A method and system for evaluating prognosis of mantle cell lymphoma

Abstract

The application relates to the field of data processing, and discloses a mantle cell lymphoma prognosis evaluation method and system, wherein the method comprises the following steps: acquiring basic diagnosis and treatment data of mantle cell lymphoma of a target patient, performing prognosis evaluation on the target patient based on basic diagnosis and treatment indexes in the basic diagnosis and treatment data to obtain a basic prognosis evaluation score, acquiring index data of a Ki-67 percentage and other special prognosis diagnosis and treatment indexes of the target patient to perform prognosis evaluation on the target patient to obtain a special prognosis evaluation score, and comprehensively evaluating the basic prognosis evaluation score and the special prognosis evaluation score corresponding to the special prognosis diagnosis and treatment indexes to obtain a mantle cell lymphoma prognosis evaluation result of the target patient. The main purpose of the application is to improve the accuracy of mantle cell lymphoma prognosis evaluation.

Description

Technical Field

[0001] The present invention relates to a mantle cell lymphoma prognosis assessment method and system, and belongs to the field of data processing. Background Art

[0002] Mantle cell lymphoma (MCL) is a rare cancer, a subtype of non-Hodgkin's lymphoma that originates from mature B cells and accounts for 6% to 8% of non-Hodgkin's lymphoma (NHL). It is characterized by swollen lymph nodes, often accompanied by systemic symptoms such as fever, night sweats, and weight loss. Its prognosis is influenced by multiple factors, such as age, blood markers, tumor stage, etc. Its treatment options include chemotherapy, targeted therapy, immunotherapy, and stem cell transplantation, but there is currently no cure, only prolonging survival and improving quality of life. In order to facilitate the development of a more appropriate rehabilitation treatment plan for the patient's prognosis, it is necessary to conduct a prognostic assessment of mantle cell lymphoma patients.

[0003] The current prognostic assessment method for mantle cell lymphoma uses a single type of assessment indicator to evaluate the prognosis of mantle cell lymphoma in patients. The assessment dimension is single and the accuracy of the assessment is poor. Summary of the Invention

[0004] The present invention provides a mantle cell lymphoma prognosis assessment method and system, the main purpose of which is to improve the accuracy of mantle cell lymphoma prognosis assessment.

[0005] To achieve the above objectives, the present invention provides a method for assessing the prognosis of mantle cell lymphoma, comprising:

[0006] Obtaining basic diagnostic and treatment data of the target patient's mantle cell lymphoma, wherein the basic diagnostic and treatment data includes different basic prognostic diagnostic and treatment indicators and an indicator value corresponding to each basic prognostic diagnostic and treatment indicator;

[0007] All the prognostic basic diagnosis and treatment indicators and their corresponding indicator values ​​in the basic diagnosis and treatment data are coded and combined according to a preset prognostic basic diagnosis and treatment indicator combination order to obtain a prognostic basic diagnosis and treatment indicator matrix;

[0008] Extracting features from the prognostic basic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector;

[0009] Based on the basic diagnosis and treatment feature vector, a pre-built mantle cell lymphoma prognostic assessment model is used to perform a prognostic assessment to obtain a basic prognostic assessment score;

[0010] Obtaining at least one special prognostic diagnostic and therapeutic indicator for mantle cell lymphoma and a prognostic evaluation rule corresponding to each special prognostic diagnostic and therapeutic indicator, wherein all obtained special prognostic diagnostic and therapeutic indicators include: Ki-67 percentage;

[0011] Obtaining an index value of each of the special prognostic diagnostic and treatment indicators of the target patient, performing a prognostic evaluation based on the index value of the special prognostic diagnostic and treatment indicator and the prognostic evaluation rule corresponding to the special prognostic diagnostic and treatment indicator, and obtaining a special prognostic evaluation score corresponding to the special prognostic diagnostic and treatment indicator;

[0012] A comprehensive evaluation is performed using the basic prognostic evaluation score and the special prognostic evaluation score corresponding to the special prognostic diagnosis and treatment indicator to obtain a prognostic evaluation result of mantle cell lymphoma for the target patient;

[0013] The prognostic evaluation result of the mantle cell lymphoma of the target patient is sent to a preset terminal device of the prognostic evaluator.

[0014] Optionally, all the prognostic basic diagnosis and treatment indicators and their corresponding indicator values ​​in the basic diagnosis and treatment data are coded and combined according to a preset prognostic basic diagnosis and treatment indicator combination order to obtain a prognostic basic diagnosis and treatment indicator matrix, including:

[0015] Converting the prognostic basic diagnosis and treatment indicators into vectors to obtain basic indicator vectors corresponding to the preset basic diagnosis and treatment indicators;

[0016] Combining the basic indicator vector corresponding to the prognostic basic diagnosis and treatment indicator with the indicator value to obtain a basic indicator feature vector corresponding to the preset basic diagnosis and treatment indicator;

[0017] The basic indicator characteristic vectors corresponding to all the preset basic diagnosis and treatment indicators are combined into a matrix form according to the preset prognosis basic diagnosis and treatment indicator combination order to obtain the prognosis basic diagnosis and treatment indicator matrix.

[0018] Optionally, converting the prognostic basic diagnosis and treatment indicator into a vector to obtain a basic indicator vector corresponding to the preset basic diagnosis and treatment indicator includes:

[0019] Segmenting the prognostic basic diagnosis and treatment indicators to obtain indicator segmentation words;

[0020] Convert the indicator segmentation words into vectors to obtain indicator segmentation word vectors;

[0021] All the indicator segmentation word vectors are averaged to obtain the basic indicator vector corresponding to the preset basic diagnosis and treatment indicator.

[0022] Optionally, the prognostic assessment is performed based on the basic diagnosis and treatment feature vector using a pre-built mantle cell lymphoma prognostic assessment model to obtain a basic prognostic assessment score, including:

[0023] Inputting the basic diagnosis and treatment feature vector into the mantle cell lymphoma prognosis assessment model;

[0024] Extracting the output value of the output node of the last output layer of the mantle cell lymphoma prognosis assessment model to obtain an initial assessment score, wherein the last output layer has only one output node;

[0025] Based on a preset score magnitude, the initial assessment score is normalized to obtain the basic prognostic assessment score.

[0026] Optionally, the normalizing the initial assessment score based on a preset score magnitude to obtain the basic prognostic assessment score includes:

[0027]

[0028] Wherein, f is the basic prognostic evaluation score, l is the preset score magnitude, and x is the initial evaluation score.

[0029] Optionally, the prognostic evaluation is performed based on the index value of the special prognostic diagnosis and treatment index and the prognostic evaluation rule corresponding to the special prognostic diagnosis and treatment index to obtain a special prognostic evaluation score corresponding to the special prognostic diagnosis and treatment index, including:

[0030] Determining the index value range including the index value of the prognostic special diagnosis and treatment index in the prognostic evaluation rule as the target index value range;

[0031] The score corresponding to the target indicator value range in the prognosis evaluation rule is determined as the special prognosis evaluation score corresponding to the special prognosis diagnosis and treatment indicator.

[0032] Optionally, the comprehensive evaluation using the basic prognostic evaluation score and the special prognostic evaluation score corresponding to the special prognostic diagnosis and treatment indicator to obtain the mantle cell lymphoma prognostic evaluation result of the target patient includes:

[0033] Obtaining the indicator weight corresponding to each of the special prognostic diagnostic and treatment indicators;

[0034] Performing weighted calculation on the special prognosis assessment score corresponding to the special prognosis diagnosis and treatment indicator based on the indicator weight corresponding to the special prognosis diagnosis and treatment indicator to obtain an initial special prognosis assessment score corresponding to the special prognosis diagnosis and treatment indicator;

[0035] performing calculation based on all of the initial special prognostic assessment scores to obtain a target special prognostic assessment score;

[0036] A comprehensive calculation is performed based on the basic prognostic assessment score and the target specific prognostic assessment score to obtain the mantle cell lymphoma prognostic assessment result of the target patient.

[0037] Optionally, the weighted calculation of the special prognosis assessment score corresponding to the special prognosis diagnosis and treatment indicator based on the indicator weight corresponding to the special prognosis diagnosis and treatment indicator to obtain the initial special prognosis assessment score corresponding to the special prognosis diagnosis and treatment indicator includes:

[0038]

[0039] Among them, k and i are the serial numbers of special prognostic diagnostic and treatment indicators, L k represents the special prognostic evaluation score corresponding to the special prognostic treatment indicator with serial number k, h k Indicates the weight of the prognostic special diagnosis and treatment indicator with serial number k, h i represents the weight of the prognostic special diagnosis and treatment indicator corresponding to the serial number i, m represents the total number of prognostic special diagnosis and treatment indicators, p k Represents the initial special prognostic assessment score corresponding to the special prognostic treatment indicator with serial number k.

[0040] Optionally, the feature extraction of the prognostic basic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector includes: dimensionality reduction of the prognostic basic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector of a preset dimension.

[0041] In order to solve the above problems, the present invention also provides a mantle cell lymphoma prognosis assessment system, the system comprising:

[0042] A basic assessment module is used to obtain basic diagnosis and treatment data of mantle cell lymphoma of a target patient, wherein the basic diagnosis and treatment data includes different basic prognostic diagnosis and treatment indicators and the indicator value corresponding to each of the basic prognostic diagnosis and treatment indicators; encode and combine all basic prognostic diagnosis and treatment indicators and their corresponding indicator values ​​in the basic diagnosis and treatment data according to a preset basic prognostic diagnosis and treatment indicator combination order to obtain a basic prognostic diagnosis and treatment indicator matrix; perform feature extraction on the basic prognostic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector; and perform prognostic assessment based on the basic diagnosis and treatment feature vector using a pre-constructed mantle cell lymphoma prognostic assessment model to obtain a basic prognostic assessment score;

[0043] a special assessment module for obtaining at least one special prognostic diagnostic and treatment indicator for mantle cell lymphoma and a prognostic assessment rule corresponding to each special prognostic diagnostic and treatment indicator, wherein all acquired special prognostic diagnostic and treatment indicators include: Ki-67 percentage; obtaining an index value for each special prognostic diagnostic and treatment indicator of a target patient, performing a prognostic assessment based on the index value of the special prognostic diagnostic and treatment indicator and the prognostic assessment rule corresponding to the special prognostic diagnostic and treatment indicator, and obtaining a special prognostic assessment score corresponding to the special prognostic diagnostic and treatment indicator;

[0044] A comprehensive evaluation module is used to perform a comprehensive evaluation using the basic prognostic evaluation score and the special prognostic evaluation score corresponding to the special prognostic diagnosis and treatment indicator to obtain a prognostic evaluation result of mantle cell lymphoma for the target patient; and send the prognostic evaluation result of mantle cell lymphoma for the target patient to a preset terminal device of the prognostic evaluator.

[0045] In order to solve the above problem, the present invention further provides an electronic device, comprising:

[0046] at least one processor; and,

[0047] a memory communicatively connected to the at least one processor; wherein,

[0048] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to implement the above-mentioned mantle cell lymphoma prognosis assessment method.

[0049] In order to solve the above problems, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores at least one instruction, and the at least one instruction is executed by a processor in an electronic device to implement the above-mentioned mantle cell lymphoma prognosis assessment method.

[0050] Compared with the problem described in the background technology, the embodiment of the present invention first obtains the basic diagnosis and treatment data of the mantle cell lymphoma of the target patient, wherein the basic diagnosis and treatment data contains different prognostic basic diagnosis and treatment indicators and the indicator value corresponding to each of the prognostic basic diagnosis and treatment indicators; all the prognostic basic diagnosis and treatment indicators and their corresponding indicator values ​​in the basic diagnosis and treatment data are encoded and combined according to a preset prognostic basic diagnosis and treatment indicator combination order to obtain a prognostic basic diagnosis and treatment indicator matrix; feature extraction is performed on the prognostic basic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector; based on the basic diagnosis and treatment feature vector, a pre-constructed mantle cell lymphoma prognostic evaluation model is used to perform prognostic evaluation to obtain a basic prognostic evaluation score; and at least one prognostic score of mantle cell lymphoma is obtained. Special diagnostic and treatment indicators and prognostic evaluation rules corresponding to each of the special diagnostic and treatment indicators, wherein all acquired special diagnostic and treatment indicators include: Ki-67 percentage; acquiring the index value of each of the special diagnostic and treatment indicators of the target patient, performing prognostic evaluation based on the index value of the special diagnostic and treatment indicator and the prognostic evaluation rules corresponding to the special diagnostic and treatment indicator, and obtaining the special prognostic evaluation score corresponding to the special diagnostic and treatment indicator; performing a comprehensive evaluation using the basic prognostic evaluation score and the special prognostic evaluation score corresponding to the special diagnostic and treatment indicator to obtain the target patient's mantle cell lymphoma prognostic evaluation result; and sending the target patient's mantle cell lymphoma prognostic evaluation result to a preset terminal device of a prognostic evaluator. Compared with the background technology, the embodiment of the present invention comprehensively evaluates the target patient's prognostic survival score from multiple indicator dimensions of basic diagnostic and treatment indicators and special diagnostic and treatment indicators of prognosis. Compared with the evaluation of a single type of evaluation indicator, the evaluation indicator type dimensions are more diverse, thereby improving the accuracy of the target patient's mantle cell lymphoma prognostic evaluation. Therefore, the main purpose of the mantle cell lymphoma prognosis assessment method and system proposed in the present invention is to improve the accuracy of mantle cell lymphoma prognosis assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 A schematic diagram of a process for evaluating the prognosis of mantle cell lymphoma according to one embodiment of the present invention;

[0052] Figure 2 A schematic diagram of a process for obtaining a prognostic basic diagnosis and treatment indicator matrix in a method for prognostic evaluation of mantle cell lymphoma provided in one embodiment of the present invention;

[0053] Figure 3 This is a functional module diagram of a mantle cell lymphoma prognosis assessment system provided by one embodiment of the present invention;

[0054] Figure 4 A schematic structural diagram of an electronic device for implementing the mantle cell lymphoma prognosis assessment method provided by one embodiment of the present invention.

[0055] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0056] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0057] The present embodiment provides a method for assessing the prognosis of mantle cell lymphoma. The method can be executed by at least one electronic device, such as a server or a terminal, that can be configured to execute the method provided in the embodiments of the present application. In other words, the method can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0058] Example 1:

[0059] Reference Figure 1 FIG. 1 is a flow chart of a method for evaluating the prognosis of mantle cell lymphoma according to an embodiment of the present invention. In this embodiment, the method for evaluating the prognosis of mantle cell lymphoma includes:

[0060] S1. Obtaining basic diagnosis and treatment data of mantle cell lymphoma of a target patient, wherein the basic diagnosis and treatment data includes different basic prognostic diagnosis and treatment indicators and an indicator value corresponding to each basic prognostic diagnosis and treatment indicator;

[0061] In the embodiment of the present invention, the target patient is a mantle cell lymphoma patient. In order to perform a prognostic assessment of mantle cell lymphoma on the target patient, basic diagnostic and treatment data of the mantle cell lymphoma of the target patient is obtained, wherein the basic diagnostic and treatment data includes different basic prognostic diagnostic and treatment indicators, wherein the basic prognostic diagnostic and treatment indicators are diagnostic and treatment indicator values ​​that cannot directly characterize the patient's prognosis (such as age, gender, serum lactate dehydrogenase (LDH), platelet count and performance status (ECOG), and can also be evaluation indicators in the International Prognostic Index for Mantle Cell Lymphoma (MIPI)) and an indicator value corresponding to each basic prognostic diagnostic and treatment indicator (which can be understood as the indicator value of the basic prognostic diagnostic and treatment indicator represented by a numerical value).

[0062] It should be explained that in the embodiment of the present invention, the prognosis of mantle cell lymphoma of the target patient is evaluated through basic diagnosis and treatment data to obtain a corresponding basic prognosis evaluation score to represent the survival status score of the target patient's prognosis. The higher the score, the worse the user's prognosis of survival status.

[0063] S2. Encoding and combining all the basic prognostic diagnosis and treatment indicators and their corresponding indicator values ​​in the basic diagnosis and treatment data according to a preset basic prognostic diagnosis and treatment indicator combination order to obtain a basic prognostic diagnosis and treatment indicator matrix;

[0064] In an embodiment of the present invention, in order to comprehensively characterize the indicator characteristic information of all prognostic basic diagnosis and treatment indicators of the target patient, all prognostic basic diagnosis and treatment indicators and their corresponding indicator values ​​in the basic diagnosis and treatment data are encoded and combined according to a preset prognostic basic diagnosis and treatment indicator combination order to obtain a prognostic basic diagnosis and treatment indicator matrix.

[0065] In the embodiment of the present invention, see Figure 2 As shown, all the prognostic basic diagnosis and treatment indicators and their corresponding indicator values ​​in the basic diagnosis and treatment data are coded and combined according to the preset prognostic basic diagnosis and treatment indicator combination order to obtain a prognostic basic diagnosis and treatment indicator matrix, including:

[0066] S21, converting the prognostic basic diagnosis and treatment indicators into a vector to obtain a basic indicator vector corresponding to the preset basic diagnosis and treatment indicators;

[0067] S22, combining the basic indicator vector corresponding to the prognostic basic diagnosis and treatment indicator with the indicator value to obtain a basic indicator feature vector corresponding to the preset basic diagnosis and treatment indicator;

[0068] S23. The basic indicator characteristic vectors corresponding to all the preset basic diagnosis and treatment indicators are combined into a matrix according to a preset combination order of the prognostic basic diagnosis and treatment indicators to obtain the prognostic basic diagnosis and treatment indicator matrix.

[0069] In another embodiment of the present invention, all the prognostic basic diagnosis and treatment indicators and their corresponding indicator values ​​in the basic diagnosis and treatment data are coded and combined according to a preset prognostic basic diagnosis and treatment indicator combination order to obtain a prognostic basic diagnosis and treatment indicator matrix, including:

[0070] Converting the prognostic basic diagnosis and treatment indicators into vectors to obtain basic indicator vectors corresponding to the preset basic diagnosis and treatment indicators;

[0071] Combining the basic indicator vector corresponding to the prognostic basic diagnosis and treatment indicator with the indicator value to obtain a basic indicator feature vector corresponding to the preset basic diagnosis and treatment indicator;

[0072] Obtaining the combination sequence of the preset basic diagnosis and treatment indicators in the combination sequence of the prognostic basic diagnosis and treatment indicators, and obtaining the combination sequence values ​​corresponding to the preset basic diagnosis and treatment indicators;

[0073] Combining the basic indicator feature vector corresponding to the prognostic basic diagnosis and treatment indicator with the combination order value to obtain the target basic indicator feature vector corresponding to the preset basic diagnosis and treatment indicator;

[0074] The target basic indicator feature vectors corresponding to all the preset basic diagnosis and treatment indicators are combined into a matrix form according to the combination order of the prognostic basic diagnosis and treatment indicators to obtain the prognostic basic diagnosis and treatment indicator matrix.

[0075] For example: the basic prognostic indicator is "age", and the basic indicator vector corresponding to "age" is The indicator value corresponding to "age" is 36, so the basic indicator vector corresponding to "age" is combined with the indicator value to obtain the basic indicator feature vector corresponding to "age": In the combination order of the prognostic basic diagnosis and treatment indicators, the combination order of "age" is the second, so the combination order value corresponding to "age" is 2. Then the basic indicator feature vector corresponding to "age" is combined with the combination order value to obtain the target basic indicator feature vector corresponding to "age":

[0076] Specifically, the preset order of combinations of basic prognostic diagnosis and treatment indicators in the embodiment of the present invention is the preset order of combinations of all basic prognostic diagnosis and treatment indicators.

[0077] Furthermore, in the embodiment of the present invention, converting the prognostic basic diagnosis and treatment indicators into a vector to obtain a basic indicator vector corresponding to the preset basic diagnosis and treatment indicators includes:

[0078] Segmenting the prognostic basic diagnosis and treatment indicators to obtain indicator segmentation words;

[0079] Convert the indicator segmentation words into vectors to obtain indicator segmentation word vectors;

[0080] All the indicator segmentation word vectors are averaged to obtain the basic indicator vector corresponding to the preset basic diagnosis and treatment indicator.

[0081] Optionally, in an embodiment of the present invention, a deep learning model (such as a BERT model) or a related algorithm (such as a one-hot algorithm) may be used to convert words into vectors, and the embodiment of the present invention is not limited to this.

[0082] S3. Extracting features from the prognostic basic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector;

[0083] In order to condense the characteristic information contained in the prognostic basic diagnosis and treatment indicator matrix and reduce subsequent computing resource consumption in the embodiment of the present invention, feature extraction is performed on the prognostic basic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector.

[0084] Specifically, the embodiment of the present invention performs dimensionality reduction on the prognostic basic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector of a preset dimension. The embodiment of the present invention does not limit the method of matrix dimensionality reduction.

[0085] S4. Based on the basic diagnosis and treatment feature vector, a pre-built mantle cell lymphoma prognostic assessment model is used to perform a prognostic assessment to obtain a basic prognostic assessment score;

[0086] In order to evaluate the prognostic survival score of mantle cell lymphoma of a target patient based on basic diagnosis and treatment data, an embodiment of the present invention performs a prognostic evaluation based on the basic diagnosis and treatment feature vector using a pre-built mantle cell lymphoma prognostic evaluation model to obtain a basic prognostic evaluation score.

[0087] In detail, the embodiment of the present invention uses the pre-built mantle cell lymphoma prognostic assessment model based on the basic diagnosis and treatment feature vector to perform prognostic assessment to obtain a basic prognostic assessment score, including:

[0088] Inputting the basic diagnosis and treatment feature vector into the mantle cell lymphoma prognosis assessment model;

[0089] Extracting the output value of the output node of the last output layer of the mantle cell lymphoma prognosis assessment model to obtain an initial assessment score, wherein the last output layer has only one output node;

[0090] Based on a preset score magnitude, the initial assessment score is normalized to obtain the basic prognostic assessment score.

[0091] In detail, in the embodiment of the present invention, the initial evaluation score is normalized based on the preset score magnitude to obtain the basic prognostic evaluation score, including:

[0092]

[0093] Wherein, f is the basic prognostic evaluation score, l is the preset score magnitude, and x is the initial evaluation score.

[0094] Optionally, the preset fractional order of magnitude is 100.

[0095] It should be explained that the mantle cell lymphoma prognosis assessment model described in the embodiment of the present invention is a survival status score (i.e., represented by a basic prognosis assessment score) that assesses the prognosis of the target patient's mantle cell lymphoma based on the basic diagnosis and treatment feature vector. The higher the score, the worse the user's prognosis survival status. The mantle cell lymphoma prognosis assessment model is a trained neural network model. The embodiment of the present invention does not limit the type of model (e.g., it can be a convolutional neural network, a deep neural network, etc.).

[0096] S5. Obtain at least one special prognostic diagnostic and therapeutic indicator for mantle cell lymphoma and a prognostic evaluation rule corresponding to each special prognostic diagnostic and therapeutic indicator, wherein all obtained special prognostic diagnostic and therapeutic indicators include: Ki-67 percentage;

[0097] The special prognostic diagnostic and therapeutic indicators described in the embodiments of the present invention are diagnostic and therapeutic indicators that can clearly characterize the prognosis of a patient's mantle cell lymphoma, and may include Ki-67 percentage (i.e., the positive expression rate of the Ki-67 protein), TP53 mutation, and blast transformation. Since Ki-67 percentage is an important prognostic indicator for mantle cell lymphoma, all obtained special prognostic diagnostic and therapeutic indicators include: Ki-67 percentage.

[0098] S6. Obtaining the index value of each of the special prognostic diagnosis and treatment indicators of the target patient, performing a prognostic assessment based on the index value of the special prognostic diagnosis and treatment indicator and the prognostic assessment rule corresponding to the special prognostic diagnosis and treatment indicator, and obtaining a special prognostic assessment score corresponding to the special prognostic diagnosis and treatment indicator;

[0099] The index value of the special prognostic treatment indicator in the embodiment of the present invention is the numerical value of the treatment result of the preset special prognostic treatment indicator of the target patient. The prognostic evaluation rule includes different index value ranges and corresponding scores. In order to evaluate the score corresponding to the index value of the special prognostic treatment indicator, the special prognostic evaluation score corresponding to the special prognostic treatment indicator is obtained.

[0100] In detail, the embodiment of the present invention performs prognostic evaluation based on the index value of the special prognostic diagnosis and treatment index and the prognostic evaluation rule corresponding to the special prognostic diagnosis and treatment index to obtain a special prognostic evaluation score corresponding to the special prognostic diagnosis and treatment index;

[0101] Determining the index value range including the index value of the prognostic special diagnosis and treatment index in the prognostic evaluation rule as the target index value range;

[0102] The score corresponding to the target indicator value range in the prognosis evaluation rule is determined as the special prognosis evaluation score corresponding to the special prognosis diagnosis and treatment indicator.

[0103] It should be explained that the special prognostic treatment indicators in the embodiment of the present invention are treatment indicators that can clearly characterize the prognosis of the patient's mantle cell lymphoma. Therefore, according to the indicator value of each special prognostic treatment indicator, the survival status score of the target patient's mantle cell lymphoma prognosis can also be evaluated (that is, expressed as a special prognostic evaluation score). The higher the score, the worse the user's prognosis survival status.

[0104] S7. Performing a comprehensive assessment using the basic prognostic assessment score and the special prognostic assessment score corresponding to the special prognostic diagnosis and treatment indicator to obtain a prognostic assessment result of mantle cell lymphoma for the target patient;

[0105] In the embodiment of the present invention, the basic prognostic evaluation score and the special prognostic evaluation score corresponding to the special prognostic diagnosis and treatment indicator are used for comprehensive evaluation to obtain the prognostic evaluation result of mantle cell lymphoma of the target patient, including:

[0106] Obtaining the indicator weight corresponding to each of the special prognostic diagnostic and treatment indicators;

[0107] Performing weighted calculation on the special prognosis assessment score corresponding to the special prognosis diagnosis and treatment indicator based on the indicator weight corresponding to the special prognosis diagnosis and treatment indicator to obtain an initial special prognosis assessment score corresponding to the special prognosis diagnosis and treatment indicator;

[0108] performing calculation based on all of the initial special prognostic assessment scores to obtain a target special prognostic assessment score;

[0109] A comprehensive calculation is performed based on the basic prognostic assessment score and the target specific prognostic assessment score to obtain the mantle cell lymphoma prognostic assessment result of the target patient.

[0110] Optionally, the calculation based on all the initial special prognosis assessment scores to obtain the target special prognosis assessment score in the embodiment of the present invention includes: adding all the initial special prognosis assessment scores to obtain the target special prognosis assessment score.

[0111] In detail, the embodiment of the present invention performs weighted calculation on the special prognosis assessment score corresponding to the special prognosis diagnosis and treatment indicator based on the indicator weight corresponding to the special prognosis diagnosis and treatment indicator to obtain the initial special prognosis assessment score corresponding to the special prognosis diagnosis and treatment indicator, including:

[0112]

[0113] Among them, k and i are the serial numbers of special prognostic diagnostic and treatment indicators, L k represents the special prognostic evaluation score corresponding to the special prognostic treatment indicator with serial number k, h k Indicates the weight of the prognostic special diagnosis and treatment indicator with serial number k, h i represents the weight of the prognostic special diagnosis and treatment indicator corresponding to the serial number i, m represents the total number of prognostic special diagnosis and treatment indicators, p k Represents the initial special prognostic assessment score corresponding to the special prognostic treatment indicator with serial number k.

[0114] It should be explained that in the embodiment of the present invention, the prognostic survival score of the target patient is comprehensively evaluated from multiple dimensions of basic diagnostic and treatment indicators and special prognostic diagnostic and treatment indicators. The evaluation dimensions are more diverse, thereby improving the accuracy of the prognostic assessment of mantle cell lymphoma in the target patient.

[0115] Specifically, in the embodiment of the present invention, a comprehensive calculation is performed based on the basic prognostic evaluation score and the target specific prognostic evaluation score to obtain the mantle cell lymphoma prognostic evaluation result of the target patient, including:

[0116] g=a*j+b*t

[0117] Among them, g is the prognostic evaluation result of mantle cell lymphoma of the target patient, j is the basic prognostic evaluation score, a is the preset first weight, t is the special prognostic evaluation score, and b is the preset second weight.

[0118] It should be explained that, in the embodiment of the present invention, the preset first weight is a real number greater than or equal to 0 and less than or equal to 1, and the sum of the preset first weight and the preset second weight is 1.

[0119] S8. Sending the prognostic evaluation result of the mantle cell lymphoma of the target patient to a preset terminal device of the prognostic evaluator.

[0120] In an embodiment of the present invention, the prognostic assessment result of the mantle cell lymphoma of the target patient is sent to a preset terminal device of the prognostic assessor. The preset terminal device is an electronic device that can receive and view the prognostic assessment result of the mantle cell lymphoma, including but not limited to: a mobile phone, a computer, and a tablet.

[0121] Compared with the problem described in the background technology, the embodiment of the present invention first obtains the basic diagnosis and treatment data of the mantle cell lymphoma of the target patient, wherein the basic diagnosis and treatment data contains different prognostic basic diagnosis and treatment indicators and the indicator value corresponding to each of the prognostic basic diagnosis and treatment indicators; all the prognostic basic diagnosis and treatment indicators and their corresponding indicator values ​​in the basic diagnosis and treatment data are encoded and combined according to a preset prognostic basic diagnosis and treatment indicator combination order to obtain a prognostic basic diagnosis and treatment indicator matrix; feature extraction is performed on the prognostic basic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector; based on the basic diagnosis and treatment feature vector, a pre-constructed mantle cell lymphoma prognostic evaluation model is used to perform prognostic evaluation to obtain a basic prognostic evaluation score; and at least one prognostic score of mantle cell lymphoma is obtained. Special diagnostic and treatment indicators and prognostic evaluation rules corresponding to each of the special diagnostic and treatment indicators, wherein all acquired special diagnostic and treatment indicators include: Ki-67 percentage; acquiring the index value of each of the special diagnostic and treatment indicators of the target patient, performing prognostic evaluation based on the index value of the special diagnostic and treatment indicator and the prognostic evaluation rules corresponding to the special diagnostic and treatment indicator, and obtaining the special prognostic evaluation score corresponding to the special diagnostic and treatment indicator; performing a comprehensive evaluation using the basic prognostic evaluation score and the special prognostic evaluation score corresponding to the special diagnostic and treatment indicator to obtain the target patient's mantle cell lymphoma prognostic evaluation result; and sending the target patient's mantle cell lymphoma prognostic evaluation result to a preset terminal device of a prognostic evaluator. Compared with the background technology, the embodiment of the present invention comprehensively evaluates the target patient's prognostic survival score from multiple indicator dimensions of basic diagnostic and treatment indicators and special diagnostic and treatment indicators of prognosis. Compared with the evaluation of a single type of evaluation indicator, the evaluation indicator type dimensions are more diverse, thereby improving the accuracy of the target patient's mantle cell lymphoma prognostic evaluation.

[0122] Example 2:

[0123] like Figure 3 FIG. 1 is a functional module diagram of a mantle cell lymphoma prognosis evaluation system provided by one embodiment of the present invention.

[0124] The mantle cell lymphoma prognosis assessment system 100 described herein can be installed in an electronic device. Depending on the functionality implemented, the mantle cell lymphoma prognosis assessment system 100 can include a basic assessment module 101, a special assessment module 102, and a comprehensive assessment module 103. A module, also referred to as a unit, is a series of computer program segments that can be executed by an electronic device processor and perform a fixed function, and is stored in the electronic device's memory.

[0125] The basic assessment module 101 is used to obtain basic diagnosis and treatment data of mantle cell lymphoma of a target patient, wherein the basic diagnosis and treatment data includes different basic prognostic diagnosis and treatment indicators and an indicator value corresponding to each basic prognostic diagnosis and treatment indicator; all basic prognostic diagnosis and treatment indicators and their corresponding indicator values ​​in the basic diagnosis and treatment data are encoded and combined according to a preset basic prognostic diagnosis and treatment indicator combination sequence to obtain a basic prognostic diagnosis and treatment indicator matrix; feature extraction is performed on the basic prognostic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector; based on the basic diagnosis and treatment feature vector, a pre-constructed mantle cell lymphoma prognostic assessment model is used to perform a prognostic assessment to obtain a basic prognostic assessment score;

[0126] The special evaluation module 102 is used to obtain at least one special prognostic diagnostic and treatment indicator for mantle cell lymphoma and a prognostic evaluation rule corresponding to each special prognostic diagnostic and treatment indicator, wherein all acquired special prognostic diagnostic and treatment indicators include: Ki-67 percentage; obtain the index value of each special prognostic diagnostic and treatment indicator of the target patient, perform a prognostic evaluation based on the index value of the special prognostic diagnostic and treatment indicator and the prognostic evaluation rule corresponding to the special prognostic diagnostic and treatment indicator, and obtain a special prognostic evaluation score corresponding to the special prognostic diagnostic and treatment indicator;

[0127] The comprehensive evaluation module 103 is configured to perform a comprehensive evaluation using the basic prognostic evaluation score and the special prognostic evaluation score corresponding to the special prognostic diagnosis and treatment indicator to obtain a mantle cell lymphoma prognostic evaluation result for the target patient; and send the mantle cell lymphoma prognostic evaluation result for the target patient to a preset terminal device of a prognostic evaluator.

[0128] In detail, the modules in the mantle cell lymphoma prognosis evaluation system 100 according to the embodiment of the present invention are used in the same manner as described above. Figure 1 The prognostic evaluation method for mantle cell lymphoma described in the present invention is the same as the technical means and can produce the same technical effects, so it will not be described in detail here.

[0129] Example 3:

[0130] like Figure 4 FIG. 1 is a schematic diagram of the structure of an electronic device for implementing a method for evaluating the prognosis of mantle cell lymphoma according to an embodiment of the present invention.

[0131] The electronic device 1 may include a processor 10, a memory 11, a bus 12, and a communication interface 13. It may also include a computer program stored in the memory 11 and executable on the processor 10, such as a mantle cell lymphoma prognosis assessment program.

[0132] The memory 11 includes at least one type of readable storage medium, including a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 11 may be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 11 may also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart memory card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 1. Furthermore, the memory 11 may include both an internal storage unit of the electronic device 1 and an external storage device. The memory 11 may be used not only to store application software and various types of data installed in the electronic device 1, such as the code of the mantle cell lymphoma prognosis assessment program, but also to temporarily store data that has been output or is to be output.

[0133] In some embodiments, the processor 10 may be comprised of an integrated circuit, such as a single packaged integrated circuit or a combination of multiple packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control core (control unit) of the electronic device, connecting the various components of the electronic device using various interfaces and circuits. It executes programs or modules stored in the memory 11 (e.g., a mantle cell lymphoma prognosis assessment program) and accesses data stored in the memory 11 to perform various functions and process data.

[0134] The bus may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable connection and communication between the memory 11 and at least one processor 10, etc.

[0135] Figure 4 Only the electronic device with components is shown, and it can be understood by those skilled in the art that Figure 4The structure shown does not constitute a limitation on the electronic device 1 , and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0136] For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for supplying power to various components. Preferably, the power source may be logically connected to the at least one processor 10 via a power management system, thereby implementing functions such as charge management, discharge management, and power consumption management through the power management system. The power source may further include any components such as one or more DC or AC power sources, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, etc. The electronic device 1 may further include a variety of sensors, a Bluetooth module, a Wi-Fi module, etc., which will not be described in detail here.

[0137] 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 generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0138] Optionally, the electronic device 1 may further include a user interface, which may be a display or an input unit (such as a keyboard). Optionally, the user interface may also be a standard wired interface or a 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) touch device. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 1 and to display a visual user interface.

[0139] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0140] The mantle cell lymphoma prognosis assessment program stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When executed in the processor 10, it can achieve the following:

[0141] Obtaining basic diagnostic and treatment data of the target patient's mantle cell lymphoma, wherein the basic diagnostic and treatment data includes different basic prognostic diagnostic and treatment indicators and an indicator value corresponding to each basic prognostic diagnostic and treatment indicator;

[0142] All the prognostic basic diagnosis and treatment indicators and their corresponding indicator values ​​in the basic diagnosis and treatment data are coded and combined according to a preset prognostic basic diagnosis and treatment indicator combination order to obtain a prognostic basic diagnosis and treatment indicator matrix;

[0143] Extracting features from the prognostic basic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector;

[0144] Based on the basic diagnosis and treatment feature vector, a pre-built mantle cell lymphoma prognostic assessment model is used to perform a prognostic assessment to obtain a basic prognostic assessment score;

[0145] Obtaining at least one special prognostic diagnostic and therapeutic indicator for mantle cell lymphoma and a prognostic evaluation rule corresponding to each special prognostic diagnostic and therapeutic indicator, wherein all obtained special prognostic diagnostic and therapeutic indicators include: Ki-67 percentage;

[0146] Obtaining an index value of each of the special prognostic diagnostic and treatment indicators of the target patient, performing a prognostic evaluation based on the index value of the special prognostic diagnostic and treatment indicator and the prognostic evaluation rule corresponding to the special prognostic diagnostic and treatment indicator, and obtaining a special prognostic evaluation score corresponding to the special prognostic diagnostic and treatment indicator;

[0147] A comprehensive evaluation is performed using the basic prognostic evaluation score and the special prognostic evaluation score corresponding to the special prognostic diagnosis and treatment indicator to obtain a prognostic evaluation result of mantle cell lymphoma for the target patient;

[0148] The prognostic evaluation result of the mantle cell lymphoma of the target patient is sent to a preset terminal device of the prognostic evaluator.

[0149] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figures 1 to 3 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0150] Furthermore, if the modules / units integrated into 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 can include: any entity or system capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0151] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor of an electronic device, the computer program can implement:

[0152] Obtaining basic diagnostic and treatment data of the target patient's mantle cell lymphoma, wherein the basic diagnostic and treatment data includes different basic prognostic diagnostic and treatment indicators and an indicator value corresponding to each basic prognostic diagnostic and treatment indicator;

[0153] All the prognostic basic diagnosis and treatment indicators and their corresponding indicator values ​​in the basic diagnosis and treatment data are coded and combined according to a preset prognostic basic diagnosis and treatment indicator combination order to obtain a prognostic basic diagnosis and treatment indicator matrix;

[0154] Extracting features from the prognostic basic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector;

[0155] Based on the basic diagnosis and treatment feature vector, a pre-built mantle cell lymphoma prognostic assessment model is used to perform a prognostic assessment to obtain a basic prognostic assessment score;

[0156] Obtaining at least one special prognostic diagnostic and therapeutic indicator for mantle cell lymphoma and a prognostic evaluation rule corresponding to each special prognostic diagnostic and therapeutic indicator, wherein all obtained special prognostic diagnostic and therapeutic indicators include: Ki-67 percentage;

[0157] Obtaining an index value of each of the special prognostic diagnostic and treatment indicators of the target patient, performing a prognostic evaluation based on the index value of the special prognostic diagnostic and treatment indicator and the prognostic evaluation rule corresponding to the special prognostic diagnostic and treatment indicator, and obtaining a special prognostic evaluation score corresponding to the special prognostic diagnostic and treatment indicator;

[0158] A comprehensive evaluation is performed using the basic prognostic evaluation score and the special prognostic evaluation score corresponding to the special prognostic diagnosis and treatment indicator to obtain a prognostic evaluation result of mantle cell lymphoma for the target patient;

[0159] The prognostic evaluation result of the mantle cell lymphoma of the target patient is sent to a preset terminal device of the prognostic evaluator.

[0160] The modules described as separate components may or may not be physically separate, and 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 elements. Some or all of the modules may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0161] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0162] 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.

[0163] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for evaluating the prognosis of mantle cell lymphoma, characterized in that: The method comprises: Obtaining basic diagnostic and treatment data of the target patient's mantle cell lymphoma, wherein the basic diagnostic and treatment data includes different basic prognostic diagnostic and treatment indicators and an indicator value corresponding to each basic prognostic diagnostic and treatment indicator; All the prognostic basic diagnosis and treatment indicators and their corresponding indicator values ​​in the basic diagnosis and treatment data are coded and combined according to a preset prognostic basic diagnosis and treatment indicator combination order to obtain a prognostic basic diagnosis and treatment indicator matrix; Extracting features from the prognostic basic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector; Based on the basic diagnosis and treatment feature vector, a pre-built mantle cell lymphoma prognostic assessment model is used to perform a prognostic assessment to obtain a basic prognostic assessment score; Obtaining at least one special prognostic diagnostic and therapeutic indicator for mantle cell lymphoma and a prognostic evaluation rule corresponding to each special prognostic diagnostic and therapeutic indicator, wherein all obtained special prognostic diagnostic and therapeutic indicators include: Ki-67 percentage; Obtaining an index value of each of the special prognostic diagnostic and treatment indicators of the target patient, performing a prognostic evaluation based on the index value of the special prognostic diagnostic and treatment indicator and the prognostic evaluation rule corresponding to the special prognostic diagnostic and treatment indicator, and obtaining a special prognostic evaluation score corresponding to the special prognostic diagnostic and treatment indicator; A comprehensive evaluation is performed using the basic prognostic evaluation score and the special prognostic evaluation score corresponding to the special prognostic diagnosis and treatment indicator to obtain a prognostic evaluation result of mantle cell lymphoma for the target patient; The prognostic evaluation result of the mantle cell lymphoma of the target patient is sent to a preset terminal device of the prognostic evaluator.

2. The method for evaluating the prognosis of mantle cell lymphoma according to claim 1, wherein: The basic diagnosis and treatment index matrix of the prognosis is obtained by encoding and combining all the basic diagnosis and treatment indexes and their corresponding index values ​​in the basic diagnosis and treatment data according to a preset basic diagnosis and treatment index combination sequence, including: Converting the prognostic basic diagnosis and treatment indicators into vectors to obtain basic indicator vectors corresponding to the preset basic diagnosis and treatment indicators; Combining the basic indicator vector corresponding to the prognostic basic diagnosis and treatment indicator with the indicator value to obtain a basic indicator feature vector corresponding to the preset basic diagnosis and treatment indicator; The basic indicator characteristic vectors corresponding to all the preset basic diagnosis and treatment indicators are combined into a matrix form according to the preset prognosis basic diagnosis and treatment indicator combination order to obtain the prognosis basic diagnosis and treatment indicator matrix.

3. The method for evaluating the prognosis of mantle cell lymphoma according to claim 2, wherein: The converting the prognostic basic diagnosis and treatment indicator into a vector to obtain a basic indicator vector corresponding to the preset basic diagnosis and treatment indicator includes: Segmenting the prognostic basic diagnosis and treatment indicators to obtain indicator segmentation words; Convert the indicator segmentation words into vectors to obtain indicator segmentation word vectors; All the indicator segmentation word vectors are averaged to obtain the basic indicator vector corresponding to the preset basic diagnosis and treatment indicator.

4. The method for evaluating the prognosis of mantle cell lymphoma according to claim 1, wherein: The prognostic evaluation is performed based on the basic diagnosis and treatment feature vector using a pre-built mantle cell lymphoma prognostic evaluation model to obtain a basic prognostic evaluation score, including: Inputting the basic diagnosis and treatment feature vector into the mantle cell lymphoma prognosis assessment model; Extracting the output value of the output node of the last output layer of the mantle cell lymphoma prognosis assessment model to obtain an initial assessment score, wherein the last output layer has only one output node; Based on a preset score magnitude, the initial assessment score is normalized to obtain the basic prognostic assessment score.

5. The method for evaluating the prognosis of mantle cell lymphoma according to claim 4, wherein: Normalizing the initial assessment score based on a preset score magnitude to obtain the basic prognostic assessment score includes: Wherein, f is the basic prognostic evaluation score, l is the preset score magnitude, and x is the initial evaluation score.

6. The method for evaluating the prognosis of mantle cell lymphoma according to claim 1, wherein: The prognostic evaluation is performed based on the index value of the special prognostic diagnosis and treatment index and the prognostic evaluation rule corresponding to the special prognostic diagnosis and treatment index to obtain the special prognostic evaluation score corresponding to the special prognostic diagnosis and treatment index, including: Determining the index value range including the index value of the prognostic special diagnosis and treatment index in the prognostic evaluation rule as the target index value range; The score corresponding to the target indicator value range in the prognosis evaluation rule is determined as the special prognosis evaluation score corresponding to the special prognosis diagnosis and treatment indicator.

7. The method for evaluating the prognosis of mantle cell lymphoma according to claim 1, wherein: The comprehensive evaluation using the basic prognostic evaluation score and the special prognostic evaluation score corresponding to the special prognostic diagnosis and treatment indicator to obtain the mantle cell lymphoma prognostic evaluation result of the target patient includes: Obtaining the indicator weight corresponding to each of the special prognostic diagnostic and treatment indicators; Performing weighted calculation on the special prognosis assessment score corresponding to the special prognosis diagnosis and treatment indicator based on the indicator weight corresponding to the special prognosis diagnosis and treatment indicator to obtain an initial special prognosis assessment score corresponding to the special prognosis diagnosis and treatment indicator; performing calculation based on all of the initial special prognostic assessment scores to obtain a target special prognostic assessment score; A comprehensive calculation is performed based on the basic prognostic assessment score and the target specific prognostic assessment score to obtain the mantle cell lymphoma prognostic assessment result of the target patient.

8. The method for evaluating the prognosis of mantle cell lymphoma according to claim 7, wherein: The weighted calculation of the special prognosis assessment score corresponding to the special prognosis diagnosis and treatment indicator based on the indicator weight corresponding to the special prognosis diagnosis and treatment indicator to obtain the initial special prognosis assessment score corresponding to the special prognosis diagnosis and treatment indicator includes: Among them, k and i are the serial numbers of special prognostic diagnostic and treatment indicators, L k represents the special prognostic evaluation score corresponding to the special prognostic treatment indicator with serial number k, h k Indicates the weight of the prognostic special diagnosis and treatment indicator with serial number k, h i represents the weight of the prognostic special diagnosis and treatment indicator corresponding to the serial number i, m represents the total number of prognostic special diagnosis and treatment indicators, p k Represents the initial special prognostic assessment score corresponding to the special prognostic treatment indicator with serial number k.

9. The method for evaluating the prognosis of mantle cell lymphoma according to any one of claims 1 to 8, wherein: The extracting features of the prognostic basic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector includes: reducing the dimension of the prognostic basic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector of a preset dimension.

10. A prognostic evaluation system for mantle cell lymphoma, characterized in that: The system comprises: A basic assessment module is used to obtain basic diagnosis and treatment data of mantle cell lymphoma of a target patient, wherein the basic diagnosis and treatment data includes different basic prognostic diagnosis and treatment indicators and the indicator value corresponding to each of the basic prognostic diagnosis and treatment indicators; encode and combine all basic prognostic diagnosis and treatment indicators and their corresponding indicator values ​​in the basic diagnosis and treatment data according to a preset basic prognostic diagnosis and treatment indicator combination order to obtain a basic prognostic diagnosis and treatment indicator matrix; perform feature extraction on the basic prognostic diagnosis and treatment indicator matrix to obtain a basic diagnosis and treatment feature vector; and perform prognostic assessment based on the basic diagnosis and treatment feature vector using a pre-constructed mantle cell lymphoma prognostic assessment model to obtain a basic prognostic assessment score; a special assessment module for obtaining at least one special prognostic diagnostic and treatment indicator for mantle cell lymphoma and a prognostic assessment rule corresponding to each special prognostic diagnostic and treatment indicator, wherein all acquired special prognostic diagnostic and treatment indicators include: Ki-67 percentage; obtaining an index value for each special prognostic diagnostic and treatment indicator of a target patient, performing a prognostic assessment based on the index value of the special prognostic diagnostic and treatment indicator and the prognostic assessment rule corresponding to the special prognostic diagnostic and treatment indicator, and obtaining a special prognostic assessment score corresponding to the special prognostic diagnostic and treatment indicator; A comprehensive evaluation module is used to perform a comprehensive evaluation using the basic prognostic evaluation score and the special prognostic evaluation score corresponding to the special prognostic diagnosis and treatment indicator to obtain a prognostic evaluation result of mantle cell lymphoma for the target patient; and send the prognostic evaluation result of mantle cell lymphoma for the target patient to a preset terminal device of the prognostic evaluator.

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