Radiotherapy medication collaborative management method and system based on digital twinning

Abstract

The invention relates to the technical field of digital twinborn biology, in particular to a radiotherapy medication collaborative management method and system based on digital twinborn, and the method comprises the steps: obtaining a tumor organ simulation model corresponding to a tumor object according to a content identifier; according to the radiotherapy-medication scheme, performing simulation implementation on the tumor organ simulation model to obtain a simulation implementation effect score; when the simulation implementation effect score is greater than a preset implementation standard, outputting the radiotherapy-medication scheme as an effective medical scheme; performing scheme implementation operation on the tumor object by utilizing an effective medical scheme to obtain real pathological change information, and updating the tumor organ simulation model by utilizing the real pathological change information to obtain an updated tumor organ simulation model; generating an updated content identifier corresponding to the updated tumor organ simulation model; and according to a pre-constructed identity identifier, carrying out block chain uplink operation on the updated content identifier. According to the invention, the radiotherapy and medication accuracy can be improved.

Description

Technical Field

[0001] This invention relates to the field of digital twin biotechnology, and in particular to a method and system for collaborative management of radiotherapy medication based on digital twins. Background Technology

[0002] Traditionally, radiotherapy and medication management are independent of each other. Radiotherapy plans are formulated by the radiotherapy department, while medication plans are formulated separately by the chemotherapy department or internal medicine department. The lack of information exchange and collaborative decision-making between the two can easily lead to problems such as conflicting medical plans and dosage superposition that exacerbates adverse reactions.

[0003] Therefore, there is currently a lack of a coordinated management mechanism for radiotherapy and medication, making it impossible to achieve integrated planning for both. Summary of the Invention

[0004] This invention provides a method for collaborative management of radiotherapy medication based on digital twins, the main purpose of which is to improve the accuracy of radiotherapy and medication administration.

[0005] To achieve the above objectives, the present invention provides a method for collaborative management of radiotherapy medication based on digital twins, comprising:

[0006] When the pre-built radiotherapy medication collaborative management terminal receives the radiotherapy-medication plan sent by the doctor, it obtains the doctor object and the tumor object from the radiotherapy-medication plan, and uses the pre-built verification smart contract to verify the responsibility relationship between the doctor object and the tumor object to obtain the relationship verification result.

[0007] When the relationship verification result is successful, the content identifier corresponding to the tumor object is obtained using the radiotherapy drug collaborative management terminal, and the tumor organ simulation model corresponding to the tumor object is obtained from the pre-built distributed storage system based on the content identifier.

[0008] According to the radiotherapy-drug regimen, the tumor organ simulation model is simulated and implemented to obtain a simulation implementation effect score;

[0009] When the simulated implementation effect score is greater than the preset implementation standard, the radiotherapy-medication plan is determined to be a preset qualified plan, and the radiotherapy-medication plan is output as an effective medical plan;

[0010] Using the effective medical plan, the tumor object is subjected to the plan implementation operation to obtain real pathological change information, and the tumor organ simulation model is updated using the real pathological change information according to the content identifier to obtain an updated tumor organ simulation model.

[0011] Using the distributed storage system, an update content identifier corresponding to the updated tumor organ simulation model is generated;

[0012] Using a pre-built automatic on-chain smart contract, the updated content identifier is on-chained on the blockchain based on the pre-built identity identifier.

[0013] Optionally, before the pre-built radiotherapy medication collaborative management terminal receives the radiotherapy-medication plan sent by the doctor, the method further includes:

[0014] Using a pre-built tumor management terminal, the pathological information of the target tumor is obtained, and tumor organ simulation modeling is performed on the pathological information of the target tumor to obtain a tumor organ simulation model.

[0015] The tumor organ simulation model is sent to a pre-built distributed storage system for distributed storage, and the content identifier fed back by the distributed storage system is obtained.

[0016] Using a pre-built physically unclonable function, an identity identifier is constructed for the tumor organ simulation model. Based on the identity identifier, a blockchain-based encrypted on-chain operation is performed on the content identifier to obtain a tumor on-chain identity credential fed back by the blockchain.

[0017] Optionally, the step of performing tumor organ simulation modeling on the target tumor pathological information to obtain a tumor organ simulation model includes:

[0018] Acquire genomic data, radiotherapy dose data, medical imaging structural data, and real-time physiological detection data from the target tumor pathology information;

[0019] An initial tumor model is obtained, and the basic structure of the initial tumor model is adjusted using the genomic data, radiotherapy dose data, and medical imaging structure data to obtain a three-dimensional model of the tumor organ.

[0020] Using a pre-constructed physiological function simulation model, the three-dimensional model of the tumor organ is functionally configured to obtain a primary model of the tumor organ;

[0021] The real-time physiological detection data is subjected to a Transformer-based tumor development trend prediction operation to obtain a tumor development trend model;

[0022] Using the tumor development trend model, the development process of the primary model of the tumor organ is configured to obtain a tumor organ simulation model.

[0023] Optionally, the step of using a pre-built verification smart contract to verify the responsibility relationship between the doctor and the tumor object, and obtaining the relationship verification result, includes:

[0024] Using a pre-built verification smart contract, the validity of the doctor's credentials is verified, and the doctor's credentials verification result is obtained.

[0025] The validity of the credential for the tumor object is verified to obtain the tumor credential verification result.

[0026] The responsibility relationship between the physician and the tumor patient was verified to obtain the corresponding relationship verification results.

[0027] When the verification results of the doctor's certificate, the tumor certificate, and the corresponding relationship are all verified, the relationship verification result is determined to be verified.

[0028] Optionally, when the relationship verification result is successful, the radiotherapy medication collaborative management terminal is used to obtain the content identifier corresponding to the tumor object, and based on the content identifier, the tumor organ simulation model corresponding to the tumor object is obtained from the pre-built distributed storage system, including:

[0029] When the relationship verification result is successful, a session key is generated using the radiotherapy medication collaborative management terminal, and the session key is sent to the tumor management terminal;

[0030] Using the tumor management terminal, the content identifier corresponding to the tumor object is queried, and the content identifier is encrypted according to the session key to obtain an encrypted content identifier, which is then sent to the radiotherapy medication collaborative management terminal.

[0031] Using the radiotherapy medication collaborative management terminal, the encrypted content identifier is decrypted according to the session key to obtain the content identifier, and the tumor organ simulation model corresponding to the tumor object is obtained from the pre-built distributed storage system according to the content identifier.

[0032] Optionally, the step of simulating the tumor organ model according to the radiotherapy-drug regimen to obtain a simulation effect score includes:

[0033] The radiotherapy-medication regimen is subjected to text segmentation and quantization to obtain a set of segmented vectors;

[0034] Perform medical feature extraction on the word segmentation vector set to obtain a medical feature vector set;

[0035] Using the tumor organ simulation model, a tumor evolution prediction operation based on virtual implementation is performed according to the medical feature vector set to obtain a predicted tumor organ simulation model.

[0036] By comparing the tumor organ simulation model with the predicted tumor organ simulation model, a simulation implementation effect score is obtained.

[0037] Optionally, the step of comparing the tumor organ simulation model with the predicted tumor organ simulation model to obtain a simulation implementation effect score includes:

[0038] Data information of the tumor organ simulation model and the predicted tumor organ simulation model based on a preset set of indicators is obtained to obtain a simulation model information set and a prediction model information set;

[0039] Obtain a set of standard indicator information, calculate the difference between the set of standard indicator information and the set of simulation model information on each indicator to obtain a simulation indicator difference sequence, and calculate the difference between the set of standard indicator information and the set of prediction model information on each indicator to obtain a prediction indicator difference sequence.

[0040] Based on the preset index weight coefficients, the simulation index difference in the simulation index difference sequence is weighted and calculated to obtain the simulation comprehensive evaluation score; the prediction index difference in the prediction index difference sequence is weighted and calculated to obtain the prediction comprehensive evaluation score.

[0041] The difference between the predicted comprehensive evaluation score and the simulated comprehensive evaluation score is calculated to obtain the simulated implementation effect score.

[0042] Optionally, after obtaining the actual pathological change information, the method further includes:

[0043] Obtain information on predicted pathological changes from the tumor organ simulation model;

[0044] The loss value between the actual pathological change information and the predicted pathological change information is calculated based on the pre-constructed cross-entropy loss algorithm.

[0045] The loss value is minimized according to the pre-built gradient descent algorithm to obtain the network update parameters;

[0046] Using the network update parameters, a reverse network parameter update operation is performed on the tumor development trend model to obtain an optimized tumor development trend model.

[0047] Optionally, after outputting the radiotherapy-medication regimen as an effective medical plan, the method further includes:

[0048] Obtain the identity identifier from the tumor management terminal;

[0049] Using a pre-built log device, based on the identity identifier, the operation records of the responsibility relationship verification process are obtained according to a preset monitoring frequency to obtain access records;

[0050] The access records are subjected to abnormal behavior identification to obtain abnormal behavior identification results.

[0051] To achieve the above objectives, the present invention also provides a radiotherapy medication collaborative management system based on digital twins, comprising:

[0052] The object verification module is used to obtain the doctor object and tumor object from the radiotherapy-medication plan when the pre-built radiotherapy medication collaborative management terminal receives the radiotherapy-medication plan sent by the doctor, and to verify the responsibility relationship between the doctor object and the tumor object using the pre-built verification smart contract to obtain the relationship verification result.

[0053] The scheme verification module is used to obtain the content identifier corresponding to the tumor object using the radiotherapy-medication collaborative management terminal when the relationship verification result is successful, and to obtain the tumor organ simulation model corresponding to the tumor object from the pre-built distributed storage system based on the content identifier. The module then simulates the implementation of the tumor organ simulation model according to the radiotherapy-medication scheme to obtain a simulation implementation effect score. When the simulation implementation effect score is greater than the preset implementation standard, the module determines that the radiotherapy-medication scheme is a preset qualified scheme and outputs the radiotherapy-medication scheme as an effective medical scheme.

[0054] The scheme implementation module is used to implement the scheme on the tumor object using the effective medical scheme, obtain real pathological change information, update the tumor organ simulation model using the real pathological change information according to the content identifier, obtain an updated tumor organ simulation model, and generate an updated content identifier corresponding to the updated tumor organ simulation model using the distributed storage system.

[0055] The solution on-chain module is used to perform blockchain on-chain operations on the updated content identifier based on the pre-built identity identifier using a pre-built automatic on-chain smart contract.

[0056] To address the above problems, the present invention also provides an electronic device, the electronic device comprising:

[0057] Memory, storing at least one instruction;

[0058] The processor executes the instructions stored in the memory to implement the above-described method for collaborative management of radiotherapy medication based on digital twins.

[0059] To address the aforementioned issues, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the aforementioned digital twin-based radiotherapy medication collaborative management method.

[0060] To address the problems described in the background section, this invention first verifies the physician and tumor subjects of the radiotherapy-medication regimen to ensure the accuracy of the regimen's source and subjects. Then, it acquires a distributed storage tumor organ simulation model using content identifiers and simulates the implementation of the tumor organ model using the radiotherapy-medication regimen, obtaining a simulation effectiveness score. This invention utilizes digital twin technology to simulate tumor organ tissue, thereby ensuring the effectiveness of each radiotherapy-medication regimen. Furthermore, each time medication or radiotherapy is administered, the radiotherapy-medication regimen is recorded offline and online, and the tumor organ simulation model is updated. This ensures that each radiotherapy or medication regimen is a further design based on all current medical regimens, avoiding conflicts or duplicate treatments. Therefore, this invention can improve the accuracy of radiotherapy and medication administration. Attached Figure Description

[0061] Figure 1 This is a flowchart illustrating a method for collaborative management of radiotherapy medication based on digital twins, provided in an embodiment of the present invention.

[0062] Figure 2 A functional block diagram of a radiotherapy medication collaborative management system based on digital twins provided in an embodiment of the present invention;

[0063] Figure 3 This is a schematic diagram of the structure of an electronic device for implementing the digital twin-based radiotherapy medication collaborative management method according to an embodiment of the present invention.

[0064] Explanation of reference numerals in the attached figures:

[0065] 10. Electronic device; 11. Processor; 12. Memory; 13. Bus.

[0066] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0067] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0068] This application provides a method for collaborative management of radiotherapy medication based on digital twins. The executing entity of this method includes, but is not limited to, at least one electronic device that can be configured to execute the method provided in this application, such as a server or a terminal. In other words, the method can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0069] Reference Figure 1 The diagram shown is a flowchart illustrating a digital twin-based collaborative management method for radiotherapy medications according to an embodiment of the present invention. In this embodiment, the digital twin-based collaborative management method for radiotherapy medications includes:

[0070] S1. When the pre-built radiotherapy medication collaborative management terminal receives the radiotherapy-medication plan sent by the doctor, it obtains the doctor object and the tumor object from the radiotherapy-medication plan, and uses the pre-built verification smart contract to verify the responsibility relationship between the doctor object and the tumor object, and obtains the relationship verification result.

[0071] The radiotherapy medication collaborative management terminal refers to a client operated by a doctor, which is used to record and predict the effects of the radiotherapy plan or medication plan provided by the doctor, thereby ensuring the effectiveness of each medical plan and preventing conflicts between the plans.

[0072] The radiotherapy-medication plan refers to any medical plan such as "radiotherapy plan" or "medication plan". Only one radiotherapy-medication plan can be entered at a given time.

[0073] Here, the "doctor" refers to the person who formulates the medical plan, such as a certain doctor. The "tumor" refers to the target tumor being treated, such as a tumor in part C of organ B on person A.

[0074] The aforementioned verification smart contract refers to a program that can automatically execute predetermined verification functions.

[0075] The aforementioned responsibility relationship verification refers to the process of verifying whether the physician and the tumor have passed the verification, such as verifying whether the physician is a doctor of this hospital, whether the physician's level and department correspond, whether the patient is a patient of this hospital, and whether the physician is the patient's responsible physician.

[0076] The relationship verification result refers to the execution result of the responsibility relationship verification operation, including two results: "verification passed" and "verification failed".

[0077] In detail, in this embodiment of the invention, the step of using a pre-built verification smart contract to verify the responsibility relationship between the doctor and the tumor object, and obtaining the relationship verification result, includes:

[0078] Using a pre-built verification smart contract, the validity of the doctor's credentials is verified, and the doctor's credentials verification result is obtained.

[0079] The validity of the credential for the tumor object is verified to obtain the tumor credential verification result.

[0080] The responsibility relationship between the physician and the tumor patient was verified to obtain the corresponding relationship verification results.

[0081] When the verification results of the doctor's certificate, the tumor certificate, and the corresponding relationship are all verified, the relationship verification result is determined to be verified.

[0082] The verification of the credentials refers to the process of verifying whether the identity information of the doctor and the tumor patient is valid.

[0083] The doctor's credentials verification result refers to the result of verifying the doctor's identity information. The tumor credentials verification result refers to the result of verifying the tumor patient's information.

[0084] The responsibility relationship verification refers to the process of determining whether there is a responsibility relationship between the physician and the tumor. The correspondence verification result refers to the result of determining whether there is a responsibility relationship between the physician and the tumor.

[0085] Specifically, in this embodiment of the invention, the identity information of the doctor, such as the delegation relationship, doctor's level, and professional field, is verified through a smart contract to ensure the validity of the radiotherapy-medication plan. Then, the validity of the credentials for the tumor patient is verified, such as whether the patient's identity is correct and whether the condition corresponds to the diagnosis, thereby avoiding incorrect medical plans and improving the targeting of the treatment. Once the identity information of both the doctor and the tumor patient is confirmed, it can be determined whether there is a responsibility relationship between them, thus avoiding management conflicts.

[0086] Specifically, in this embodiment of the invention, after all the verification processes in the responsibility relationship verification operation have passed, the relationship verification result of "verification passed" can be output.

[0087] In detail, in this embodiment of the invention, before the pre-built radiotherapy medication collaborative management terminal receives the radiotherapy-medication plan sent by the doctor, the method further includes:

[0088] Using a pre-built tumor management terminal, the pathological information of the target tumor is obtained, and tumor organ simulation modeling is performed on the pathological information of the target tumor to obtain a tumor organ simulation model.

[0089] The tumor organ simulation model is sent to a pre-built distributed storage system for distributed storage, and the content identifier fed back by the distributed storage system is obtained.

[0090] Using a pre-built physically unclonable function, an identity identifier is constructed for the tumor organ simulation model. Based on the identity identifier, a blockchain-based encrypted on-chain operation is performed on the content identifier to obtain a tumor on-chain identity credential fed back by the blockchain.

[0091] The tumor management terminal refers to a device that acquires various information about tumor subjects and stores it in a distributed manner.

[0092] The target tumor pathology information refers to comprehensive information about the target tumor, including basic data (such as medical records, medical imaging information, genomics data, etc.), real-time information (real-time data on various bodily indicators, such as blood pressure, blood sugar, etc.), and medical data (implementation progress of medical plans, drug content in the body, radiotherapy dose data, etc.).

[0093] The tumor organ simulation modeling refers to the process of virtually replicating a tumor organ using digital twin technology. The tumor organ simulation model refers to the modeling result of the tumor organ simulation modeling process.

[0094] The distributed storage system is configured as the InterPlanetary File System (IPFS), which can distribute the data of the tumor organ simulation model across multiple nodes, improving data security and availability and avoiding single points of failure.

[0095] The Content Identifier (CID) is a unique hash value used to locate data in the IPFS system, similar to a digital fingerprint of a file, ensuring data integrity and addressability.

[0096] The Physically Unclonable Function (PUF) is used to generate a unique identifier that cannot be copied or cloned by utilizing the inherent random physical characteristics of hardware, thus providing hardware-level identity authentication for the tumor object.

[0097] The identity identifier refers to a unique identifier that provides hardware-level identity authentication for the tumor object.

[0098] The blockchain-based encrypted on-chain operation refers to the process of converting the content identifier into an encrypted content identifier and then storing the encrypted content identifier in the blockchain.

[0099] The tumor on-chain identity certificate is a digital identity certificate representing the patient, indicating that the patient can view the data stored in the blockchain at any time.

[0100] Specifically, in this embodiment of the invention, the pathological information of the target tumor is first obtained through the tumor management terminal, and then the tumor organ simulation model is obtained by using digital twin technology. However, since the tumor organ simulation model is sensitive patient information and should not be disclosed, this invention requires confidentiality measures.

[0101] Specifically, this invention uses the InterPlanetary File System (IPS) to distribute the storage of tumor organ simulation models, obtains the IPS content identifier (i.e., index information), and then uploads the content identifier to the blockchain, thereby achieving offline data storage and online index storage.

[0102] In the process of putting the content identifier on the blockchain, it is necessary to construct the identity identifier of the tumor organ simulation model based on the physical non-cloning function, so as to ensure that the tumor on-chain identity certificate is obtained through blockchain identity verification.

[0103] In detail, in this embodiment of the invention, the step of performing tumor organ simulation modeling on the target tumor pathological information to obtain a tumor organ simulation model includes:

[0104] Acquire genomic data, radiotherapy dose data, medical imaging structural data, and real-time physiological detection data from the target tumor pathology information;

[0105] An initial tumor model is obtained, and the basic structure of the initial tumor model is adjusted using the genomic data, radiotherapy dose data, and medical imaging structure data to obtain a three-dimensional model of the tumor organ.

[0106] Using a pre-constructed physiological function simulation model, the three-dimensional model of the tumor organ is functionally configured to obtain a primary model of the tumor organ;

[0107] The real-time physiological detection data is subjected to a Transformer-based tumor development trend prediction operation to obtain a tumor development trend model;

[0108] Using the tumor development trend model, the development process of the primary model of the tumor organ is configured to obtain a tumor organ simulation model.

[0109] The genomic data refers to a digital data set that reflects the genetic information of an organism's whole genome, obtained through gene sequencing technology, including information such as DNA sequence, gene expression level, and genetic variation.

[0110] The medical imaging structural data refers to digital data that reflects the anatomical structure and tissue morphology of the human body, acquired through medical imaging equipment, including CT images, magnetic resonance imaging, and ultrasound imaging, etc.

[0111] The radiotherapy dose data refers to the quantitative numerical indicators used to determine the irradiation dose, distribution method, and safety limits in the radiotherapy plan, obtained through radiotherapy equipment. These include prescription dose-related data, target area dose assessment data, and normal tissue dose limit data.

[0112] The real-time physiological monitoring data refers to dynamic data reflecting the physiological function status of the human body, which is continuously collected through various sensors and monitoring devices, including vital signs, biochemical indicators, and electrophysiological signals.

[0113] The initial tumor model refers to a visualized organ model whose three-dimensional structure is determined but whose gene content is not filled.

[0114] The basic structure adjustment operation refers to the process of filling the initial tumor model with genomic data and modifying the visualization structure of the initial tumor model according to radiotherapy dose data and medical imaging structure data.

[0115] The three-dimensional modeling of tumor organs refers to the initialization of the tumor model by adjusting its genetic composition and morphological structure.

[0116] The physiological function simulation model refers to a model based on biomechanics and fluid dynamics, used to simulate processes such as blood circulation and nerve conduction.

[0117] The "functional configuration" refers to the process of adding dynamic functions to a static 3D model of a tumor organ. The "primary tumor organ modeling" refers to the 3D model of a tumor organ after functional configuration.

[0118] The Transformer-based tumor development trend prediction operation refers to the process of using a large Transformer model to analyze the data correlations in the real-time physiological monitoring data, thereby predicting the tumor development trend. The tumor development trend model is a regression prediction network model that has learned the relationship between time and tumor development trend from the real-time physiological monitoring data.

[0119] The development process configuration refers to the process of configuring the relationship between tumor changes and time in the primary modeling of the tumor organ to conform to the prediction results of the tumor development trend model.

[0120] Specifically, in this embodiment of the invention, the construction of digital twins of organs and tissues is a complex process involving multiple disciplines. This invention requires integrating multi-source data to obtain target tumor pathological information, and then using this multimodal target tumor pathological information to perform basic structural adjustments on the initial tumor model, thereby obtaining a three-dimensional model of the tumor organ and completing the construction of the basic structure.

[0121] Then, this invention requires AI-driven modeling technology to simulate processes such as blood circulation and nerve conduction through physiological function simulation models, such as biomechanical and fluid dynamics models, to perform functional configuration on the three-dimensional model of the tumor organ, thereby obtaining a primary model of the tumor organ. Finally, the data correlation in the real-time physiological detection data is analyzed through a Transformer large model to predict the process of tumor development trend, thereby obtaining a tumor development trend model. Then, the development process of the primary model of the tumor organ is configured using the tumor development trend model to obtain a tumor organ simulation model.

[0122] S2. When the relationship verification result is successful, the content identifier corresponding to the tumor object is obtained using the radiotherapy drug collaborative management terminal, and the tumor organ simulation model corresponding to the tumor object is obtained from the pre-built distributed storage system based on the content identifier.

[0123] In detail, in this embodiment of the invention, when the relationship verification result is successful, the content identifier corresponding to the tumor object is obtained using the radiotherapy drug collaborative management terminal, and the tumor organ simulation model corresponding to the tumor object is obtained from the pre-built distributed storage system based on the content identifier, including:

[0124] When the relationship verification result is successful, a session key is generated using the radiotherapy medication collaborative management terminal, and the session key is sent to the tumor management terminal;

[0125] Using the tumor management terminal, the content identifier corresponding to the tumor object is queried, and the content identifier is encrypted according to the session key to obtain an encrypted content identifier, which is then sent to the radiotherapy medication collaborative management terminal.

[0126] Using the radiotherapy medication collaborative management terminal, the encrypted content identifier is decrypted according to the session key to obtain the content identifier, and the tumor organ simulation model corresponding to the tumor object is obtained from the pre-built distributed storage system according to the content identifier.

[0127] The session key, abbreviated as SK, is a temporarily generated encryption key that is only valid within the current session. It is used to encrypt and decrypt communication data to ensure the secure transmission of the content identifier.

[0128] The encryption refers to the process of calculating the content identifier using an MD4 or MD5 hash function and the session key.

[0129] The encrypted content identifier refers to the CID encrypted with SK.

[0130] Here, decryption refers to the reverse process of the above-mentioned "encryption" process.

[0131] Specifically, in this embodiment of the invention, to ensure the privacy of tumor data, the data acquisition process of the target tumor pathology information and the data storage process of the tumor organ simulation model are both isolated and controlled through the tumor management terminal.

[0132] However, when validating the radiotherapy-drug regimen, the present invention needs to extract a tumor organ simulation model for digital twin simulation. Therefore, the present invention needs to encrypt the data transmission process to ensure the data security of CID.

[0133] Specifically, this invention uses a tumor management terminal to manage the CID, then encrypts the CID to obtain an encrypted CID, and then sends the encrypted CID to the radiotherapy drug co-management terminal. The radiotherapy drug co-management terminal then uses a pre-built SK to decrypt the encrypted CID, thereby obtaining the CID managed by the tumor management terminal. Based on the CID, it directly accesses the distributed storage system to obtain the tumor organ simulation model corresponding to the tumor object.

[0134] Through the above structure, this invention enables the data management and calling format of the tumor management terminal "managing" and the radiotherapy drug co-management terminal "calling", thereby improving the independence of the tumor organ simulation model.

[0135] S3. Based on the radiotherapy-drug regimen, the tumor organ simulation model is simulated and implemented to obtain a simulation implementation effect score.

[0136] The simulation implementation refers to the process of virtually implementing a tumor organ simulation model according to a radiotherapy-medication plan using digital twin technology.

[0137] The simulated implementation effect score refers to the score representing the simulated implementation effect.

[0138] In detail, in this embodiment of the invention, the step of simulating the tumor organ simulation model according to the radiotherapy-drug regimen to obtain a simulation effect score includes:

[0139] The radiotherapy-medication regimen is subjected to text segmentation and quantization to obtain a set of segmented vectors;

[0140] Perform medical feature extraction on the word segmentation vector set to obtain a medical feature vector set;

[0141] Using the tumor organ simulation model, a tumor evolution prediction operation based on virtual implementation is performed according to the medical feature vector set to obtain a predicted tumor organ simulation model.

[0142] By comparing the tumor organ simulation model with the predicted tumor organ simulation model, a simulation implementation effect score is obtained.

[0143] The text segmentation and quantization process is a complete workflow that converts unstructured natural language text into a structured digital representation that can be understood by machine learning models. It includes two processes: segmentation and quantization. Segmentation refers to the process of dividing continuous text into meaningful semantic units. Quantization refers to assigning a unique numerical ID to each semantic unit and converting it into a vector representation, enabling the text data to be processed by machine learning models.

[0144] The word segmentation vector set refers to the result of text segmentation and quantization processing of the radiotherapy-medication plan.

[0145] The medical feature extraction operation refers to the process of extracting medical features that have an impact on tumor development from the word segmentation vector set and reducing the data dimensionality.

[0146] The medical feature vector set refers to the word segmentation vector set that has undergone medical feature extraction.

[0147] The virtual-based tumor evolution prediction operation refers to the process of simulating the changes of the tumor organ simulation model after passing through the medical feature vector set through multiphysics field evolution in digital twin technology. The predicted tumor organ simulation model refers to the tumor evolution prediction operation result of the tumor organ simulation model.

[0148] The comparison between the tumor organ simulation model and the predicted tumor organ simulation model refers to identifying the gap between the tumor organ simulation model and the predicted tumor organ simulation model in terms of the standard of healthy organ data.

[0149] Specifically, in this embodiment of the invention, firstly, the radiotherapy-medication plan is processed by text segmentation and quantization using a pre-built natural language processing system to obtain a set of segmented vectors. Then, medical feature extraction is performed on the segmented vector set using a preset convolution kernel to obtain a set of medical feature vectors. Finally, based on the set of medical feature vectors, a tumor evolution prediction operation based on virtual implementation is performed on the tumor organ simulation model to obtain a predicted tumor organ simulation model. The tumor organ simulation model before and after virtual implementation is compared with the predicted tumor organ simulation model to obtain a simulation implementation effect score. A positive simulation implementation effect score indicates effective processing, while a negative score indicates ineffective processing.

[0150] In detail, in this embodiment of the invention, comparing the tumor organ simulation model with the predicted tumor organ simulation model to obtain a simulation implementation effect score includes:

[0151] Data information of the tumor organ simulation model and the predicted tumor organ simulation model based on a preset set of indicators is obtained to obtain a simulation model information set and a prediction model information set;

[0152] Obtain a set of standard indicator information, calculate the difference between the set of standard indicator information and the set of simulation model information on each indicator to obtain a simulation indicator difference sequence, and calculate the difference between the set of standard indicator information and the set of prediction model information on each indicator to obtain a prediction indicator difference sequence.

[0153] Based on the preset index weight coefficients, the simulation index difference in the simulation index difference sequence is weighted and calculated to obtain the simulation comprehensive evaluation score; the prediction index difference in the prediction index difference sequence is weighted and calculated to obtain the prediction comprehensive evaluation score.

[0154] The difference between the predicted comprehensive evaluation score and the simulated comprehensive evaluation score is calculated to obtain the simulated implementation effect score.

[0155] The set of indicators includes indicators such as the number of lesions and the size of lymph nodes.

[0156] The simulation model information set refers to the data corresponding to the tumor organ simulation model in the indicator set. Similarly, the prediction model information set refers to the data corresponding to the prediction tumor organ simulation model in the indicator set.

[0157] The set of standard indicator information refers to the parameters of indicators that indicate a patient has recovered to a healthy standard. For example, if conventional imaging techniques show that the diameter of a target lesion is less than 5 mm, it means that the further implementation of the medical plan can be stopped.

[0158] The simulation index difference sequence refers to the difference between the standard index information set and the simulation model information set on each index. The prediction index difference sequence refers to the difference between the standard index information set and the prediction model information set on each index.

[0159] The weighting coefficients refer to the weighting relationships between various indicators such as the number of lesions and lymph node size. For example, the weighting relationship between the number of lesions and lymph node size might be 15% : 25%...

[0160] The simulation comprehensive evaluation score refers to the sum of the product results of the individual simulation index differences in the simulation index difference sequence, multiplied according to the index weight coefficients. Similarly, the prediction comprehensive evaluation score refers to the sum of the product results of the individual prediction index differences in the prediction index difference sequence, multiplied according to the index weight coefficients.

[0161] Specifically, in this embodiment of the invention, the tumor organ simulation model and the predicted tumor organ simulation model are difficult to directly compare. Therefore, the data information of these two models for a preset set of indicators can be obtained to obtain the simulation model information set and the prediction model information set.

[0162] This invention calculates the difference between the simulation model information set and the standard indicator information set to obtain a simulation indicator difference sequence, and calculates the difference between the standard indicator information set and the prediction model information set to obtain a prediction indicator difference sequence. This allows for a direct comparison between the tumor organ simulation model and the predicted tumor organ simulation model.

[0163] Specifically, in order to comprehensively evaluate the scores of each model, this invention configures the importance of each indicator through indicator weight coefficients, thereby performing weighted calculations on each simulation indicator difference in the simulation indicator difference sequence to obtain a comprehensive simulation evaluation score, and performing weighted calculations on each prediction indicator difference in the prediction indicator difference sequence to obtain a comprehensive prediction evaluation score.

[0164] Finally, the simulated implementation effect score is obtained by calculating the difference between the predicted comprehensive evaluation score and the simulated comprehensive evaluation score. The simulated implementation effect score can be normalized to output a percentage.

[0165] S4. When the simulated implementation effect score is greater than the preset implementation standard, the radiotherapy-medication plan is determined to be a preset qualified plan, and the radiotherapy-medication plan is output as an effective medical plan.

[0166] The standard configuration for implementation is 20%.

[0167] The qualified protocol refers to a marker indicating that the radiotherapy-drug regimen can be used for the implementation of a medical protocol.

[0168] The effective medical plan refers to a radiotherapy-medication plan marked as a "qualified plan".

[0169] Specifically, in this embodiment of the invention, a radiotherapy-medication plan is simulated using digital twin technology. When the simulated implementation effect score is greater than a preset implementation standard, it indicates that the radiotherapy-medication plan is relatively effective and can be included in the implementation of subsequent medical plans. Therefore, the radiotherapy-medication plan is output as an effective medical plan and awaits implementation.

[0170] In detail, in this embodiment of the invention, after outputting the radiotherapy-medication plan as an effective medical plan, the method further includes:

[0171] Obtain the identity identifier from the tumor management terminal;

[0172] Using a pre-built log device, based on the identity identifier, the operation records of the responsibility relationship verification process are obtained according to a preset monitoring frequency to obtain access records;

[0173] The access records are subjected to abnormal behavior identification to obtain abnormal behavior identification results.

[0174] The log device refers to a device that records and visualizes the operation records of the [responsibility relationship verification] process.

[0175] The monitoring frequency is configured to be once per hour.

[0176] The access record refers to a text that records information such as the execution time and number of times the responsibility relationship verification process is performed.

[0177] The abnormal behavior identification refers to the process of identifying abnormal behaviors in access records using a neural network. Abnormal behaviors include expired visitor credentials, abnormal access frequency, and unauthorized actions.

[0178] The abnormal behavior identification result refers to the abnormal behavior identification result of the access record.

[0179] Specifically, in this embodiment of the invention, to promptly detect unauthorized access and prevent the leakage of sensitive medical data, or to monitor the access behavior of medical personnel and prevent internal personnel from illegally obtaining patient data, a pre-built log device can be used to monitor the process of verifying the responsibility relationship through an identity identifier, obtaining access records. These access records are then analyzed using a pre-built abnormal behavior identification model to obtain abnormal behavior identification results. When the abnormal behavior identification result is abnormal, relevant departments can be notified to verify and handle the matter.

[0180] S5. Using the effective medical plan, perform the plan implementation operation on the tumor object to obtain real pathological change information, and update the tumor organ simulation model according to the content identifier using the real pathological change information to obtain an updated tumor organ simulation model.

[0181] The implementation of the plan refers to the process of carrying out the effective medical plan, such as administering medication or radiotherapy.

[0182] The actual pathological change information refers to the tumor change information after the implementation of the protocol.

[0183] The step of updating the tumor organ simulation model using the real pathological change information refers to the process of using a tumor management terminal to store the real pathological change information in a distributed storage system, thereby changing the data of the tumor organ simulation model.

[0184] The updated tumor organ simulation model refers to a tumor organ simulation model that has been updated with real pathological change information.

[0185] Specifically, in this embodiment of the invention, after an effective medical plan is implemented and real pathological change information is obtained, the pathological information of the target tumor can be updated, thereby updating the tumor organ simulation model and obtaining an updated tumor organ simulation model.

[0186] In detail, in this embodiment of the invention, after obtaining the actual pathological change information, the method further includes:

[0187] Obtain information on predicted pathological changes from the tumor organ simulation model;

[0188] The loss value between the actual pathological change information and the predicted pathological change information is calculated based on the pre-constructed cross-entropy loss algorithm.

[0189] The loss value is minimized according to the pre-built gradient descent algorithm to obtain the network update parameters;

[0190] Using the network update parameters, a reverse network parameter update operation is performed on the tumor development trend model to obtain an optimized tumor development trend model.

[0191] The predicted pathological change information refers to the indicator information of each tumor organ corresponding to the predicted tumor organ simulation model.

[0192] The cross-entropy loss algorithm is an algorithm that measures the difference between the actual pathological change information and the predicted pathological change information.

[0193] The gradient descent algorithm refers to the algorithm that minimizes the loss value to update the network parameters of the model. The cross-entropy loss algorithm and gradient descent algorithm are common processing algorithms in the training process of neural network models, and will not be described in detail in this invention.

[0194] The network update parameters refer to the network parameters of the tumor development trend model corresponding to the minimum loss value.

[0195] The reverse network parameter update operation refers to the process of obtaining network update parameters based on the output results, thereby updating the parameters in the tumor development trend model.

[0196] The optimized tumor development trend model refers to the tumor development trend model updated using the network update parameters.

[0197] Specifically, in this embodiment of the invention, the tumor development trend model is trained based on the real-time physiological detection data, which contains medical data such as drug or radiotherapy data. By acquiring the predicted pathological change information of the tumor organ simulation model and calculating the loss value between the actual pathological change information and the predicted pathological change information, the invention can train the tumor development trend model and ensure that the tumor development trend model can accurately predict the effect of medical treatment on the tumor.

[0198] S6. Using the distributed storage system, generate the update content identifier corresponding to the updated tumor organ simulation model.

[0199] The updated content identifier refers to the updated content identifier.

[0200] Specifically, in this embodiment of the invention, since the tumor organ simulation model changes to the updated tumor organ simulation model, the data content in the distributed storage system also changes accordingly, and the CID used for indexing the data also changes naturally. Therefore, the distributed storage system automatically generates an updated content identifier corresponding to the updated tumor organ simulation model.

[0201] S7. Using a pre-built automatic on-chain smart contract, perform blockchain on-chain operation on the updated content identifier according to the pre-built identity identifier.

[0202] The automatic on-chain smart contract refers to a pre-defined executable program that automatically encrypts and uploads the updated content identifier to the blockchain when an update is detected.

[0203] Specifically, in this embodiment of the invention, to ensure the traceability of data, an automatic blockchain smart contract is used to automatically perform blockchain-based operations on the updated content identifier, thereby enabling the recording of the updated version of the updated content identifier in the blockchain.

[0204] To address the problems described in the background section, this invention first verifies the physician and tumor subjects of the radiotherapy-medication regimen to ensure the accuracy of the regimen's source and subjects. Then, it acquires a distributed storage tumor organ simulation model using content identifiers and simulates the implementation of the tumor organ model using the radiotherapy-medication regimen, obtaining a simulation effectiveness score. This invention utilizes digital twin technology to simulate tumor organ tissue, thereby ensuring the effectiveness of each radiotherapy-medication regimen. Furthermore, each time medication or radiotherapy is administered, the radiotherapy-medication regimen is recorded offline and online, and the tumor organ simulation model is updated. This ensures that each radiotherapy or medication regimen is a further design based on all current medical regimens, avoiding conflicts or duplicate treatments. Therefore, this invention can improve the accuracy of radiotherapy and medication administration.

[0205] like Figure 2 The diagram shown is a functional block diagram of a radiotherapy medication collaborative management system based on digital twins provided in an embodiment of the present invention.

[0206] The radiotherapy medication collaborative management system 100 based on digital twins described in this invention can be installed in an electronic device. Depending on the functions implemented, the radiotherapy medication collaborative management system 100 based on digital twins may include an object verification module 101, a scheme verification module 102, a scheme implementation module 103, and a scheme uploading module 104. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0207] The object verification module 101 is used to obtain the doctor object and the tumor object from the radiotherapy-medication plan when the pre-built radiotherapy medication collaborative management terminal receives the radiotherapy-medication plan sent by the doctor, and to use the pre-built verification smart contract to verify the responsibility relationship between the doctor object and the tumor object to obtain the relationship verification result.

[0208] The scheme verification module 102 is used to obtain the content identifier corresponding to the tumor object using the radiotherapy drug collaborative management terminal when the relationship verification result is verified as passed, and to obtain the tumor organ simulation model corresponding to the tumor object from the pre-built distributed storage system according to the content identifier, and to simulate the implementation of the tumor organ simulation model according to the radiotherapy-drug scheme to obtain the simulation implementation effect score, and when the simulation implementation effect score is greater than the preset implementation standard, to determine that the radiotherapy-drug scheme is a preset qualified scheme, and to output the radiotherapy-drug scheme as an effective medical scheme;

[0209] The scheme implementation module 103 is used to implement the scheme on the tumor object using the effective medical scheme to obtain real pathological change information, and update the tumor organ simulation model using the real pathological change information according to the content identifier to obtain an updated tumor organ simulation model, and use the distributed storage system to generate an updated content identifier corresponding to the updated tumor organ simulation model.

[0210] The on-chain module 104 of the solution is used to perform on-chain operation on the updated content identifier based on the pre-built identity identifier using a pre-built automatic on-chain smart contract.

[0211] In detail, the modules in the digital twin-based radiotherapy medication collaborative management system 100 described in this embodiment of the invention employ the same methods as described above. Figure 1 The method uses the same technical means as the digital twin-based radiotherapy medication collaborative management method described in the article and can produce the same technical effects, so it will not be elaborated here.

[0212] like Figure 3 The diagram shown is a structural schematic of an electronic device for implementing a digital twin-based collaborative management method for radiotherapy medication, according to an embodiment of the present invention.

[0213] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and capable of running on the processor 10, such as a radiotherapy medication collaborative management method program based on digital twins.

[0214] The memory 11 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 1. Furthermore, the memory 11 includes both internal storage units and external storage devices of the electronic device 1. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 1, such as the code of a radiotherapy drug co-management method program based on digital twins, but also to temporarily store data that has been output or will be output.

[0215] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., a radiotherapy drug co-management method program based on digital twins) and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0216] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0217] Figure 3 Only electronic devices with components are shown; it will be understood by those skilled in the art that... Figure 3The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0218] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power the various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0219] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the electronic device 1 and other electronic devices.

[0220] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired or wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 1 and to display a visual user interface.

[0221] The radiotherapy medication co-management method program based on digital twins, stored in the memory 11 of the electronic device 1, is a combination of multiple instructions. When run in the processor 10, it can achieve the following:

[0222] When the pre-built radiotherapy medication collaborative management terminal receives the radiotherapy-medication plan sent by the doctor, it obtains the doctor object and the tumor object from the radiotherapy-medication plan, and uses the pre-built verification smart contract to verify the responsibility relationship between the doctor object and the tumor object to obtain the relationship verification result.

[0223] When the relationship verification result is successful, the content identifier corresponding to the tumor object is obtained using the radiotherapy drug collaborative management terminal, and the tumor organ simulation model corresponding to the tumor object is obtained from the pre-built distributed storage system based on the content identifier.

[0224] According to the radiotherapy-drug regimen, the tumor organ simulation model is simulated and implemented to obtain a simulation implementation effect score;

[0225] When the simulated implementation effect score is greater than the preset implementation standard, the radiotherapy-medication plan is determined to be a preset qualified plan, and the radiotherapy-medication plan is output as an effective medical plan;

[0226] Using the effective medical plan, the tumor object is subjected to the plan implementation operation to obtain real pathological change information, and the tumor organ simulation model is updated using the real pathological change information according to the content identifier to obtain an updated tumor organ simulation model.

[0227] Using the distributed storage system, an update content identifier corresponding to the updated tumor organ simulation model is generated;

[0228] Using a pre-built automatic on-chain smart contract, the updated content identifier is on-chained on the blockchain based on the pre-built identity identifier.

[0229] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figures 1 to 3 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0230] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0231] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following:

[0232] When the pre-built radiotherapy medication collaborative management terminal receives the radiotherapy-medication plan sent by the doctor, it obtains the doctor object and the tumor object from the radiotherapy-medication plan, and uses the pre-built verification smart contract to verify the responsibility relationship between the doctor object and the tumor object to obtain the relationship verification result.

[0233] When the relationship verification result is successful, the content identifier corresponding to the tumor object is obtained using the radiotherapy drug collaborative management terminal, and the tumor organ simulation model corresponding to the tumor object is obtained from the pre-built distributed storage system based on the content identifier.

[0234] According to the radiotherapy-drug regimen, the tumor organ simulation model is simulated and implemented to obtain a simulation implementation effect score;

[0235] When the simulated implementation effect score is greater than the preset implementation standard, the radiotherapy-medication plan is determined to be a preset qualified plan, and the radiotherapy-medication plan is output as an effective medical plan;

[0236] Using the effective medical plan, the tumor object is subjected to the plan implementation operation to obtain real pathological change information, and the tumor organ simulation model is updated using the real pathological change information according to the content identifier to obtain an updated tumor organ simulation model.

[0237] Using the distributed storage system, an update content identifier corresponding to the updated tumor organ simulation model is generated;

[0238] Using a pre-built automatic on-chain smart contract, the updated content identifier is on-chained on the blockchain based on the pre-built identity identifier.

[0239] In the embodiments provided by this invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and actual implementations may have other classification methods.

[0240] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0241] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0242] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0243] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for collaborative management of radiotherapy medication based on digital twins, characterized in that, The method includes: When the pre-built radiotherapy medication collaborative management terminal receives the radiotherapy-medication plan sent by the doctor, it obtains the doctor object and the tumor object from the radiotherapy-medication plan, and uses the pre-built verification smart contract to verify the responsibility relationship between the doctor object and the tumor object to obtain the relationship verification result. When the relationship verification result is successful, the content identifier corresponding to the tumor object is obtained using the radiotherapy drug collaborative management terminal, and the tumor organ simulation model corresponding to the tumor object is obtained from the pre-built distributed storage system based on the content identifier. According to the radiotherapy-drug regimen, the tumor organ simulation model is simulated and implemented to obtain a simulation implementation effect score; When the simulated implementation effect score is greater than the preset implementation standard, the radiotherapy-medication plan is determined to be a preset qualified plan, and the radiotherapy-medication plan is output as an effective medical plan; Using the effective medical plan, the tumor object is subjected to the plan implementation operation to obtain real pathological change information, and the tumor organ simulation model is updated using the real pathological change information according to the content identifier to obtain an updated tumor organ simulation model. Using the distributed storage system, an update content identifier corresponding to the updated tumor organ simulation model is generated; Using a pre-built automatic on-chain smart contract, the updated content identifier is on-chained on the blockchain based on the pre-built identity identifier.

2. The method for collaborative management of radiotherapy medication based on digital twins as described in claim 1, characterized in that, Before the pre-built radiotherapy medication collaborative management terminal receives the radiotherapy-medication plan sent by the doctor, the method further includes: Using a pre-built tumor management terminal, the pathological information of the target tumor is obtained, and tumor organ simulation modeling is performed on the pathological information of the target tumor to obtain a tumor organ simulation model. The tumor organ simulation model is sent to a pre-built distributed storage system for distributed storage, and the content identifier fed back by the distributed storage system is obtained. Using a pre-built physically unclonable function, an identity identifier is constructed for the tumor organ simulation model. Based on the identity identifier, a blockchain-based encrypted on-chain operation is performed on the content identifier to obtain a tumor on-chain identity credential fed back by the blockchain.

3. The method for collaborative management of radiotherapy medication based on digital twins as described in claim 2, characterized in that, The process of performing tumor organ simulation modeling on the target tumor pathological information to obtain a tumor organ simulation model includes: Acquire genomic data, radiotherapy dose data, medical imaging structural data, and real-time physiological detection data from the target tumor pathology information; An initial tumor model is obtained, and the basic structure of the initial tumor model is adjusted using the genomic data, radiotherapy dose data, and medical imaging structure data to obtain a three-dimensional model of the tumor organ. Using a pre-constructed physiological function simulation model, the three-dimensional model of the tumor organ is functionally configured to obtain a primary model of the tumor organ; The real-time physiological detection data is subjected to a Transformer-based tumor development trend prediction operation to obtain a tumor development trend model; Using the tumor development trend model, the development process of the primary model of the tumor organ is configured to obtain a tumor organ simulation model.

4. The method for collaborative management of radiotherapy medication based on digital twins as described in claim 3, characterized in that, The method of using a pre-built verification smart contract to verify the responsibility relationship between the doctor and the tumor object, and obtaining the relationship verification result, includes: Using a pre-built verification smart contract, the validity of the doctor's credentials is verified, and the doctor's credentials verification result is obtained. The validity of the credential for the tumor object is verified to obtain the tumor credential verification result. The responsibility relationship between the physician and the tumor patient was verified to obtain the corresponding relationship verification results. When the verification results of the doctor's certificate, the tumor certificate, and the corresponding relationship are all verified, the relationship verification result is determined to be verified.

5. The method for collaborative management of radiotherapy medication based on digital twins as described in claim 4, characterized in that, When the relationship verification result is successful, the content identifier corresponding to the tumor object is obtained using the radiotherapy medication collaborative management terminal, and based on the content identifier, the tumor organ simulation model corresponding to the tumor object is obtained from the pre-built distributed storage system, including: When the relationship verification result is successful, a session key is generated using the radiotherapy medication collaborative management terminal, and the session key is sent to the tumor management terminal; Using the tumor management terminal, the content identifier corresponding to the tumor object is queried, and the content identifier is encrypted according to the session key to obtain an encrypted content identifier, which is then sent to the radiotherapy medication collaborative management terminal. Using the radiotherapy medication collaborative management terminal, the encrypted content identifier is decrypted according to the session key to obtain the content identifier, and the tumor organ simulation model corresponding to the tumor object is obtained from the pre-built distributed storage system according to the content identifier.

6. The method for collaborative management of radiotherapy medication based on digital twins as described in claim 5, characterized in that, The step of simulating the tumor organ model according to the radiotherapy-drug regimen and obtaining a simulation effect score includes: The radiotherapy-medication regimen is subjected to text segmentation and quantization to obtain a set of segmented vectors; Perform medical feature extraction on the word segmentation vector set to obtain a medical feature vector set; Using the tumor organ simulation model, a tumor evolution prediction operation based on virtual implementation is performed according to the medical feature vector set to obtain a predicted tumor organ simulation model. By comparing the tumor organ simulation model with the predicted tumor organ simulation model, a simulation implementation effect score is obtained.

7. The method for collaborative management of radiotherapy medication based on digital twins as described in claim 6, characterized in that, The comparison between the tumor organ simulation model and the predicted tumor organ simulation model yields a simulation implementation effect score, including: Data information of the tumor organ simulation model and the predicted tumor organ simulation model based on a preset set of indicators is obtained to obtain a simulation model information set and a prediction model information set; Obtain a set of standard indicator information, calculate the difference between the set of standard indicator information and the set of simulation model information on each indicator to obtain a simulation indicator difference sequence, and calculate the difference between the set of standard indicator information and the set of prediction model information on each indicator to obtain a prediction indicator difference sequence. Based on the preset index weight coefficients, the simulation index difference in the simulation index difference sequence is weighted and calculated to obtain the simulation comprehensive evaluation score; the prediction index difference in the prediction index difference sequence is weighted and calculated to obtain the prediction comprehensive evaluation score. The difference between the predicted comprehensive evaluation score and the simulated comprehensive evaluation score is calculated to obtain the simulated implementation effect score.

8. The method for collaborative management of radiotherapy medication based on digital twins as described in claim 7, characterized in that, After obtaining the actual pathological change information, the method further includes: Obtain information on predicted pathological changes from the tumor organ simulation model; The loss value between the actual pathological change information and the predicted pathological change information is calculated based on the pre-constructed cross-entropy loss algorithm. The loss value is minimized according to the pre-built gradient descent algorithm to obtain the network update parameters; Using the network update parameters, a reverse network parameter update operation is performed on the tumor development trend model to obtain an optimized tumor development trend model.

9. The method for collaborative management of radiotherapy medication based on digital twins as described in claim 8, characterized in that, After outputting the radiotherapy-medication regimen as an effective medical plan, the method further includes: Obtain the identity identifier from the tumor management terminal; Using a pre-built log device, based on the identity identifier, the operation records of the responsibility relationship verification process are obtained according to a preset monitoring frequency to obtain access records; The access records are subjected to abnormal behavior identification to obtain abnormal behavior identification results.

10. A radiotherapy medication collaborative management system based on digital twins, characterized in that, The system includes: The object verification module is used to obtain the doctor object and tumor object from the radiotherapy-medication plan when the pre-built radiotherapy medication collaborative management terminal receives the radiotherapy-medication plan sent by the doctor, and to verify the responsibility relationship between the doctor object and the tumor object using the pre-built verification smart contract to obtain the relationship verification result. The scheme verification module is used to obtain the content identifier corresponding to the tumor object using the radiotherapy-medication collaborative management terminal when the relationship verification result is successful, and to obtain the tumor organ simulation model corresponding to the tumor object from the pre-built distributed storage system based on the content identifier. The module then simulates the implementation of the tumor organ simulation model according to the radiotherapy-medication scheme to obtain a simulation implementation effect score. When the simulation implementation effect score is greater than the preset implementation standard, the module determines that the radiotherapy-medication scheme is a preset qualified scheme and outputs the radiotherapy-medication scheme as an effective medical scheme. The scheme implementation module is used to implement the scheme on the tumor object using the effective medical scheme, obtain real pathological change information, update the tumor organ simulation model using the real pathological change information according to the content identifier, obtain an updated tumor organ simulation model, and generate an updated content identifier corresponding to the updated tumor organ simulation model using the distributed storage system. The solution on-chain module is used to perform blockchain on-chain operations on the updated content identifier based on the pre-built identity identifier using a pre-built automatic on-chain smart contract.

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