A multi-task based brain edema progression prediction system and method

Abstract

This application belongs to the field of healthcare systems. This application discloses a multi-task-based cerebral edema progression prediction system and method. First, based on the obtained cerebral edema change data before and after care, the key change features of cerebral edema are extracted. Then, based on the key change features of cerebral edema, the abnormal evaluation of cerebral edema changes is carried out. Finally, based on the nerve function change data at the corresponding position of cerebral edema and the abnormal evaluation result of cerebral edema changes, the analysis of the nursing effect of cerebral edema is carried out. Based on the comprehensive analysis of the extraction of the key change features of cerebral edema and taking into account the quantitative analysis of the nerve function changes at the corresponding position of cerebral edema, the evaluation and prediction of the nursing progress of cerebral edema are carried out, improving the accuracy of the evaluation of the nursing progress of cerebral edema.

Description

Technical Field

[0001] This application belongs to the field of healthcare systems, and specifically relates to a multi-task based cerebral edema progression prediction system and method. Background Art

[0002] Cerebral edema refers to a pathological state in which the liquid content in brain tissue increases, leading to an increase in brain volume and intracranial pressure. It is a common complication of many neurological diseases, such as stroke, brain trauma, encephalitis, and brain tumors. The prognosis of cerebral edema depends on the degree, duration, and cause of the edema. Severe cerebral edema may lead to brain herniation, which is an emergency situation that requires immediate treatment to prevent patient death. Since cerebral edema may deteriorate rapidly and cause serious consequences, for any suspected symptoms of cerebral edema, medical attention should be sought immediately and professional treatment should be received. Currently, during the care of cerebral edema by medical staff, it is impossible to quickly evaluate and predict the care effect. At this time, a cerebral edema progression prediction system is needed.

[0003] There is no dedicated system for predicting the progression of cerebral edema in the existing technology. If the prediction mode of other disease progression prediction systems is directly transformed for predicting cerebral edema, the following problems will occur: First, it is impossible to comprehensively analyze the extraction of key change features of cerebral edema, and then it is impossible to take into account the quantitative analysis of the changes in nerve function at the corresponding location of cerebral edema, resulting in a low accuracy rate for evaluating and predicting the care progress of cerebral edema. To solve the problems raised in this background art, this application designs a multi-task based cerebral edema progression prediction system and method. Summary of the Invention

[0004] To solve the deficiencies in the existing technology mentioned in the background art, this application proposes a multi-task based cerebral edema progression prediction system and method. This application first extracts the key change features of cerebral edema based on the obtained data of cerebral edema changes before and after care, then evaluates the abnormality of cerebral edema changes based on the key change features of cerebral edema, and finally analyzes the care effect of cerebral edema based on the nerve function change data at the corresponding location of cerebral edema and the evaluation result of cerebral edema change abnormality. Based on the comprehensive analysis of the extraction of key change features of cerebral edema and taking into account the quantitative analysis of the changes in nerve function at the corresponding location of cerebral edema, the care progress of cerebral edema is evaluated and predicted, improving the accuracy of the evaluation of the care progress of cerebral edema.

[0005] To achieve the above object, this application provides the following technical solutions: In the first aspect, this application provides a multi-task based cerebral edema progression prediction method, which includes the following specific steps:

[0006] S1. Obtain the data of the location and scope of cerebral edema before and after care through medical images, and at the same time obtain the nerve function change data at the corresponding location of cerebral edema;

[0007] S2. Extract the key change features of cerebral edema based on the obtained data of cerebral edema changes before and after nursing;

[0008] S3. Conduct an abnormal assessment of cerebral edema changes based on the key change features of cerebral edema to obtain the abnormal assessment result of cerebral edema changes;

[0009] S4. Analyze the nursing effect of cerebral edema based on the data of nerve function changes at the corresponding position of cerebral edema and the abnormal assessment result of cerebral edema changes;

[0010] S5. Conduct an early warning of abnormal progress based on the analysis result of the nursing effect of cerebral edema.

[0011] As an optimal technical solution of a multi-task-based method for predicting the progress of cerebral edema, the specific content of data acquisition in step S1 is as follows:

[0012] S11. Obtain the medical image data of the patient's brain before and after nursing based on the medical image acquisition component, and construct a three-dimensional image of the patient's brain based on the medical image data of the patient's brain;

[0013] S12. Obtain the change curve data of the intracranial pressure of the patient before and after nursing through the intracranial pressure acquisition terminal;

[0014] S13. Simultaneously obtain the data of nerve function changes at the corresponding position of cerebral edema before and after nursing;

[0015] S14. Store the obtained data in the corresponding storage component according to the data type.

[0016] As an optimal technical solution of a multi-task-based method for predicting the progress of cerebral edema, the extraction of the key change features of cerebral edema based on the obtained data of cerebral edema changes before and after nursing in S2 includes the following specific steps:

[0017] S21. Obtain the data of the position and range of cerebral edema before and after nursing, and obtain the range change amount of cerebral edema through the comparison of ranges, that is, subtract the nursing range of cerebral edema before nursing from the nursing range of cerebral edema after nursing to obtain the range change amount of cerebral edema;

[0018] S22. Obtain the change curve data of the intracranial pressure before and after nursing, and respectively obtain the change curves of the differences from the normal intracranial pressure to 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 amount 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 features of cerebral edema.

[0019] As a preferred technical solution of a multi-task-based method for predicting the progression of brain edema, the assessment of abnormal changes in brain edema based on key change characteristics of brain edema includes the following specific steps:

[0020] S31. Obtain the range change amount of brain edema, import the brain edema position and range data before and after care into the calculation formula of the brain edema morphological change value, and calculate the brain edema morphological change value;

[0021] S32. Obtain the change curve of the intracranial pressure difference before care and the change curve of the intracranial pressure difference after care. Evaluate the intracranial pressure abnormality coefficient before care based on the change curve of the intracranial pressure difference before care, evaluate the intracranial pressure abnormality coefficient after care based on the change curve of the intracranial pressure difference after care, and divide the difference between the intracranial pressure abnormality coefficient after care and the intracranial pressure abnormality coefficient before care by the intracranial pressure abnormality coefficient before care to obtain the intracranial pressure change value, and accurately analyze the intracranial pressure abnormality situation through the abnormality and change speed of the intracranial pressure;

[0022] S33. Obtain the obtained brain edema morphological change value and intracranial pressure change value, and sum them after weighting respectively to obtain the brain edema change abnormality assessment coefficient.

[0023] As a preferred technical solution of a multi-task-based method for predicting the progression of brain edema, the analysis of the brain edema care effect in S4 includes the following specific contents:

[0024] S41. Obtain the calculated brain edema change abnormality assessment coefficient, and at the same time obtain the nerve function change data at the corresponding positions of the brain edema before and after care;

[0025] S42. Import the calculated brain edema change abnormality assessment coefficient and the nerve function change data at the corresponding positions of the brain edema before and after care into the calculation formula of the brain edema care effect analysis value, where the calculation formula of the brain edema care effect analysis value is: , where Ym is the brain edema change abnormality assessment coefficient, Nq is the NIHSS score data before care, and Nh is the NIHSS score data after care;

[0026] S43. Compare the calculated brain edema care effect analysis value with the set threshold. If the obtained brain edema care effect analysis value is greater than or equal to the set threshold, it means that the care effect is normal and no abnormal warning is given. If the obtained brain edema care effect analysis value is less than the set threshold, it means that the care effect is abnormal and an abnormal warning is given.

[0027] In a second aspect, the present application provides a multi-task-based system for predicting the progression of brain edema, which is implemented based on the above multi-task-based method for predicting the progression of brain edema, and specifically includes:

[0028] A data acquisition unit, configured to obtain data on the location and scope of cerebral edema before and after care through medical images, and simultaneously obtain data on the changes in nerve function at the corresponding locations of the cerebral edema;

[0029] A feature extraction unit, configured to extract key change features of cerebral edema based on the obtained data on the changes in cerebral edema before and after care;

[0030] A change abnormality assessment unit, configured to assess the abnormality of the changes in cerebral edema based on the key change features of cerebral edema;

[0031] A care effect analysis unit, configured to analyze the care effect of cerebral edema based on the data on the changes in nerve function at the corresponding locations of the cerebral edema and the results of the assessment of the abnormality of the changes in cerebral edema;

[0032] An abnormality warning unit, configured to give an early warning of abnormal progression based on the results of the analysis of the care effect of cerebral edema.

[0033] In a third aspect, the present application further provides an electronic device, including: a processor and a memory, wherein a computer program that can be called by the processor is stored in the memory;

[0034] The processor executes the above-mentioned method for predicting the progression of cerebral edema based on multiple tasks by calling the computer program stored in the memory.

[0035] In a fourth aspect, the present application further provides a computer-readable storage medium, storing instructions, which when run on a computer, cause the computer to execute the above-mentioned method for predicting the progression of cerebral edema based on multiple tasks.

[0036] Advantageous effects:

[0037] The advantageous effects of the present application compared with the prior art are as follows: First, the present application extracts key change features of cerebral edema based on the obtained data on the changes in cerebral edema before and after care, then assesses the abnormality of the changes in cerebral edema based on the key change features of cerebral edema, and finally analyzes the care effect of cerebral edema based on the data on the changes in nerve function at the corresponding locations of the cerebral edema and the results of the assessment of the abnormality of the changes in cerebral edema. Through comprehensive analysis of the extraction of key change features of cerebral edema and taking into account the quantitative analysis of the changes in nerve function at the corresponding locations of the cerebral edema, the progression of cerebral edema care is evaluated and predicted, improving the accuracy of the assessment of the progression of cerebral edema care. Description of the Drawings

[0038] By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, objects, and advantages of the present application will become more obvious;

[0039] Figure 1 It is a schematic diagram of the overall process of a method for predicting the progression of cerebral edema based on multiple tasks according to the present application;

[0040] Figure 2 This is a schematic flowchart of step S3 of a multi-task-based cerebral edema progression prediction method of the present application;

[0041] Figure 3 This is a schematic flowchart of step S4 of a multi-task-based cerebral edema progression prediction method of the present application;

[0042] Figure 4 This is a schematic diagram of the framework of a multi-task-based cerebral edema progression prediction system of the present application. Detailed implementation manners

[0043] To better understand the present application, more detailed descriptions of various aspects of the present application will be made 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.

[0044] In the drawings, for ease of illustration, the sizes, dimensions, and shapes of the elements have been slightly adjusted. The drawings are only examples and are not drawn to an exact scale. As used herein, terms such as "substantially", "about", and similar terms are used as terms indicating approximation and not as terms indicating degree, and are intended to account for the inherent deviations in measured or calculated values that would be recognized by a person of ordinary skill in the art. Additionally, in the present application, the order of description of each step process does not necessarily represent the order in which these processes occur in actual operation, unless there is a clear other limitation or can be deduced from the context. It should also be understood that expressions such as "including", "including having", "having", "containing", and / or "containing having" in this specification are open-ended rather than closed-ended expressions, which mean that there are the stated features, elements, and / or components, but do not exclude the existence of one or more other features, elements, components, and / or their combinations. Furthermore, when an expression such as "at least one of..." appears after a list of listed features, it modifies the entire list of features rather than just an individual element in the list. Additionally, when describing the embodiments of the present application, the use of "may" means "one or more embodiments of the present application". And the term "exemplary" is intended to refer to an example or illustration. Unless otherwise defined, all terms used herein (including engineering terms and technical terms) have the same meaning as commonly understood by a person of ordinary skill in the art to which the present application belongs. It should also be understood that unless there is a clear statement in the present application, words defined in a common dictionary should be interpreted as having a meaning consistent with their meaning in the context of the related art and should not be interpreted in an idealized or overly formal sense.

[0045] Example 1

[0046] To solve the technical problems raised in the background art, the present application provides a preferred embodiment: Please refer to Figure 1 , a method for predicting the progression of brain edema based on multiple tasks, which includes the following specific steps:

[0047] S1. Obtain the data of the location and scope of brain edema before and after care through medical images, and at the same time obtain the data of the changes in neurological function at the corresponding locations of the brain edema;

[0048] First of all, when predicting the progression of brain edema, it is necessary to obtain the data of the brain edema site. The specific content of the data acquisition is as follows:

[0049] S11. Obtain the medical image data of the patient's brain before and after care based on the medical image acquisition component, and construct a three-dimensional image of the patient's brain based on the medical image data of the patient's brain. This step can be realized through brain three-dimensional construction software, and obtain the location data and scope data covered by the brain edema from the medical images of the brain;

[0050] S12. Obtain the change curve data of the intracranial pressure of the patient before and after care through the intracranial pressure acquisition terminal;

[0051] S13. At the same time, obtain the data of the changes in neurological function at the corresponding locations of the brain edema before and after care. The data of the changes in neurological function here are the NIHSS score data before and after care. Among them, the NIHSS scoring scale is a tool used to evaluate the neurological function status of patients with brain injuries. Through the NIHSS score, medical staff can objectively describe the patient's condition and provide appropriate treatment and care for the patient;

[0052] S14. Store the obtained data in the corresponding storage components according to the data types. It should be noted here that they can be stored separately according to the number of acquisitions, or according to the types of acquired data;

[0053] S2. Extract the key change features of the brain edema based on the obtained data of the changes in the brain edema before and after care;

[0054] Secondly, after the data is acquired, it is necessary to organize the data to obtain the key change features. Extracting the key change features of the brain edema based on the obtained data of the changes in the brain edema before and after care in S2 includes the following specific steps:

[0055] S21. Obtain the data of the location and scope of the brain edema before and after the corresponding care, and obtain the change amount of the scope of the brain edema through the comparison of the scopes, that is, obtain the change amount of the scope of the brain edema by subtracting the scope of the brain edema before care from the scope of the brain edema after care;

[0056] S22. Obtain the change curve data of intracranial pressure before and after nursing, respectively obtain the change curves of the differences between them and the normal intracranial pressure, 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 amount of brain 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 brain edema;

[0057] S3. Based on the key change characteristics of brain edema, conduct an abnormal assessment of the brain edema change to obtain the abnormal assessment result of the brain edema change;

[0058] In this embodiment, please refer to Figure 2 , and the abnormal assessment of the brain edema change based on the key change characteristics of brain edema includes the following specific steps:

[0059] S31. Import the obtained range change amount of brain edema, the brain edema position and range data before and after nursing into the calculation formula of the brain edema morphological change value in the nursing process. Among them, the calculation formula of the brain edema morphological change value is: , where xc is the range change amount of brain edema, exp() is the exponential power of the natural constant e, xm is the set safety value of the range change amount, m() is the volume of the figure in the parentheses, au is the range of brain edema before nursing, bu is the range of brain edema after nursing, is the union of the brain edema images, is the intersection of the brain edema images;

[0060] S32. Obtain the change curve of the intracranial pressure difference before nursing and the change curve of the intracranial pressure difference after nursing. Based on the change curve of the intracranial pressure difference before nursing, evaluate the intracranial pressure abnormality coefficient before nursing. Based on the change curve of the intracranial pressure difference after nursing, evaluate the intracranial pressure abnormality coefficient after nursing. Based on the difference between the intracranial pressure abnormality coefficient after nursing minus the intracranial pressure abnormality coefficient before nursing, and then divided by the intracranial pressure abnormality coefficient before nursing, obtain the intracranial pressure change value. Among them, the calculation formula of the intracranial pressure abnormality 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 safe range of the intracranial pressure difference, and v(t - 1) is the intracranial pressure difference at time t - 1. In this way, the abnormal situation of the intracranial pressure can be accurately analyzed through the abnormality and change speed of the intracranial pressure;

[0061] S33. Obtain the obtained brain edema morphological change value and intracranial pressure change value, and sum them after weighting respectively to obtain the brain edema change abnormal assessment coefficient;

[0062] S4. Analyze the nursing effect of brain edema based on the nerve function change data corresponding to the brain edema position and the abnormal assessment result of the brain edema change;

[0063] In this embodiment, please refer to Figure 3 , the analysis of the nursing effect of cerebral edema in S4 includes the following specific contents:

[0064] S41. Obtain the calculated abnormal evaluation coefficient of cerebral edema change, and at the same time obtain the data of the neurological function change at the corresponding position of cerebral edema before and after nursing;

[0065] S42. Import the calculated abnormal evaluation coefficient of cerebral edema change and the data of the neurological function change at the corresponding position of cerebral edema before and after nursing into the calculation formula of the nursing effect analysis value of cerebral edema. Among them, the calculation formula of the nursing effect analysis value of cerebral edema is: , where Ym is the abnormal evaluation coefficient of cerebral edema change, Nq is the NIHSS score data before nursing, and Nh is the NIHSS score data after nursing;

[0066] S43. Compare the calculated nursing effect analysis value of cerebral edema with the set threshold. If the obtained nursing effect analysis value of cerebral edema is greater than or equal to the set threshold, it means that the nursing effect is normal and no abnormal warning is given. If the obtained nursing effect analysis value of cerebral edema is less than the set threshold, it means that the nursing effect is abnormal and an abnormal warning is given;

[0067] S5. Perform an abnormal warning based on the analysis result of the nursing effect of cerebral edema;

[0068] In this embodiment, the specific content of S5 is: Send the analysis result of the nursing effect to the management library of the attending doctor, and at the same time send the nursing warning information of cerebral edema to the attending doctor according to the obtained abnormal warning instruction.

[0069] It should be noted that in this example, this embodiment has the following advantages compared with the prior art: First, extract the key change features of cerebral edema based on the obtained data of cerebral edema change before and after nursing, then perform an abnormal evaluation of cerebral edema change based on the key change features of cerebral edema, and finally perform an analysis of the nursing effect of cerebral edema based on the data of the neurological function change at the corresponding position of cerebral edema and the abnormal evaluation result of cerebral edema change. Based on the comprehensive analysis of the extraction of the key change features of cerebral edema, and at the same time taking into account the quantitative analysis of the neurological function change situation at the corresponding position of cerebral edema, to evaluate and predict the progress of cerebral edema nursing, and improve the accuracy of the evaluation of the progress of cerebral edema nursing.

[0070] Embodiment 2

[0071] As Figure 4 shown, a multi-task-based cerebral edema progression prediction system is implemented based on the above-mentioned multi-task-based cerebral edema progression prediction method, and it specifically includes:

[0072] A data acquisition unit, configured to obtain data on the location and scope of cerebral edema before and after care through medical images, and at the same time obtain data on the changes in neurological function at the corresponding locations of the cerebral edema; a feature extraction unit, configured to extract key change features of the cerebral edema based on the obtained data on the changes in the cerebral edema before and after care; a change abnormality evaluation unit, configured to evaluate the abnormality of the changes in the cerebral edema based on the key change features of the cerebral edema; a care effect analysis unit, configured to analyze the care effect of the cerebral edema based on the data on the changes in neurological function at the corresponding locations of the cerebral edema and the results of the evaluation of the abnormality of the changes in the cerebral edema; an abnormality warning unit, configured to give a warning of abnormal progression based on the results of the analysis of the care effect of the cerebral edema; at the same time, the data transmission directions of the various modules in this embodiment are as Figure 4 shown by the arrow directions in []. At the same time, the specific steps of the various modules in this embodiment have been described in detail in the above method embodiment and will not be elaborated here.

[0073] Embodiment 3

[0074] This embodiment provides an electronic device, including: a processor and a memory, wherein, a computer program that can be called by the processor is stored in the memory;

[0075] The processor executes the above-mentioned method for predicting the progression of cerebral edema based on multitasks by calling the computer program stored in the memory.

[0076] This electronic device may vary greatly due to different configurations or performances, and can include one or more processors and one or more memories. Among them, at least one computer program is stored in the memory, and this computer program is loaded and executed by the processor to implement the method for predicting the progression of cerebral edema based on multitasks provided in the above method embodiment. This electronic device can also include other components for realizing the functions of the device. For example, this electronic device can also have components such as wired or wireless network interfaces and input / output interfaces for data input and output. This embodiment will not be elaborated here.

[0077] Embodiment 4

[0078] This embodiment proposes a computer-readable storage medium, on which a rewritable computer program is stored;

[0079] 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 multitasks.

[0080] For example, the computer-readable storage medium can be a read-only memory, a random access memory, a read-only optical disc, magnetic tape, floppy disk, and optical data storage device, etc.

[0081] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using 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 the computer instructions or computer programs are loaded or executed on a computer, the processes or functions according to the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that contains a collection of one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0082] The above provides a detailed introduction to a multi-task-based brain edema progression prediction system and method. The embodiments in the specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. For the same or similar parts among the embodiments, reference can be made to each other. For the system disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple. For the relevant parts, reference can be made to the description in the method part. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and modifications can be made to the present application, and these improvements and modifications also fall within the protection scope of the claims of the present application.

[0083] It should also be noted that in this specification, relational terms such as "first" and "second" are only 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 term "comprising", "including", or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, article, or device that includes a series of elements includes not only those elements but also other elements that are not explicitly listed, or further includes elements that are inherent to such process, method, article, or device. Without further limitation, the element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article, or device that includes the element.

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. 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, 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, obtaining a change curve of the intracranial pressure difference value before nursing and a change curve of the intracranial pressure difference value after nursing, evaluating the abnormal intracranial pressure coefficient before nursing based on the change curve of the intracranial pressure difference value before nursing, evaluating the abnormal intracranial pressure coefficient after nursing based on the change curve of the intracranial pressure difference value after nursing, and obtaining 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 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 intracranial pressure difference safety range, and v(t-1) is the intracranial pressure difference at time t-1; 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; 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 2, 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.

4. A multi-task based method for predicting the progression of cerebral edema as claimed in claim 3, 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.

5. 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 4, 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.

6. 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 4 by calling the computer program stored in the memory.

7. 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 4.

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