the analysis model may be trained to form models for detecting different lesions according to different characteristics of the sample set, thereby improving the efficiency of the entire analysis.
Specifically, the analysis model is obtained by training a deep learning network with a plurality of medical images with labels of whether or not a lesion exists and labels of position information of the lesion when the lesion exists as a sample set. Specifically, in this embodiment, the following documents can be referred to for the analysis model: depth learning and identification research progress of capsule endoscopic image focus in recent four years [ J ] electronic measurement and instrument bulletin, 2019, v.33; no.224(08) 75-83.
Adopting a sample set as a positive sample and a negative sample, for example, a sample set with a tumor focus label and a tumor position is used as a positive sample, and the others are used as negative samples; in this embodiment, a Long Short-Term Memory network (LSTM) is used as a deep learning network for training, a variance is used as an error function for processing, and parameters of the deep learning network are continuously adjusted, so that after part of verification sets divided from a sample set is input to the model, an accurate analysis result can be obtained.
The method is characterized in that health influencing factors such as lesions and the like are associated with physical characteristics of individual body types, the health influencing factors are associated with physiological, biochemical examination values or examination values, the physical characteristics of individual body types are associated with the examination values or examination values, the health influencing factors are associated with multiple chronic diseases, the physical characteristics of individual body types are associated with multiple chronic diseases, the examination values are associated with multiple chronic diseases, an effective analysis and prediction mode can be combined, an omnibearing full-generation multiple chronic disease occurrence risk analysis and prediction mode can be constructed, the method is beneficial to integrated medical application of multiple chronic diseases besides medical and personal health promotion, and the method is further suitable for risk analysis and prediction before disease occurrence and accurate analysis, analysis and prediction of core causes when core diseases coexist with the common diseases, Accurate analysis and prediction of disease progression pathways.
After the analysis result is obtained, the analysis result can be fed back to the terminal, if the analysis result shows that a focus, such as a breast nodule exists and the position of the focus such as the breast nodule is given, the health condition can be obtained, and the subsequent health monitoring is convenient.
According to the intelligent medical data analysis method based on 5G, after the intelligent medical data are obtained through the 5G technology, the deep learning network is adopted for analysis, the data are obtained quickly, the overall analysis efficiency can be improved, the deep learning network is adopted for accurate analysis, the analysis accuracy can be improved, and the follow-up healthy monitoring is facilitated.
Fig. 4 is a schematic flowchart of a 5G-based intelligent medical data analysis method according to another embodiment of the present invention. As shown in FIG. 4, the 5G-based intelligent medical data analysis method of the present embodiment includes steps S210-S240. Steps S210 to S230 are similar to steps S110 to S130 in the above embodiments, and are not described herein again. The added step S240 in the present embodiment is explained in detail below.
And S240, determining the health condition of the human body according to the analysis result and the personal information.
In this embodiment, the human health condition includes the disease stage and the subsequent health condition changes.
In an embodiment, referring to fig. 5, the step S240 may include steps S241 to S243.
And S241, determining the stage of the focus according to the analysis result.
In this embodiment, the stage where the focus is located is determined by the body state size of the focus, so that the coordinates of each point of the focus can be obtained by the position information in the analysis result, the body state size of the focus is calculated according to the coordinate difference, and then the stage determination is performed according to the body state size of the focus. Specifically, in the present embodiment, the deep learning network technology refers to the contents of the following links: https:// blog.csdn.net/qq _ 32618327/article/details/99069240.
And S242, extracting key words according to the analysis result, the stage of the focus and the personal information to obtain key features.
In this embodiment, the key features include the type of lesion, the stage of the lesion, and the sex and age of the individual. Specifically, the lesion type is specified by data corresponding to personal information (historically registered lesion type-related data).
Since the disease condition and the progression of the disease condition of people of different sexes and ages are different, the extraction of key features is required, and in this embodiment, the extraction of keywords can be performed by Natural Language Processing (NLP) technology.
And S243, screening out the corresponding human health condition from a preset mapping table in the database according to the key characteristics.
In this embodiment, a mapping table associated with age, gender, lesion size, lesion type and human health status is constructed in the preset database, and after the key features are known, the corresponding human health status including current health level such as sub-health and the like and cautions can be obtained from the mapping table.
The extracted key features are directly mapped to the human health condition, the human health condition is standardized, the health condition is not judged by the experience of doctors, and in addition, the mapping table is a table continuously updated by a group of experienced doctors, so that the subsequent monitoring is more accurate.
Fig. 6 is a schematic flow chart of a 5G-based intelligent medical data analysis method according to another embodiment of the present invention. As shown in FIG. 6, the 5G-based intelligent medical data analysis method of the present embodiment includes steps S310-S360. Steps S310 to S340 are similar to steps S210 to S240 in the above embodiments, and are not described herein again. The added steps S350 to S360 in the present embodiment will be described in detail below.
And S350, adjusting the health condition of the human body to form a monitoring result.
In this embodiment, the monitoring result refers to the health condition of the human body after fine adjustment.
After the human health condition is obtained from the mapping table, sometimes a non-unique condition or a condition that cannot be queried occurs, and this condition needs to be finely adjusted, for example, the condition is forwarded to a doctor to manually determine the human health condition, so that the human health condition of different conditions is considered, and if the condition is a special focus, the human health condition can be determined and then output.
And S360, feeding back the monitoring result to the terminal so as to display the monitoring result on the terminal.
And feeding back the monitoring result to the terminal, so that the terminal holder can check the monitoring result to monitor the subsequent health condition conveniently.
Fig. 7 is a schematic block diagram of a 5G-based intelligent medical data analysis device 300 according to an embodiment of the present invention. As shown in fig. 7, the present invention also provides a 5G-based intelligent medical data analysis device 300 corresponding to the above 5G-based intelligent medical data analysis method. The 5G-based smart medical data analysis apparatus 300 includes a unit for performing the above-described 5G-based smart medical data analysis method, and the apparatus may be configured in a terminal. Specifically, referring to fig. 7, the 5G-based intelligent medical data analysis apparatus 300 includes a data acquisition unit 301, a preprocessing unit 302 and an analysis unit 303.
A data acquisition unit 301, configured to acquire smart medical data from a shared platform by using a 5G technology to obtain initial data; a preprocessing unit 302, configured to preprocess the initial data to obtain intermediate data; the analysis unit 303 is configured to input the intermediate data into an analysis model for health information analysis, so as to obtain an analysis result.
In one embodiment, as shown in fig. 8, the preprocessing unit 302 includes a collecting subunit 3021, an extracting subunit 3022, and a filtering subunit 3023.
A collecting subunit 3021 configured to collect the initial data; an extracting subunit 3022, configured to perform information extraction on the initial data to obtain personal information; a filtering subunit 3023, configured to filter the image information in the initial data to obtain intermediate data.
Fig. 9 is a schematic block diagram of a 5G-based intelligent medical data analysis device 300 according to another embodiment of the present invention. As shown in fig. 9, the 5G-based intelligent medical data analysis device 300 of the present embodiment is the above-mentioned embodiment, and is added with a situation determination unit 304.
A situation determining unit 304, configured to determine a health situation of the human body according to the analysis result and the personal information.
In an embodiment, as shown in fig. 10, the situation determining unit 304 includes a stage determining subunit 3041, a feature extracting subunit 3042, and a situation screening subunit 3043.
A stage determining subunit 3041, configured to determine a stage where the lesion is located according to the analysis result; a feature extraction subunit 3042, configured to perform keyword extraction according to the analysis result, the stage of the focus, and the personal information, to obtain a key feature; a situation screening subunit 3043, configured to screen out, according to the key feature, a corresponding human health situation from a preset mapping table in the database.
Fig. 11 is a schematic block diagram of a 5G-based intelligent medical data analysis device 300 according to another embodiment of the present invention. As shown in fig. 11, the 5G-based intelligent medical data analysis device 300 of the present embodiment is added with an adjustment unit 305 and a feedback unit 306 in addition to the above-mentioned embodiments.
An adjusting unit 305, configured to adjust the health condition of the human body to form a monitoring result; a feedback unit 306, configured to feed back the monitoring result to the terminal, so as to display the monitoring result on the terminal.
It should be noted that, as can be clearly understood by those skilled in the art, the detailed implementation process of the 5G-based intelligent medical data analysis apparatus 300 and each unit may refer to the corresponding description in the foregoing method embodiments, and for convenience and brevity of description, no further description is provided herein.
The above-mentioned 5G-based intelligent medical data analysis apparatus 300 may be implemented in the form of a computer program that can be run on a computer device as shown in fig. 12.
Referring to fig. 12, fig. 12 is a schematic block diagram of a computer device according to an embodiment of the present application. The computer device 500 may be a server, wherein the server may be an independent server or a server cluster composed of a plurality of servers.
Referring to fig. 12, the computer device 500 includes a processor 502, memory, and a network interface 505 connected by a system bus 501, where the memory may include a non-volatile storage medium 503 and an internal memory 504.
The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions that, when executed, cause the processor 502 to perform a 5G-based intelligent medical data analysis method.
The processor 502 is used to provide computing and control capabilities to support the operation of the overall computer device 500.
The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503, and when the computer program 5032 is executed by the processor 502, the processor 502 can execute a 5G-based intelligent medical data analysis method.
The network interface 505 is used for network communication with other devices. Those skilled in the art will appreciate that the configuration shown in fig. 12 is a block diagram of only a portion of the configuration associated with the present application and does not constitute a limitation of the computer device 500 to which the present application may be applied, and that a particular computer device 500 may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
Wherein the processor 502 is configured to run the computer program 5032 stored in the memory to implement the following steps:
acquiring intelligent medical data from a sharing platform through a 5G technology to obtain initial data; preprocessing the initial data to obtain intermediate data; and inputting the intermediate data into an analysis model for health information analysis to obtain an analysis result.
Wherein the analysis model is obtained by training a deep learning network by using a plurality of medical images with labels of whether the focus exists and position information labels of the focus when the focus exists as a sample set.
The analysis result includes information on whether a lesion is present and a location of the lesion when the lesion is present.
In an embodiment, when the processor 502 implements the step of preprocessing the initial data to obtain the intermediate data, the following steps are specifically implemented:
collecting the initial data; extracting information from the initial data to obtain personal information; and screening the image information in the initial data to obtain intermediate data.
In an embodiment, after the step of inputting the intermediate data into the analysis model for health information analysis to obtain the analysis result, the processor 502 further implements the following steps:
and determining the health condition of the human body according to the analysis result and the personal information.
In an embodiment, when the processor 502 implements the step of determining the health condition of the human body according to the analysis result and the personal information, the following steps are specifically implemented:
determining the stage of the focus according to the analysis result; extracting key words according to the analysis result, the stage of the focus and the personal information to obtain key features; and screening out the corresponding human health condition from a preset mapping table in a database according to the key characteristics.
In an embodiment, after the step of determining the health condition of the human body according to the analysis result and the personal information is performed, the processor 502 further performs the following steps:
adjusting the health condition of a human body to form a monitoring result; and feeding back the monitoring result to the terminal so as to display the monitoring result on the terminal.
It should be understood that in the embodiment of the present Application, the Processor 502 may be a Central Processing Unit (CPU), and the Processor 502 may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
It will be understood by those skilled in the art that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program instructing associated hardware. The computer program includes program instructions, and the computer program may be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the flow steps of the embodiments of the method described above.
Accordingly, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program, when executed by a processor, causes the processor to perform the steps of:
acquiring intelligent medical data from a sharing platform through a 5G technology to obtain initial data; preprocessing the initial data to obtain intermediate data; and inputting the intermediate data into an analysis model for health information analysis to obtain an analysis result.
Wherein the analysis model is obtained by training a deep learning network by using a plurality of medical images with labels of whether the focus exists and position information labels of the focus when the focus exists as a sample set.
The analysis result includes information on whether a lesion is present and a location of the lesion when the lesion is present.
In an embodiment, when the processor executes the computer program to implement the step of preprocessing the initial data to obtain the intermediate data, the following steps are specifically implemented:
collecting the initial data; extracting information from the initial data to obtain personal information; and screening the image information in the initial data to obtain intermediate data.
In an embodiment, after the step of executing the computer program to implement the step of inputting the intermediate data into an analysis model for health information analysis to obtain an analysis result, the processor further implements the following steps:
and determining the health condition of the human body according to the analysis result and the personal information.
In an embodiment, when the processor executes the computer program to implement the step of determining the health condition of the human body according to the analysis result and the personal information, the processor specifically implements the following steps:
determining the stage of the focus according to the analysis result; extracting key words according to the analysis result, the stage of the focus and the personal information to obtain key features; and screening out the corresponding human health condition from a preset mapping table in a database according to the key characteristics.
In an embodiment, after the step of determining the health condition of the human body according to the analysis result and the personal information is implemented by the processor by executing the computer program, the following steps are further implemented:
adjusting the health condition of a human body to form a monitoring result; and feeding back the monitoring result to the terminal so as to display the monitoring result on the terminal.
The storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk, which can store various computer readable storage media.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative. For example, the division of each unit is only one logic function division, and there may be another division manner in actual implementation. For example, various elements or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented.
The steps in the method of the embodiment of the invention can be sequentially adjusted, combined and deleted according to actual needs. The units in the device of the embodiment of the invention can be merged, divided and deleted according to actual needs. In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a terminal, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (9)
1. A5G-based intelligent medical data analysis method is characterized by comprising the following steps:
step 110, acquiring intelligent medical data from a sharing platform through a 5G technology to obtain initial data, wherein the initial data comprises data obtained by medical equipment detection, physical examination data and medical treatment information;
step 120, preprocessing the initial data to obtain intermediate data, wherein the intermediate data comprises personal information and image information;
and step 130, inputting the intermediate data into an analysis model to analyze health information, wherein the health information refers to information related to the focus, the analysis model is obtained by using a plurality of medical images with labels of whether the focus exists and position information labels of the focus when the focus exists as a sample set training deep learning network, and the analysis result comprises the position information of the focus when the focus exists and the label of whether the focus exists.
2. The method according to claim 1, wherein the step 120 comprises:
step 121, collecting the initial data;
step 122, extracting information from the initial data by adopting an optical character recognition method to obtain personal information, wherein the personal information comprises weight, height, blood type and age;
and step 123, screening the image information in the initial data to obtain intermediate data.
3. The method according to claim 1, further comprising the following step 130:
step 240, determining a human health condition according to the analysis result and the personal information, wherein the human health condition comprises a disease stage and subsequent health condition changes;
the step 240 includes: step 241, determining the stage of the focus according to the analysis result;
step 242, extracting keywords according to the analysis result, the stage of the focus and the personal information to obtain key features, wherein the key features comprise the type of the focus, the stage of the focus, the sex and the age of the person;
and 243, screening out the corresponding human health condition from a preset mapping table in the database according to the key characteristics.
4. The method according to claim 1, further comprising the following step 130:
step 350, adjusting the health condition of the human body to form a monitoring result;
and 360, feeding back the monitoring result to a terminal, and displaying the monitoring result on the terminal.
5. A 5G-based intelligent medical data analysis device for performing a 5G-based intelligent medical data analysis method according to any one of claims 1-5, the device comprising: a data acquisition unit 301, a preprocessing unit 302, and an analysis unit 303;
the data acquisition unit 301 is configured to acquire the smart medical data from the sharing platform through a 5G technology to obtain initial data;
the preprocessing unit 302 is configured to preprocess the initial data to obtain intermediate data;
the analysis unit 303 is configured to input the intermediate data into an analysis model to perform health information analysis, so as to obtain an analysis result.
6. The 5G-based intelligent medical data analysis device as claimed in claim 5, wherein the preprocessing unit 302 comprises an aggregation subunit 3021, an extraction subunit 3022 and a screening subunit 3023;
the collecting subunit 3021 is configured to collect the initial data;
the extracting subunit 3022 is configured to perform information extraction on the initial data to obtain personal information;
the screening subunit 3023 is configured to screen image information in the initial data to obtain intermediate data.
7. The 5G-based intelligent medical data analysis device according to claim 5, further comprising: a situation determination unit 304, configured to determine a health situation of the human body according to the analysis result and the personal information;
the situation determination unit 304 includes a stage determination subunit 3041, a feature extraction subunit 3042, and a situation screening subunit 3043;
the stage determining subunit 3041, configured to determine a stage where the lesion is located according to the analysis result;
the feature extraction subunit 3042 is configured to perform keyword extraction according to the analysis result, the stage of the focus, and the personal information to obtain a key feature;
the situation screening subunit 3043 is configured to screen out a corresponding human health situation from a preset mapping table in the database according to the key feature.
8. The 5G-based intelligent medical data analysis device according to claim 5, further comprising: an adjustment unit 305 and a feedback unit 306;
the adjusting unit 305 is configured to adjust the health condition of the human body to form a monitoring result;
the feedback unit 306 is configured to feed back the monitoring result to the terminal, and display the monitoring result on the terminal.
9. A computer device configured to operate on the 5G-based smart medical data analysis device of any one of claims 6-9;
the computer device comprises a processor 502, a memory and a network interface 505 connected by a system bus 501, wherein the memory comprises a non-volatile storage medium 503 and an internal memory 504;
the non-volatile storage medium 503 may store an operating system 5031 and computer programs 5032;
the computer programs 5032 include program instructions that, when executed, cause the processor 502 to perform a 5G-based intelligent medical data analysis method;
the processor 502 is used for providing computing and control capability, and supporting the operation of the whole computer device;
the internal memory 504 provides an environment for running the computer program 5032 in the non-volatile storage medium 503, and when the computer program 5032 is executed by the processor 502, the processor 502 can be enabled to execute a 5G-based intelligent medical data analysis method;
the network interface 505 is used for network communication with other devices;
the processor 502 is configured to run the computer program 5032 stored in the memory, and to perform the following steps:
acquiring intelligent medical data from a sharing platform through a 5G technology to obtain initial data; preprocessing the initial data to obtain intermediate data; inputting the intermediate data into an analysis model for health information analysis to obtain an analysis result;
wherein, the analysis model is obtained by training a deep learning network by using a plurality of medical images with labels of whether the focus exists and position information labels of the focus when the focus exists as a sample set;
the analysis result includes information on whether a lesion is present and a location of the lesion when the lesion is present;
when the processor 502 implements the step of preprocessing the initial data to obtain intermediate data, the following steps are specifically implemented:
collecting the initial data; extracting information from the initial data to obtain personal information; screening image information in the initial data to obtain intermediate data;
or, after the step of inputting the intermediate data into the analysis model for health information analysis to obtain an analysis result, the processor 502 further implements the following steps:
determining the health condition of the human body according to the analysis result and the personal information;
or, when the processor 502 implements the step of determining the human health condition according to the analysis result and the personal information, the following steps are specifically implemented:
determining the stage of the focus according to the analysis result; extracting key words according to the analysis result, the stage of the focus and the personal information to obtain key features; screening out corresponding human health conditions from a preset mapping table in a database according to the key features;
alternatively, after the step of determining the health condition of the human body according to the analysis result and the personal information is implemented, the processor 502 further implements the following steps:
adjusting the health condition of a human body to form a monitoring result; and feeding back the monitoring result to a terminal, and displaying the monitoring result at the terminal.
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