Multitask-based encephaledema progress prediction system and method

Abstract

The invention belongs to the field of medical care systems, and discloses a multi-task-based encephaledema progress prediction system and method.The method comprises the steps that firstly, key encephaledema change characteristics are extracted based on obtained encephaledema change data before and after nursing, and then encephaledema change abnormity evaluation is carried out based on the key encephaledema change characteristics; and finally, performing encephaledema nursing effect analysis based on the neurological function change data of the corresponding position of the encephaledema and the encephaledema change abnormity evaluation result, and performing quantitative analysis on the neurological function change condition of the corresponding position of the encephaledema based on extraction comprehensive analysis of key change characteristics of the encephaledema. Therefore, the encephaledema nursing progress is evaluated and predicted, and the accuracy of encephaledema nursing progress evaluation is improved.

Description

Technical Field

[0001] The present application belongs to the field of medical care systems, and specifically, is a multi-task-based system and method for predicting the progression of cerebral edema. Background Art

[0002] Brain edema refers to a pathological state in which the fluid content in brain tissue increases, leading to an increase in brain volume and increased intracranial pressure. It is a common complication of many neurological diseases, such as stroke, brain trauma, encephalitis and brain tumors. The prognosis of brain edema depends on the degree, duration and cause of the edema. Severe brain edema may lead to brain herniation, which is an emergency that requires immediate treatment to prevent the patient's death. Since brain edema may rapidly worsen and lead to serious consequences, any suspected symptoms of brain edema should be treated immediately and receive professional treatment. At present, medical staff cannot quickly evaluate and predict the effect of care during the care of brain edema. At this time, a brain edema progression prediction system is needed; There is no system specifically for predicting the progression of cerebral edema in the prior art. If the progression prediction system of other diseases is used to directly change the prediction model to predict cerebral edema, the following problems will arise: first, it is impossible to extract and comprehensively analyze the key change characteristics of cerebral edema, and then it is impossible to take into account the quantitative analysis of the changes in neurological function at the corresponding position of cerebral edema, resulting in a low accuracy rate in evaluating and predicting the progress of cerebral edema care. In order to solve the problems raised by this background technology, the present application designs a multi-task-based cerebral edema progression prediction system and method. Summary of the invention

[0003] In order to address the deficiencies in the prior art mentioned in the background technology, the present application proposes a multi-task-based cerebral edema progression prediction system and method. The present application proposes first extracting key change features of cerebral edema based on the acquired cerebral edema change data before and after care, then evaluating abnormal cerebral edema changes based on the key change features of cerebral edema, and finally analyzing the cerebral edema care effect based on the neurological function change data at the corresponding position of cerebral edema and the abnormal cerebral edema change evaluation results. Based on the extraction and comprehensive analysis of the key change features of cerebral edema, while taking into account the quantitative analysis of the neurological function changes at the corresponding position of cerebral edema, the progress of cerebral edema care is evaluated and predicted, thereby improving the accuracy of the evaluation of the progress of cerebral edema care.

[0004] To achieve the above objectives, the present application provides the following technical solutions: In the first aspect, the present application provides a multi-task-based method for predicting the progression of cerebral edema, which comprises the following specific steps: S1. Obtain the location and range data of brain edema before and after care through medical imaging, and at the same time obtain the data on changes in neurological function at the corresponding location of brain edema; S2. Extract key change characteristics of brain edema based on the acquired brain edema change data before and after nursing; S3. Based on the key change characteristics of cerebral edema, abnormal changes in cerebral edema are evaluated to obtain abnormal changes in cerebral edema. S4. Analyze the nursing effect of cerebral edema based on the neurological function change data corresponding to the location of cerebral edema and the abnormal evaluation results of cerebral edema changes; S5. Issue warning of abnormal progress based on the analysis results of nursing effectiveness for cerebral edema.

[0005] As a preferred technical solution of a multi-task-based method for predicting the progression of cerebral edema, the specific content of data acquisition in step S1 is: S11, acquiring medical imaging data of the patient's brain before and after nursing based on the medical imaging acquisition component, and constructing a three-dimensional image of the patient's brain based on the medical imaging data of the patient's brain; S12, obtaining intracranial pressure change curve data of the patient before and after nursing through the intracranial pressure acquisition terminal; S13. Simultaneously obtain the neurological function change data of the corresponding position of brain edema before and after nursing; S14. Store the acquired data in corresponding storage components according to the data type.

[0006] As a preferred technical solution of a multi-task-based method for predicting the progression of cerebral edema, the step of extracting key change features of cerebral edema based on the acquired cerebral edema change data before and after nursing in S2 includes the following specific steps: S21, obtaining the location and range data of the cerebral edema before and after the nursing, and obtaining the range change of the cerebral edema by comparing the ranges, that is, subtracting the range of cerebral edema before the nursing from the range of cerebral edema after the nursing to obtain the range change of the cerebral edema; S22. Obtain the change curve data of the intracranial pressure before and after nursing, obtain the change curve of the difference between the intracranial pressure and the normal intracranial pressure respectively, obtain the change curve of the intracranial pressure difference before nursing and the change curve of the intracranial pressure difference after nursing, and set the obtained range change of cerebral edema, the change curve of the intracranial pressure difference before nursing and the change curve of the intracranial pressure difference after nursing as the key change characteristics of cerebral edema.

[0007] As a preferred technical solution of a multi-task-based method for predicting the progression of cerebral edema, the abnormal assessment of cerebral edema changes based on key change characteristics of cerebral edema includes the following specific steps: S31, obtaining the range change of brain edema, and the location and range data of brain edema before and after nursing care, and importing them into the calculation formula of brain edema morphology change value during nursing care to calculate the brain edema morphology change value; S32, obtaining a change curve of the intracranial pressure difference before nursing and a change curve of the intracranial pressure difference after nursing, evaluating the abnormal intracranial pressure coefficient before nursing based on the change curve of the intracranial pressure difference before nursing, evaluating the abnormal intracranial pressure coefficient after nursing based on the change curve of the intracranial pressure difference after nursing, subtracting the abnormal intracranial pressure coefficient before nursing from the abnormal intracranial pressure coefficient after nursing, and dividing the difference by the abnormal intracranial pressure coefficient before nursing to obtain the intracranial pressure change value, and accurately analyzing the abnormal intracranial pressure situation by the abnormal intracranial pressure and the change speed; S33. The obtained brain edema morphology change value and intracranial pressure change value are weighted and summed to obtain the brain edema change abnormality assessment coefficient.

[0008] As a preferred technical solution of a multi-task-based cerebral edema progression prediction method, the cerebral edema nursing effect analysis in S4 includes the following specific contents: S41, obtaining the calculated abnormal assessment coefficient of brain edema change, and simultaneously obtaining the neurological function change data of the corresponding position of brain edema before and after nursing; S42, importing the calculated abnormal evaluation coefficient of brain edema change and the data of neurological function change at the corresponding position of brain edema before and after nursing into the calculation formula of brain edema nursing effect analysis value to calculate the brain edema nursing effect analysis value, wherein the calculation formula of brain edema nursing effect analysis value is: , where Ym is the abnormal assessment coefficient of brain edema changes, Nq is the NIHSS score data before nursing, and Nh is the NIHSS score data after nursing; S43. Compare the calculated cerebral edema nursing effect analysis value with the set threshold value. If the obtained cerebral edema nursing effect analysis value is greater than or equal to the set threshold value, it means that the nursing effect is normal and no abnormal warning is issued. If the obtained cerebral edema nursing effect analysis value is less than the set threshold value, it means that the nursing effect is abnormal and an abnormal warning is issued.

[0009] In a second aspect, the present application provides a multi-task-based cerebral edema progression prediction system, which is implemented based on the above-mentioned multi-task-based cerebral edema progression prediction method, and specifically includes: A data acquisition unit, used to acquire the location and range data of brain edema before and after nursing through medical images, and simultaneously acquire the data of changes in neurological function at the corresponding location of brain edema; A feature extraction unit extracts key change features of cerebral edema based on the acquired cerebral edema change data before and after nursing; Abnormal changes assessment unit, which assesses abnormal changes in brain edema based on the key change characteristics of brain edema; Nursing effect analysis unit, which analyzes the nursing effect of cerebral edema based on the neurological function change data corresponding to the location of cerebral edema and the abnormal evaluation results of cerebral edema changes; The abnormal warning unit issues abnormal progress warning based on the analysis results of cerebral edema nursing effects.

[0010] In a third aspect, the present application further provides an electronic device, comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned multi-task-based cerebral edema progression prediction method by calling the computer program stored in the memory.

[0011] In a fourth aspect, the present application also provides a computer-readable storage medium storing instructions, which, when executed on a computer, enable the computer to execute a multi-tasking-based method for predicting the progression of cerebral edema as described above.

[0012] Beneficial effects: The beneficial effects of the present application compared to the prior art are as follows: the present application first extracts the key change characteristics of brain edema based on the acquired brain edema change data before and after care, then evaluates the abnormal changes of brain edema based on the key change characteristics of brain edema, and finally analyzes the nursing effect of brain edema based on the neurological function change data at the corresponding position of brain edema and the evaluation results of abnormal changes of brain edema. Based on the extraction and comprehensive analysis of the key change characteristics of brain edema, while taking into account the quantitative analysis of the neurological function changes at the corresponding position of brain edema, the progress of brain edema nursing is evaluated and predicted, thereby improving the accuracy of the evaluation of the progress of brain edema nursing. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings; Figure 1 This is a schematic diagram of the overall process of a multi-task-based brain edema progression prediction method for this application; Figure 2 This is a schematic diagram of the step S3 flow chart of a multi-task-based brain edema progression prediction method of this application; Figure 3 This is a schematic flow chart of step S4 of a multi-task-based method for predicting the progression of cerebral edema in this application; Figure 4 A schematic diagram of the framework of a multi-task-based brain edema progression prediction system for this application. DETAILED DESCRIPTION

[0014] In order to better understand the present application, various aspects of the present application will be described in more detail with reference to the accompanying drawings. It should be understood that these detailed descriptions are only descriptions of exemplary embodiments of the present application and do not limit the scope of the present application in any way. Throughout the specification, the same reference numerals refer to the same elements. The expression "and / or" includes any and all combinations of one or more of the associated listed items.

[0015] In the accompanying drawings, the size, dimensions and shape of the elements have been slightly adjusted for ease of explanation. The accompanying drawings are only examples and are not strictly drawn to scale. As used herein, the terms "substantially", "approximately" and similar terms are used as terms to indicate approximation, not as terms to indicate degree, and are intended to illustrate the inherent deviations in measured or calculated values ​​that will be recognized by those of ordinary skill in the art. In addition, in the present application, the order in which the steps are processed does not necessarily represent the order in which these processes occur in actual operation, unless otherwise clearly defined or can be derived from the context. It should also be understood that expressions such as "including", "including", "having", "including" and / or "including" are open rather than closed expressions in this specification, which indicate the presence of the stated features, elements and / or components, but do not exclude the presence of one or more other features, elements, components and / or combinations thereof. In addition, when expressions such as "at least one of..." appear after a list of listed features, they modify the entire list of features, rather than just modifying the individual elements in the list. In addition, when describing the embodiments of the present application, "may" is used to represent "one or more embodiments of the present application". Furthermore, the term "exemplary" is intended to refer to an example or illustration. Unless otherwise specified, all words used herein (including engineering terms and scientific and technological terms) have the same meaning as those commonly understood by those of ordinary skill in the art to which this application belongs. It should also be understood that, unless otherwise clearly stated in this application, words defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an idealized or overly formal sense.

[0016] Example 1 In order to solve the technical problems raised in the background technology, this application provides a preferred embodiment: please refer to Figure 1 , a multi-task based method for predicting the progression of cerebral edema, comprising the following specific steps: S1. Obtain the location and range data of brain edema before and after care through medical imaging, and at the same time obtain the data on changes in neurological function at the corresponding location of brain edema; First, when predicting the progression of cerebral edema, it is necessary to obtain data on the location of cerebral edema. The specific content of data acquisition is: S11, obtaining medical imaging data of the patient's brain before and after nursing based on the medical imaging acquisition component, and constructing a three-dimensional image of the patient's brain based on the medical imaging data of the patient's brain. This step can be achieved by using a brain three-dimensional construction software, and obtaining location data and range data of brain edema coverage from the medical imaging of the brain; S12, obtaining intracranial pressure change curve data of the patient before and after nursing through the intracranial pressure acquisition terminal; S13. At the same time, obtaining the neurological function change data of the corresponding position of the brain edema before and after nursing, wherein the neurological function change data here refers to the NIHSS score data before and after nursing, wherein the NIHSS score scale is a tool for evaluating the neurological function status of patients with brain injury. Through the NIHSS score, medical staff can objectively describe the patient's condition and provide appropriate treatment and care for the patient; S14, storing the acquired data in a corresponding storage component according to the data type. It should be noted that the storage can be performed according to the number of acquisitions or according to the type of acquired data; S2. Extract key change characteristics of brain edema based on the acquired brain edema change data before and after nursing; Secondly, after data acquisition, the data needs to be sorted to obtain the key change features. The key change features of cerebral edema extracted based on the acquired cerebral edema change data before and after nursing in S2 include the following specific steps: S21, obtaining the location and range data of the cerebral edema before and after the nursing, and obtaining the range change of the cerebral edema by comparing the ranges, that is, subtracting the range of cerebral edema before the nursing from the range of cerebral edema after the nursing to obtain the range change of the cerebral edema; S22, obtaining the change curve data of the intracranial pressure before and after nursing, respectively obtaining the change curve of the difference between the intracranial pressure and the normal intracranial pressure, obtaining the change curve of the intracranial pressure difference before nursing and the change curve of the intracranial pressure difference after nursing, and setting the obtained range change of cerebral edema, the change curve of the intracranial pressure difference before nursing and the change curve of the intracranial pressure difference after nursing as the key change characteristics of cerebral edema; S3. Based on the key change characteristics of cerebral edema, abnormal changes in cerebral edema are evaluated to obtain abnormal changes in cerebral edema. In this example, see Figure 2 , based on the key characteristics of brain edema changes, the abnormal assessment of brain edema changes includes the following specific steps: S31, obtaining the range change of brain edema, the location and range data of brain edema before and after nursing, and importing them into the calculation formula of brain edema morphology change value during nursing process to calculate the brain edema morphology change value, wherein the calculation formula of brain edema morphology change value is: , where xc is the range of brain edema change, exp() is the power of the natural constant e, xm is the set range of change safety value, m() is the volume of the figure in brackets, au is the range of brain edema before care, and bu is the range of brain edema after care. is the union of brain edema images, is the intersection of brain edema images; S32. Obtain the change curve of the intracranial pressure difference value before nursing and the change curve of the intracranial pressure difference value after nursing, evaluate the abnormal intracranial pressure coefficient before nursing based on the change curve of the intracranial pressure difference value before nursing, evaluate the abnormal intracranial pressure coefficient after nursing based on the change curve of the intracranial pressure difference value after nursing, and obtain the intracranial pressure change value based on the difference between the abnormal intracranial pressure coefficient after nursing and the abnormal intracranial pressure coefficient before nursing, divided by the abnormal intracranial pressure coefficient before nursing, wherein the calculation formula of the abnormal intracranial pressure coefficient can be: , where a is the difference ratio coefficient, Tr is the test duration, dt is the time integral constant, vt is the intracranial pressure difference at time t, vm is the maximum value of the intracranial pressure difference safety range, and v(t-1) is the intracranial pressure difference at time t-1. In this way, the abnormal intracranial pressure situation can be accurately analyzed by analyzing the abnormality and change speed of intracranial pressure; S33, weighting the obtained brain edema morphology change value and intracranial pressure change value respectively and summing them to obtain the brain edema change abnormality assessment coefficient; S4. Analyze the nursing effect of cerebral edema based on the neurological function change data corresponding to the location of cerebral edema and the abnormal evaluation results of cerebral edema changes; In this example, see Figure 3 The analysis of the nursing effect of cerebral edema in S4 includes the following specific contents: S41, obtaining the calculated abnormal assessment coefficient of brain edema change, and simultaneously obtaining the neurological function change data of the corresponding position of brain edema before and after nursing; S42, importing the calculated abnormal evaluation coefficient of brain edema change and the data of neurological function change at the corresponding position of brain edema before and after nursing into the calculation formula of brain edema nursing effect analysis value to calculate the brain edema nursing effect analysis value, wherein the calculation formula of brain edema nursing effect analysis value is: , where Ym is the abnormal assessment coefficient of brain edema changes, Nq is the NIHSS score data before nursing, and Nh is the NIHSS score data after nursing; S43, comparing the calculated nursing effect analysis value of cerebral edema with the set threshold value, if the obtained nursing effect analysis value of cerebral edema is greater than or equal to the set threshold value, it means that the nursing effect is normal, and no abnormal warning is issued; if the obtained nursing effect analysis value of cerebral edema is less than the set threshold value, it means that the nursing effect is abnormal, and an abnormal warning is issued; S5. Provide early warning of abnormal progression based on the analysis results of cerebral edema nursing effects; In this embodiment, the specific content of S5 is: sending the nursing effect analysis results to the management database of the attending physician, and sending cerebral edema nursing warning information to the attending physician according to the obtained abnormal warning instruction.

[0017] It should be noted in this example that this embodiment has the following advantages over the prior art: first, the key change characteristics of cerebral edema are extracted based on the acquired cerebral edema change data before and after care, and then the abnormal changes in cerebral edema are evaluated based on the key change characteristics of cerebral edema. Finally, the cerebral edema care effect is analyzed based on the neurological function change data at the corresponding position of cerebral edema and the abnormal changes in cerebral edema evaluation results. Based on the extraction and comprehensive analysis of the key change characteristics of cerebral edema, while taking into account the quantitative analysis of the changes in neurological function at the corresponding position of cerebral edema, the progress of cerebral edema care is evaluated and predicted, thereby improving the accuracy of the evaluation of the progress of cerebral edema care.

[0018] Example 2 like Figure 4 As shown, a multi-task-based brain edema progression prediction system is implemented based on the above-mentioned multi-task-based brain edema progression prediction method, which specifically includes: The data acquisition unit is used to obtain the location and range data of brain edema before and after nursing through medical images, and at the same time obtain the data of neurological function changes at the corresponding position of brain edema; the feature extraction unit extracts the key change features of brain edema based on the acquired brain edema change data before and after nursing; the abnormal change evaluation unit evaluates the abnormal changes of brain edema based on the key change features of brain edema; the nursing effect analysis unit analyzes the nursing effect of brain edema based on the neurological function change data at the corresponding position of brain edema and the abnormal changes of brain edema evaluation results; the abnormal warning unit performs abnormal progress warning based on the analysis results of the nursing effect of brain edema; at the same time, the data transmission direction of each module in this embodiment is as follows Figure 4 As shown by the arrow direction in the figure, the specific steps of each module in this embodiment have been described in detail in the above method embodiment and will not be repeated here.

[0019] Example 3 This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned multi-task-based method for predicting the progression of cerebral edema by calling the computer program stored in the memory.

[0020] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors and one or more memories, wherein the memory stores at least one computer program, and the computer program is loaded and executed by the processor to implement a multi-task-based cerebral edema progression prediction method provided by the above method embodiment. The electronic device may also include other components for implementing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input / output interface to input and output data. This embodiment will not be described in detail here.

[0021] Example 4 This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon; When the computer program runs on a computer device, the computer device is enabled to execute the above-mentioned method for predicting the progression of cerebral edema based on multi-task.

[0022] For example, the computer readable storage medium can be a read-only memory, a random access memory, a read-only CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0023] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0024] The above is a detailed introduction to a multi-task-based cerebral edema progression prediction system and method provided by the present application. The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the embodiments can be referenced to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referenced to the method part description. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of the present application, several improvements and modifications can be made to the present application, and these improvements and modifications also fall within the scope of protection of the claims of the present application.

[0025] It should also be noted that, in this specification, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or apparatus. In the absence of further restrictions, the elements defined by the sentence "comprises one..." do not exclude the presence of other identical elements in the process, method, article or apparatus that includes the elements.

Claims

1. A multi-task based method for predicting the progression of cerebral edema, characterized in that: It includes the following specific steps: S1. Obtain the location and range data of brain edema before and after care through medical imaging, and at the same time obtain the data on changes in neurological function at the corresponding location of brain edema; S2. Extract key change characteristics of brain edema based on the acquired brain edema change data before and after nursing; S3. Based on the key change characteristics of cerebral edema, abnormal changes in cerebral edema are evaluated to obtain abnormal changes in cerebral edema. S4. Analyze the nursing effect of cerebral edema based on the neurological function change data corresponding to the location of cerebral edema and the abnormal evaluation results of cerebral edema changes; S5. Issue warning of abnormal progress based on the analysis results of nursing effectiveness for cerebral edema.

2. A multi-task based method for predicting the progression of cerebral edema as claimed in claim 1, characterized in that: The step of extracting key change features of cerebral edema based on the acquired cerebral edema change data before and after nursing in S2 includes the following specific steps: S21, obtaining the location and range data of the cerebral edema before and after the nursing, and obtaining the range change of the cerebral edema by comparing the ranges, that is, subtracting the range of cerebral edema before the nursing from the range of cerebral edema after the nursing to obtain the range change of the cerebral edema; S22. Obtain the change curve data of the intracranial pressure before and after nursing, obtain the change curve of the difference between the intracranial pressure and the normal intracranial pressure respectively, obtain the change curve of the intracranial pressure difference before nursing and the change curve of the intracranial pressure difference after nursing, and set the obtained range change of cerebral edema, the change curve of the intracranial pressure difference before nursing and the change curve of the intracranial pressure difference after nursing as the key change characteristics of cerebral edema.

3. A multi-task based method for predicting the progression of cerebral edema as claimed in claim 1, characterized in that: The abnormal assessment of brain edema changes based on the key change characteristics of brain edema includes the following specific steps: S31, obtaining the range change of brain edema, and the location and range data of brain edema before and after nursing care, and importing them into the calculation formula of brain edema morphology change value during nursing care to calculate the brain edema morphology change value; S32, obtaining a change curve of the intracranial pressure difference before nursing and a change curve of the intracranial pressure difference after nursing, evaluating the abnormal intracranial pressure coefficient before nursing based on the change curve of the intracranial pressure difference before nursing, evaluating the abnormal intracranial pressure coefficient after nursing based on the change curve of the intracranial pressure difference after nursing, and obtaining the intracranial pressure change value by subtracting the abnormal intracranial pressure coefficient before nursing from the abnormal intracranial pressure coefficient after nursing; S33. The obtained brain edema morphology change value and intracranial pressure change value are weighted and summed to obtain the brain edema change abnormality assessment coefficient.

4. A multi-task based method for predicting the progression of cerebral edema as claimed in claim 3, characterized in that: The analysis of the nursing effect of cerebral edema in S4 includes the following specific contents: S41, obtaining the calculated abnormal assessment coefficient of brain edema change, and simultaneously obtaining the neurological function change data of the corresponding position of brain edema before and after nursing; S42, importing the calculated abnormal evaluation coefficient of brain edema change and the data of neurological function change at the corresponding position of brain edema before and after nursing into the calculation formula of brain edema nursing effect analysis value to calculate the brain edema nursing effect analysis value, wherein the calculation formula of brain edema nursing effect analysis value is: , where Ym is the abnormal assessment coefficient of brain edema changes, Nq is the NIHSS score data before nursing, Nh is the NIHSS score data after nursing, and exp() is the power of the natural constant e; S43. Compare the calculated cerebral edema nursing effect analysis value with the set threshold value. If the obtained cerebral edema nursing effect analysis value is greater than or equal to the set threshold value, it means that the nursing effect is normal and no abnormal warning is issued. If the obtained cerebral edema nursing effect analysis value is less than the set threshold value, it means that the nursing effect is abnormal and an abnormal warning is issued.

5. A multi-task based method for predicting the progression of cerebral edema as claimed in claim 4, characterized in that: The calculation formula of the brain edema morphological change value in S31 is: , where xc is the range of brain edema change, exp() is the power of the natural constant e, xm is the set range of change safety value, m() is the volume of the figure in brackets, au is the range of brain edema before care, and bu is the range of brain edema after care. is the union of brain edema images, is the intersection of brain edema images.

6. A multi-task based method for predicting the progression of cerebral edema as claimed in claim 5, characterized in that: The calculation formula of the abnormal intracranial pressure coefficient in S32 is: , where a is the difference ratio, Tr is the test duration, dt is the time integration constant, vt is the intracranial pressure difference at time t, vm is the maximum value of the safety range of the intracranial pressure difference, and v(t-1) is the intracranial pressure difference at time t-1.

7. A multi-task based method for predicting the progression of cerebral edema as claimed in claim 6, characterized in that: The specific content of data acquisition in step S1 is: The medical imaging data of the patient's brain before and after care are acquired based on the medical imaging acquisition component, a three-dimensional image of the patient's brain is constructed based on the medical imaging data of the patient's brain, and the intracranial pressure change curve data of the patient before and after care is acquired through the intracranial pressure acquisition terminal. Meanwhile, the neurological function change data of the corresponding position of brain edema before and after care are acquired, and the acquired data are stored in the corresponding storage component according to the data type.

8. A multi-task based brain edema progression prediction system, which is implemented based on the multi-task based brain edema progression prediction method according to any one of claims 1 to 7, characterized in that: Specifically include: A data acquisition unit, used to acquire the location and range data of brain edema before and after nursing through medical images, and simultaneously acquire the data of changes in neurological function at the corresponding location of brain edema; A feature extraction unit extracts key change features of cerebral edema based on the acquired cerebral edema change data before and after nursing; Abnormal changes assessment unit, which assesses abnormal changes in brain edema based on the key change characteristics of brain edema; Nursing effect analysis unit, which analyzes the nursing effect of cerebral edema based on the neurological function change data corresponding to the location of cerebral edema and the abnormal evaluation results of cerebral edema changes; The abnormal warning unit issues abnormal progress warning based on the analysis results of cerebral edema nursing effects.

9. An electronic device, comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the multi-task based cerebral edema progression prediction method as described in any one of claims 1 to 7 by calling the computer program stored in the memory.

10. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer is caused to execute a multi-task-based method for predicting the progression of cerebral edema as described in any one of claims 1 to 7.

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