Radiotherapy patient daily monitoring management system based on deep learning

Abstract

The invention discloses a radiotherapy patient daily monitoring management system based on deep learning, and relates to the technical field of monitoring data management, and the system comprises a configuration module which is used for determining radiotherapy patient information registration to obtain a patient end, and configuring a corresponding information element corresponding to the patient end; the storage module is connected with the configuration module and is used for collecting radiotherapy monitoring information of the patient, storing the radiotherapy monitoring information in a corresponding information element and accessing the information element through an access end; and the analysis module is connected with the storage module, and is used for analyzing the radiotherapy monitoring information in the information element according to the learning model to obtain an analysis result, providing the analysis result to a medical care terminal and a patient terminal, and collecting basic information and disease information of a radiotherapy patient as radiotherapy patient information. According to the method, the medical data can be checked by the access end through the information element, but cannot be pulled or tampered by the data, the analysis result of the medical data cannot be influenced, and the safety of the data is also considered while the normal use of the medical data is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of monitoring data management, and in particular to a daily monitoring and management system for radiotherapy patients based on deep learning. Background Art

[0002] With the rapid development of information technology, the development of medical informatization has become an unstoppable trend in the global healthcare industry. Medical institutions have actively responded to this trend and increased their investment in medical informatization, vigorously building information infrastructure such as electronic medical record systems and medical image storage and transmission systems. The gradual improvement of this infrastructure not only provides an efficient platform for the integration and management of medical data, but also strengthens the data and technical foundation for the daily monitoring and management system for radiotherapy patients based on deep learning, driving radiotherapy monitoring towards intelligent and precise management.

[0003] In the treatment of brain diseases, radiotherapy is often indispensable for the treatment of conditions such as gliomas, brain metastases, and pituitary tumors. During radiotherapy, patient monitoring data is crucial for formulating and adjusting treatment plans. The data resources accumulated through the development of medical informatization can provide rich data support for radiotherapy monitoring of these diseases, helping medical personnel to more accurately understand the patient's condition and improve treatment effectiveness.

[0004] However, while healthcare informatization brings convenience, data security issues also become prominent. Patients' medical data contains a wealth of sensitive information, such as personal identity, health status, and treatment records. In existing healthcare systems, data access points pose a risk of unauthorized access, exposing this sensitive information to potential leaks. This could not only infringe on patient privacy but also severely damage healthcare order and patient rights. Therefore, as we leverage the advancements of healthcare informatization to advance radiotherapy monitoring, strengthening data security is a crucial issue that needs to be addressed. Summary of the Invention

[0005] The purpose of the present invention is to provide a daily monitoring and management system for radiotherapy patients based on deep learning to address the shortcomings of the background technology.

[0006] To achieve the above objectives, the present invention provides the following technical solutions: a daily monitoring and management system for radiotherapy patients based on deep learning, comprising:

[0007] A configuration module is used to determine the patient end of the radiotherapy patient registration information and configure the corresponding information element on the patient end;

[0008] The storage module is connected to the configuration module and is used to collect the patient's radiotherapy monitoring information and store it in the corresponding information element, and access the information element through the access terminal;

[0009] The analysis module is connected to the storage module and is used to analyze the radiotherapy monitoring information in the information element according to the learning model to obtain analysis results, and provide the analysis results to the medical and patient ends.

[0010] In a preferred embodiment, the configuration module includes:

[0011] A collection unit, used for collecting basic information and disease information of radiotherapy patients as radiotherapy patient information;

[0012] A registration unit, used to register and obtain a patient terminal according to radiotherapy patient information;

[0013] The configuration unit is used to formulate multiple information elements based on the medical platform and connect the information elements with the patient end one-to-one.

[0014] In a preferred embodiment, the configuration unit includes:

[0015] A formulation unit, configured to formulate a plurality of information elements in the medical platform, wherein the information elements include a main information plane, a mapping information plane, and an intermediate plane;

[0016] The connection unit is used to match the information element with the patient end, set identifiers for the corresponding information element and the patient end, and bind the information element and the patient end according to the identifier.

[0017] In a preferred embodiment, the formulation unit includes:

[0018] A first setting unit is used to set up multiple data spaces, and set up a main information plane in each data space, wherein the main information plane includes multiple information pools arranged in sequence, and storage time periods are set corresponding to the multiple information pools;

[0019] A second setting unit is configured to set a mapping information plane corresponding to the main information plane in each data space, wherein the mapping information plane includes an information network and a plurality of information points, and the number of the information points is the same as the number of the information pools;

[0020] The third setting unit is used to set an intermediate surface in each data space. The intermediate surface is composed of multiple link points. The information points in the mapping information surface are connected to the information pool in the main information surface in a one-to-one loop through the link points in the intermediate surface.

[0021] In a preferred embodiment, the second setting unit includes:

[0022] A layout unit is used to select a data space plane corresponding to the main information plane in the data space, set a plurality of fixed points on the data space plane, and connect adjacent fixed points to form an information network;

[0023] The binding unit is used to set up multiple information points on the data space surface, set the storage locations of the multiple information points corresponding to the multiple information pools in the data space surface, and bind the multiple information points to the information network.

[0024] In a preferred embodiment, the storage module comprises:

[0025] A storage unit is used to collect radiotherapy monitoring information of the patient, store the radiotherapy monitoring information in the information pool of the main information plane according to the patient end, and store the radiotherapy monitoring information of the storage period in the information pool in the next information pool in sequence;

[0026] A connection opening unit is used to connect the access end to the mapping information plane. When the access end accesses an information point in the mapping information plane, multiple information points in the mapping information plane are connected to the corresponding information pool through the link point in the intermediate plane.

[0027] The access unit is used to cyclically transmit the radiotherapy monitoring information in the information pool to the corresponding information point. When the access terminal pulls the radiotherapy monitoring information in the information point, the information point moves out of the information network through the pulled channel;

[0028] The connection and disconnection unit is used to disconnect the information point from the corresponding information pool when the information point is disconnected from the information network, and the radiotherapy monitoring information in the information point is cleared.

[0029] In a preferred embodiment, the access unit includes:

[0030] An information binding unit, configured to cyclically transmit the radiotherapy monitoring information in the information pool to the corresponding information point at a preset frequency, and bind the information point with the radiotherapy monitoring information;

[0031] The transmission separation unit is used for, when the access terminal pulls the radiotherapy monitoring information in the information point, the information point moves through the channel between the access terminal and the information network, and the information point separates from the information network.

[0032] In a preferred embodiment, the analysis module includes:

[0033] A data collection unit, configured to collect historical medical data, wherein the historical medical data includes historical radiotherapy monitoring information and corresponding analysis results;

[0034] A training unit, used to train the convolutional neural network based on historical medical data to obtain a trained learning model;

[0035] The analysis unit is used to analyze the radiotherapy monitoring information in the information element through a learning model in the medical platform to obtain analysis results.

[0036] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0037] The present invention enables medical data to be viewed by the access terminal through information elements, but cannot be pulled or tampered with by the data, will not affect the analysis results of the medical data, ensures the normal use of medical data while also taking into account the security of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0039] Figure 1 This is a system block diagram of the present invention. DETAILED DESCRIPTION

[0040] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0041] Example 1, please refer to Figure 1 As shown, the present embodiment provides a deep learning-based daily monitoring and management system for radiotherapy patients, including:

[0042] A configuration module is used to determine the patient end of the radiotherapy patient registration information and configure the corresponding information element on the patient end;

[0043] The storage module is connected to the configuration module and is used to collect the patient's radiotherapy monitoring information and store it in the corresponding information element, and access the information element through the access terminal;

[0044] The analysis module is connected to the storage module and is used to analyze the radiotherapy monitoring information in the information element according to the learning model to obtain analysis results, and provide the analysis results to the medical and patient ends.

[0045] In the medical platform, it is necessary to establish information infrastructure such as electronic medical record systems and medical image storage and transmission systems. The construction of these infrastructures provides data support and a technical platform for the daily monitoring and management system of radiotherapy patients based on deep learning. In the field of brain diseases, such as gliomas, brain metastases, and pituitary tumors, radiotherapy is required. In the medical system, the medical data of patients is sensitive information and is easily accessed by ports, without good data security protection. In this application, through information elements, medical data can be viewed by the access terminal, but it cannot be accessed or tampered with, which will not affect the analysis results of the medical data, ensuring the normal use of medical data while also taking into account data security issues.

[0046] In one embodiment, the configuration module includes:

[0047] A collection unit, used for collecting basic information and disease information of radiotherapy patients as radiotherapy patient information;

[0048] A registration unit, used to register and obtain a patient terminal according to radiotherapy patient information;

[0049] A configuration unit, used to formulate multiple information elements based on the medical platform and connect the information elements to the patient end in a one-to-one configuration;

[0050] In one embodiment, the configuration unit includes:

[0051] A formulation unit, configured to formulate a plurality of information elements in the medical platform, wherein the information elements include a main information plane, a mapping information plane, and an intermediate plane;

[0052] The connection unit is used to match the information element with the patient end, set identifiers for the corresponding information element and the patient end, and bind the information element and the patient end according to the identifier.

[0053] In one embodiment, the formulating unit includes:

[0054] A first setting unit is used to set up multiple data spaces, and set up a main information plane in each data space, wherein the main information plane includes multiple information pools arranged in sequence, and storage time periods are set corresponding to the multiple information pools;

[0055] A second setting unit is configured to set a mapping information plane corresponding to the main information plane in each data space, wherein the mapping information plane includes an information network and a plurality of information points, and the number of the information points is the same as the number of the information pools;

[0056] The third setting unit is used to set an intermediate surface in each data space. The intermediate surface is composed of multiple link points. The information points in the mapping information surface are connected to the information pool in the main information surface in a one-to-one loop through the link points in the intermediate surface.

[0057] In one embodiment, the second setting unit includes:

[0058] A layout unit is used to select a data space plane corresponding to the main information plane in the data space, set a plurality of fixed points on the data space plane, and connect adjacent fixed points to form an information network;

[0059] A binding unit is used to set a plurality of information points on the data space plane, set the storage locations of the plurality of information points corresponding to the plurality of information pools in the data space plane, and bind the plurality of information points to the information network;

[0060] It should be noted that the daily monitoring data of radiotherapy patients needs to be stored in the medical platform. Therefore, the basic information and disease information of radiotherapy patients need to be collected in advance as radiotherapy patient information. The patient end is obtained according to the radiotherapy patient information registration. The patient end is used as a port for data storage and retrieval. During the data storage process, operations need to be performed on the medical platform, which can facilitate subsequent data analysis to understand the patient's radiotherapy status. There is a data device in the medical platform. In this data space, multiple data spaces specifically for corresponding patient ends are formulated. One data space corresponds to one patient end, which can make the data storage better isolated. Information elements are set in each data space. The information elements include the main information surface, the mapping information surface and the intermediate surface. The main information surface is a partial data space divided out in the data space. Multiple information pools are obtained by dividing in the partial data space, corresponding to multiple information Each pool specifies a corresponding storage period, meaning that upon subsequent use, an information pool can store radiotherapy monitoring information for the corresponding storage period. A mapping information plane is set in each data space corresponding to the main information plane. Specifically, a data space plane (a data space plane is a data storage space with a planar structure) is selected in the data space corresponding to the main information plane. Multiple fixed points (network points) are set on the data space plane. Adjacent fixed points are connected to form an information network. Multiple information points (information points are virtual machines used to store radiotherapy monitoring information transmitted from the information pool in the information plane) are set on the data space plane. The storage locations of the multiple information points corresponding to the multiple information pools are set in the data space plane. The multiple information points are bound to the information network. The virtual machines of the information points can be bound to the fixed points in the information network, which can limit the location of the virtual machines. The fixed point settings are fixed, and the multiple information points are deeply bound to the information network. The virtual machines of the information points can be bound to the fixed points in the information network. This binding relationship is based on a specific identification and addressing mechanism. Each fixed point has a unique identifier, and the information point establishes a connection with the fixed point through this identifier.The setting of fixed points is fixed, providing a stable anchor point for information points. An intermediate surface (data storage space with a surface structure) is set in each data space. The intermediate surface is composed of multiple link points. The link point here is the transmission end. The information points in the mapping information surface and the information pool in the main information surface are connected one-to-one through the link point in the intermediate surface. The number of link points is the same as the number of information pools. According to the storage position, the information points and the information pool can be matched one-to-one. The corresponding information points can be connected to the information pool through the link point. The connection is made in the form of information point-link point-information pool. Here The circular connection is that the information pool will continuously transmit the radiotherapy monitoring information stored in it to the information point. The information point only stores the radiotherapy monitoring information for a short time and then automatically destroys it, and continuously receives radiotherapy monitoring information from the information pool. In this way, when a security problem occurs, the connection between the information point-link point-information pool can be directly disconnected to prevent the radiotherapy monitoring information from being maliciously obtained. In addition, in the newly stored information pool, the real-time nature of the data can be guaranteed by continuously transmitting it to the information point, and it can be viewed by the access port. Here, the access port is only allowed to view the information and is not allowed to copy the information or pull data by other means.

[0061] In one embodiment, the storage module comprises:

[0062] A storage unit is used to collect radiotherapy monitoring information of the patient, store the radiotherapy monitoring information in the information pool of the main information plane according to the patient end, and store the radiotherapy monitoring information of the storage period in the information pool in the next information pool in sequence;

[0063] A connection opening unit is used to connect the access end to the mapping information plane. When the access end accesses an information point in the mapping information plane, multiple information points in the mapping information plane are connected to the corresponding information pool through the link point in the intermediate plane.

[0064] The access unit is used to cyclically transmit the radiotherapy monitoring information in the information pool to the corresponding information point. When the access terminal pulls the radiotherapy monitoring information in the information point, the information point moves out of the information network through the pulled channel;

[0065] A connection and disconnection unit is used to disconnect the information point from the corresponding information pool when the information point is disconnected from the information network, and clear the radiotherapy monitoring information in the information point;

[0066] In one embodiment, the access unit includes:

[0067] An information binding unit, configured to cyclically transmit the radiotherapy monitoring information in the information pool to the corresponding information point at a preset frequency, and bind the information point with the radiotherapy monitoring information;

[0068] The transmission separation unit is used for, when the access terminal pulls the radiotherapy monitoring information in the information point, the information point moves through the channel between the access terminal and the information network, and the information point separates from the information network.

[0069] It should be noted that the collected radiotherapy monitoring information of the patient is stored according to the patient end, and is stored in the information pool in the main information surface corresponding to the patient end. The information pool is arranged in sequence. One information pool can store the radiotherapy monitoring information of the corresponding storage period. After the information pool stores the radiotherapy monitoring information of the storage period, it is stored in the next information pool in sequence. The access end is connected to the mapping information surface, and the access end and the information points in the mapping information surface are connected through a channel. When there is an access end accessing an information point in the mapping information surface, multiple information points in the mapping information surface are connected to the corresponding information pool through the link point in the middle surface, and the radiotherapy monitoring information in the information pool is cyclically transmitted to the corresponding information point at a preset frequency. For example, the radiotherapy monitoring information in the information pool is transmitted once every two seconds, and the information point is bound to the radiotherapy monitoring information. The radiotherapy monitoring information cannot be separated from the information point. If the radiotherapy monitoring information in the information point is to be pulled, The information point will also be pulled; when the access terminal pulls the radiotherapy monitoring information in the information point, the information point moves through the channel between the access terminal and the information network, and the information point is separated from the information network. After the information point is separated from the information network, the information point will lose the ability to connect to the link point, disconnect the connection between the information point and the corresponding information pool, and the radiotherapy monitoring information in the information point will be cleared. Since the information point has no long-term storage function for radiotherapy monitoring information and the update frequency is high, after the information point is disconnected from the information pool, there is no continuous information supplement from the information pool, and the radiotherapy monitoring information in the information point no longer exists and is in a cleared state. The medical data can be viewed by the access terminal through the information element, but it cannot be pulled or tampered with by the data, which will not affect the analysis results of the medical data. While ensuring the normal use of medical data, it also takes into account the security of the data. The security status of the information element can be understood through the security index, where the calculation formula of the security index is: in, is the safety index, n z is the number of times an information point leaves the information network, θ is the number of information points that have left the information network, and β is a constant greater than zero. The larger the value of the security index, the lower the security of the information element. This can be known to system personnel to strengthen system security inspections.

[0070] In one embodiment, the analysis module includes:

[0071] A data collection unit, configured to collect historical medical data, wherein the historical medical data includes historical radiotherapy monitoring information and corresponding analysis results;

[0072] A training unit, used to train the convolutional neural network based on historical medical data to obtain a trained learning model;

[0073] An analysis unit, configured to analyze the radiotherapy monitoring information in the information element through a learning model in the medical platform to obtain an analysis result;

[0074] It should be noted that historical radiotherapy monitoring information and corresponding analysis results are collected. Historical radiotherapy monitoring information is the imaging data of patients during radiotherapy obtained through various medical equipment such as CT and MRI, as well as the physiological data of patients collected through sensors, such as heart rate, blood pressure, respiration, etc. The analysis results here are tumor-related data (changes in tumor size, tumor shape and tumor density), physiological data characteristics (vital signs data and changes in blood indicators) and image texture features (image grayscale value distribution and texture complexity and roughness). The convolutional neural network is trained based on historical medical data to obtain a trained learning model. The radiotherapy monitoring information in the information element is analyzed by the learning model in the medical platform to obtain the analysis result. The analysis result is the above-mentioned content data. In this way, when brain diseases occur, radiotherapy can be used for treatment, the patient's condition can be monitored, and the analysis results can be provided to the medical and patient ends for review. The brain diseases here include gliomas, brain metastases and pituitary tumors.

[0075] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A daily monitoring and management system for radiotherapy patients based on deep learning, characterized by: include: A configuration module is used to determine the patient end of the radiotherapy patient registration information and configure the corresponding information element on the patient end; The storage module is connected to the configuration module and is used to collect the patient's radiotherapy monitoring information and store it in the corresponding information element, and access the information element through the access terminal; The analysis module is connected to the storage module and is used to analyze the radiotherapy monitoring information in the information element according to the learning model to obtain analysis results, and provide the analysis results to the medical and patient ends.

2. A daily monitoring and management system for radiotherapy patients based on deep learning according to claim 1, characterized in that: The configuration module includes: A collection unit, used for collecting basic information and disease information of radiotherapy patients as radiotherapy patient information; A registration unit, used to register and obtain a patient terminal according to radiotherapy patient information; The configuration unit is used to formulate multiple information elements based on the medical platform and connect the information elements with the patient end one-to-one.

3. The deep learning-based daily monitoring and management system for radiotherapy patients according to claim 2, characterized in that: The configuration unit includes: A formulation unit, configured to formulate a plurality of information elements in the medical platform, wherein the information elements include a main information plane, a mapping information plane, and an intermediate plane; The connection unit is used to match the information element with the patient end, set identifiers for the corresponding information element and the patient end, and bind the information element and the patient end according to the identifier.

4. The deep learning-based daily monitoring and management system for radiotherapy patients according to claim 3 is characterized by: The formulation unit includes: A first setting unit is used to set up multiple data spaces, and set up a main information plane in each data space, wherein the main information plane includes multiple information pools arranged in sequence, and storage time periods are set corresponding to the multiple information pools; A second setting unit is configured to set a mapping information plane corresponding to the main information plane in each data space, wherein the mapping information plane includes an information network and a plurality of information points, and the number of the information points is the same as the number of the information pools; The third setting unit is used to set an intermediate surface in each data space. The intermediate surface is composed of multiple link points. The information points in the mapping information surface are connected to the information pool in the main information surface in a one-to-one loop through the link points in the intermediate surface.

5. The deep learning-based daily monitoring and management system for radiotherapy patients according to claim 4 is characterized by: The second setting unit includes: A layout unit is used to select a data space plane corresponding to the main information plane in the data space, set a plurality of fixed points on the data space plane, and connect adjacent fixed points to form an information network; The binding unit is used to set up multiple information points on the data space surface, set the storage locations of the multiple information points corresponding to the multiple information pools in the data space surface, and bind the multiple information points to the information network.

6. The deep learning-based daily monitoring and management system for radiotherapy patients according to claim 5, characterized in that: The storage module includes: A storage unit is used to collect radiotherapy monitoring information of the patient, store the radiotherapy monitoring information in the information pool of the main information plane according to the patient end, and store the radiotherapy monitoring information of the storage period in the information pool in the next information pool in sequence; A connection opening unit is used to connect the access end to the mapping information plane. When the access end accesses an information point in the mapping information plane, multiple information points in the mapping information plane are connected to the corresponding information pool through the link point in the intermediate plane. The access unit is used to cyclically transmit the radiotherapy monitoring information in the information pool to the corresponding information point. When the access terminal pulls the radiotherapy monitoring information in the information point, the information point moves out of the information network through the pulled channel; The connection and disconnection unit is used to disconnect the information point from the corresponding information pool when the information point is disconnected from the information network, and the radiotherapy monitoring information in the information point is cleared.

7. The deep learning-based daily monitoring and management system for radiotherapy patients according to claim 6, characterized in that: The access unit includes: An information binding unit, configured to cyclically transmit the radiotherapy monitoring information in the information pool to the corresponding information point at a preset frequency, and bind the information point with the radiotherapy monitoring information; The transmission separation unit is used for, when the access terminal pulls the radiotherapy monitoring information in the information point, the information point moves through the channel between the access terminal and the information network, and the information point separates from the information network.

8. The deep learning-based daily monitoring and management system for radiotherapy patients according to claim 1, characterized in that: The analysis module includes: A data collection unit, configured to collect historical medical data, wherein the historical medical data includes historical radiotherapy monitoring information and corresponding analysis results; A training unit, used to train the convolutional neural network based on historical medical data to obtain a trained learning model; The analysis unit is used to analyze the radiotherapy monitoring information in the information element through a learning model in the medical platform to obtain analysis results.

Images