Brain severe nursing analysis system and method based on multi-data fusion

Abstract

The invention discloses a brain critical care analysis system and method based on multi-data fusion, and belongs to the field of medical care data analys.The brain critical care analysis system constructs a patient state evaluation model, introduces physiological monitoring parameters into the patient state evaluation model for patient state evaluation, constructs a medicine care effect evaluation model, and improves the medical care effect. Introducing the drug adaptation degree and cerebral hemodynamic into a drug nursing effect model to evaluate the drug nursing effect, constructing a complication nursing effect evaluation model, and introducing the complication severity and complication nursing action association degree into the complication nursing effect evaluation model to evaluate the complication nursing effect. A comprehensive nursing effect evaluation model is constructed, the comprehensive nursing effect of the patient is evaluated, and the brain severe nursing effect is comprehensively evaluated through the patient state, the medicine nursing effect and the complication nursing effect.

Description

Technical Field

[0001] The present invention belongs to the field of medical care data processing, and specifically is a brain critical care analysis system and method based on multi-data fusion. Background Art

[0002] With the continuous development of medical technology, the quality of care and treatment effect of critically ill patients are crucial to their recovery. The care process of critically ill brain patients faces complex challenges, especially when the condition changes rapidly, complications are numerous and interrelated. The adjustment of nursing plans often relies on experience and manual judgment, and lacks real-time and accurate evaluation tools. The existing nursing plans are not personalized enough, and it is difficult to optimize nursing actions and treatment plans in real time according to the patient's condition. There is a lack of intelligent analysis and standardized judgment on the feedback of nursing effects. The existing system usually ignores the synergy between drug therapy and nursing intervention, cannot analyze the joint effects of drug therapy and nursing plans on the patient's physiological state in real time, and does not consider the relationship between the patient's risk of complications and nursing intervention.

[0003] The present invention proposes a brain critical care analysis system and method based on multi-data fusion, which evaluates the brain critical care effect by evaluating the patient's status, drug care effect and complication care effect, integrates multi-dimensional factors in the dynamic monitoring nursing process to evaluate the care effect, and puts forward suggestions for nursing improvement. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention proposes a brain critical care analysis system and method based on multi-data fusion, the present invention constructs a patient status assessment model, imports physiological monitoring parameters into the patient status assessment model to perform patient status assessment, constructs a drug care effect assessment model, imports drug adaptability and cerebral hemodynamics into the drug care effect model to perform drug care effect assessment, constructs a complication care effect assessment model, imports complication severity and complication care action correlation into the complication care effect assessment model to perform complication care effect assessment, constructs a comprehensive care effect assessment model, evaluates the comprehensive care effect of the patient, and evaluates the brain critical care effect through a comprehensive assessment of the patient status, drug care effect and complication care effect.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] The brain critical care analysis method based on multi-data fusion includes the following specific steps:

[0007] Obtain patient condition data and nursing data;

[0008] Construct a patient status assessment model, and import physiological monitoring parameters into the patient status assessment model to conduct patient status assessment;

[0009] Construct a drug nursing effect evaluation model, and introduce drug compatibility and cerebral hemodynamics into the drug nursing effect model to evaluate the drug nursing effect;

[0010] Construct a complication nursing effect evaluation model, and import the severity of complications and the correlation between complication nursing actions into the complication nursing effect evaluation model to evaluate the complication nursing effect;

[0011] Construct a comprehensive nursing effect evaluation model to evaluate the comprehensive nursing effect of patients.

[0012] Preferably, the acquisition of patient condition data and nursing data includes the following specific steps:

[0013] S11. Obtain the patient's basic information and the type of severe brain disease, and obtain the patient's real-time physiological monitoring parameters through monitoring instruments;

[0014] S12. Obtain the type and dosage of medication used by the patient, and the occurrence of complications of the patient;

[0015] S13. Obtain the patient's critical care scenario.

[0016] Preferably, the step of constructing a patient status assessment model and importing physiological monitoring parameters into the patient status assessment model to perform patient status assessment comprises the following specific steps:

[0017] S21. Substituting the patient's physiological monitoring parameters into the parameter standardization calculation formula to calculate the standardized parameters, wherein the calculation formula for the i-th standardized parameter is: Among them, A i is the real-time monitoring value of the ith physiological parameter, H i is the standard value of the ith physiological parameter;

[0018] S22. Substituting the standardized parameters into the patient monitoring status calculation formula to calculate the patient monitoring status, wherein the patient monitoring status calculation formula is: Among them, C i is the i-th standardized parameter, ω i is the weight of the i-th standardized parameter, and n is the total number of physiological monitoring parameters.

[0019] Preferably, the construction of a drug care effect evaluation model, and the introduction of drug compatibility and cerebral hemodynamics into the drug care effect model for drug care effect evaluation comprises the following specific steps:

[0020] S31. Substituting the drug dosage used by the patient into the drug compatibility evaluation formula to calculate the compatibility between the drug and the patient, wherein the compatibility evaluation formula between the drug used by the patient and the i-th physiological parameter is: Among them, F j, is the amount of the jth drug added, B j is the standard addition amount of the jth drug, λ j is the weight of the effect of the jth drug on the ith physiological parameter, A i is the real-time monitoring value of the ith physiological parameter, A i ′ is the monitoring value of the physiological parameter without taking drugs, H i is the standard value of the ith physiological parameter, and o is a number that is infinitely close to 0 but not 0;

[0021] S32. Substituting the intracranial pressure of the patient into the intracranial pressure change degree calculation formula to calculate the degree of change of the intracranial pressure of the patient, wherein the intracranial pressure change degree calculation formula of the patient is: Among them, ICP k , is the intracranial pressure after fluid infusion, ICP z , is the normal value of intracranial pressure, and the patient's cerebral perfusion pressure is substituted into the calculation formula of the degree of change of cerebral perfusion pressure to calculate the degree of change of the patient's cerebral perfusion pressure, where the calculation formula of the degree of change of the patient's cerebral perfusion pressure is: Among them, CPP k , is the cerebral perfusion pressure after fluid infusion, CPP z , is the normal value of cerebral perfusion pressure. Substitute the degree of change of intracranial pressure and cerebral perfusion pressure into the cerebral hemodynamics evaluation formula to evaluate the cerebral hemodynamics after fluid infusion. The cerebral hemodynamics evaluation formula is: S = S ICP +S CPP ;

[0022] S33. Substitute the drug compatibility and cerebral hemodynamics into the patient drug care effect evaluation formula to evaluate the patient drug care effect. The patient drug care effect evaluation formula is: Among them, R i , is the compatibility between the drug used and the i-th physiological parameter, S, is the cerebral hemodynamics, Y, is the probability of severe brain disease in the patient's age group, and GCS, is the Glasgow Coma Scale.

[0023] Preferably, the construction of the complication nursing effect evaluation model, importing the complication severity and the complication nursing action correlation into the complication nursing effect evaluation model to perform complication nursing effect evaluation comprises the following specific steps:

[0024] S41. Substitute the severity level of complications defined by the doctor into the complication severity calculation formula to calculate the complication severity, where the complication severity calculation formula is: Among them, G α , is the severity level of the patient's αth complication, β is the number of complications that occur in the patient, and μ α , is the probability of occurrence of the αth complication, G max, is the maximum severity level of complications;

[0025] S42. Substitute the nursing actions that affect the complications into the nursing action correlation calculation formula to calculate the nursing action correlation, wherein the nursing action correlation calculation formula for the αth complication is: Among them, G α , is the severity level of the patient's αth complication, θ σ,α , is the influence of the σth nursing action on the αth complication, , is the execution frequency of the th nursing action;

[0026] S43. Substitute the severity of complications and the correlation between complication nursing actions into the complication nursing effect calculation formula to calculate the complication nursing effect, wherein the complication nursing effect calculation formula is: Among them, G′ is the severity of complications, Q α , is the nursing action correlation of the αth complication, and β is the number of complications occurring in patients.

[0027] Preferably, the construction of a comprehensive nursing effect evaluation model to evaluate the comprehensive nursing effect of patients includes the following specific steps:

[0028] S51. Substitute the patient monitoring status, drug nursing effect and complication nursing effect into the comprehensive nursing effect evaluation formula to evaluate the comprehensive nursing effect, wherein the comprehensive nursing effect evaluation formula is: Z=D×(L+P)×ζ, wherein ζ is the patient's critical care scene level;

[0029] S52. Import the comprehensive nursing effect evaluation value into the pre-trained deep learning model to obtain the threshold value. According to the nursing effect threshold value output by the model, compare it with the current comprehensive nursing effect evaluation value, and grade the comprehensive nursing effect evaluation value. The higher the comprehensive nursing effect evaluation value, the better the nursing effect.

[0030] The brain critical care analysis system based on multi-data fusion is implemented based on the above-mentioned brain critical care analysis method based on multi-data fusion, and specifically includes:

[0031] A data acquisition module is used to acquire patient condition data and nursing data;

[0032] A patient status assessment module, used to assess the patient status through physiological monitoring parameters;

[0033] Drug care effect evaluation module, used to evaluate drug care effect through drug compatibility and cerebral hemodynamics;

[0034] The complication nursing effect evaluation module is used to evaluate the complication nursing effect through the severity of the complication and the correlation between the complication nursing actions;

[0035] Comprehensive nursing effectiveness evaluation module is used to evaluate the comprehensive nursing effectiveness of patients.

[0036] An electronic device comprises: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0037] The processor executes the above-mentioned brain critical care analysis method based on multi-data fusion by calling the computer program stored in the memory.

[0038] A computer-readable storage medium, characterized in that it stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned brain critical care analysis method based on multi-data fusion.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] The present invention constructs a patient status assessment model, imports physiological monitoring parameters into the patient status assessment model to perform patient status assessment, constructs a drug nursing effect assessment model, imports drug adaptability and cerebral hemodynamics into the drug nursing effect model to perform drug nursing effect assessment, constructs a complication nursing effect assessment model, imports complication severity and complication nursing action correlation into the complication nursing effect assessment model to perform complication nursing effect assessment, constructs a comprehensive nursing effect assessment model, evaluates the comprehensive nursing effect of the patient, and evaluates the critical care effect of the brain through a comprehensive assessment of the patient status, drug nursing effect and complication nursing effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a schematic diagram of the overall process of the brain critical care analysis method based on multi-data fusion of the present invention;

[0042] Figure 2 A flowchart for comprehensive nursing effectiveness evaluation;

[0043] Figure 3 It is a schematic diagram of the overall framework of the brain critical care analysis system based on multi-data fusion of the present invention. DETAILED DESCRIPTION

[0044] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0045] Example 1

[0046] See also Figure 1-Figure 2 The present invention provides an embodiment: a brain critical care analysis method based on multi-data fusion, which includes the following specific steps:

[0047] Obtain patient condition data and nursing data;

[0048] Construct a patient status assessment model, and import physiological monitoring parameters into the patient status assessment model to conduct patient status assessment;

[0049] Construct a drug nursing effect evaluation model, and introduce drug compatibility and cerebral hemodynamics into the drug nursing effect model to evaluate the drug nursing effect;

[0050] Construct a complication nursing effect evaluation model, and import the severity of complications and the correlation between complication nursing actions into the complication nursing effect evaluation model to evaluate the complication nursing effect;

[0051] Construct a comprehensive nursing effect evaluation model to evaluate the comprehensive nursing effect of patients.

[0052] In this embodiment, it should be specifically explained that obtaining patient condition data and nursing data includes the following specific steps:

[0053] S11. Obtain the patient's basic information and the type of severe brain disease, and obtain the patient's real-time physiological monitoring parameters through monitoring instruments;

[0054] S12. Obtain the type and dosage of medication used by the patient, and the occurrence of complications of the patient;

[0055] S13. Obtain the patient's critical care scenario.

[0056] It should be specifically explained in this embodiment that constructing a patient status assessment model and importing physiological monitoring parameters into the patient status assessment model to perform patient status assessment includes the following specific steps:

[0057] S21. Substituting the patient's physiological monitoring parameters into the parameter standardization calculation formula to calculate the standardized parameters, wherein the calculation formula for the i-th standardized parameter is: Among them, A i is the real-time monitoring value of the ith physiological parameter, H i is the standard value of the ith physiological parameter, and the standardized parameter calculation makes the physiological monitoring parameters in the same dimension;

[0058] S22. Substituting the standardized parameters into the patient monitoring status calculation formula to calculate the patient monitoring status, wherein the patient monitoring status calculation formula is: Among them, C i is the i-th standardized parameter, ω i is the weight of the ith standardized parameter, indicating the importance of the ith physiological monitoring parameter in the physiological activity process, which is obtained from experts and papers, and n is the total number of physiological monitoring parameters.

[0059] It should be specifically explained in this embodiment that constructing a drug care effect evaluation model and introducing drug compatibility and cerebral hemodynamics into the drug care effect model to evaluate the drug care effect includes the following specific steps:

[0060] S31. Substituting the drug dosage used by the patient into the drug compatibility evaluation formula to calculate the compatibility between the drug and the patient, wherein the compatibility evaluation formula between the drug used by the patient and the i-th physiological parameter is: Among them, F j , is the amount of the jth drug added. Due to individual differences among patients, the amount of the same drug added is also different. j is the standard addition amount of the jth drug, λ j is the weight of the effect of the jth drug on the ith physiological parameter, obtained through clinical trial data, A i , is the real-time monitoring value of the ith physiological parameter, A i ′, is the monitoring value of the physiological parameter without taking drugs, H i is the standard value of the ith physiological parameter, o is a number that is infinitely close to 0 but not 0, where: It is the weight of the actual change value and the estimated change value of the patient's physiological parameters, which is used to measure the effect of drug use;

[0061] S32. Substituting the intracranial pressure of the patient into the intracranial pressure change degree calculation formula to calculate the degree of change of the intracranial pressure of the patient, wherein the intracranial pressure change degree calculation formula of the patient is: Among them, ICP k , is the intracranial pressure after fluid infusion, ICP z , is the normal value of intracranial pressure, and the patient's cerebral perfusion pressure is substituted into the calculation formula of the degree of change of cerebral perfusion pressure to calculate the degree of change of the patient's cerebral perfusion pressure, where the calculation formula of the degree of change of the patient's cerebral perfusion pressure is: Among them, CPP k , is the cerebral perfusion pressure after fluid infusion, CPP z , is the normal value of cerebral perfusion pressure. Substitute the degree of change of intracranial pressure and cerebral perfusion pressure into the cerebral hemodynamics evaluation formula to evaluate the cerebral hemodynamics after fluid infusion. The cerebral hemodynamics evaluation formula is: S = S ICP +S CPP ;

[0062] S33. Substitute the drug compatibility and cerebral hemodynamics into the patient drug care effect evaluation formula to evaluate the patient drug care effect. The patient drug care effect evaluation formula is: Among them, R i, is the compatibility of the drug used and the i-th physiological parameter, S, is the cerebral hemodynamics, Y, is the probability of severe brain disease in the patient's age group, GCS, is the Glasgow Coma Scale, obtained through the GCS coma scale. The larger the GCS level, the better the patient's condition. It is the overall compatibility of the drug used with all physiological parameters.

[0063] It should be specifically explained in this embodiment that constructing a complication nursing effect evaluation model and importing the complication severity and the complication nursing action correlation into the complication nursing effect evaluation model to evaluate the complication nursing effect includes the following specific steps:

[0064] S41. Substitute the severity level of complications defined by the doctor into the complication severity calculation formula to calculate the complication severity, where the complication severity calculation formula is: Among them, G α , is the severity of the patient's αth complication. The severity of the complication is obtained through the Clavien-D i ndo complication grading system. The lower the complication grade, the better the complication situation of the patient. β, is the number of complications of the patient. μ α , is the probability of occurrence of the αth complication, G max is the maximum severity level of the complication;

[0065] S42. Substitute the nursing actions that affect the complications into the nursing action correlation calculation formula to calculate the nursing action correlation, wherein the nursing action correlation calculation formula for the αth complication is: Among them, G α , is the severity level of the patient's αth complication, θ σ,α , is the influence of the σth nursing action on the αth complication, , is the execution frequency of the th nursing action;

[0066] S43. Substitute the severity of complications and the correlation between complication nursing actions into the complication nursing effect calculation formula to calculate the complication nursing effect, wherein the complication nursing effect calculation formula is: Among them, G′ is the severity of complications, Q α , is the nursing action correlation of the αth complication, and β is the number of complications occurring in patients.

[0067] It should be specifically explained in this embodiment that building a comprehensive nursing effect evaluation model to evaluate the comprehensive nursing effect of patients includes the following specific steps:

[0068] S51. Substitute the patient's monitoring status, drug nursing effect and complication nursing effect into the comprehensive nursing effect evaluation formula to evaluate the comprehensive nursing effect, wherein the comprehensive nursing effect evaluation formula is: Z = D × (L + P) × ζ,, wherein ζ is the patient's critical care scene level, and the critical care scene level is the level of care assessed by medical staff at the patient's care location;

[0069] S52, importing the comprehensive nursing effect evaluation value into the pre-trained deep learning model to obtain a threshold, comparing the nursing effect threshold output by the model with the current comprehensive nursing effect evaluation value, and grading the comprehensive nursing effect evaluation value into excellent nursing effect, good nursing effect, medium nursing effect and low nursing effect;

[0070] S521, excellent nursing effect means that the nursing effect is ideal, the patient's condition, drug management and complication control are good, the current nursing strategy is maintained, and the status is monitored regularly;

[0071] S522, good nursing effect means that the nursing effect is good, but there is room for improvement, and the deficiencies in monitoring status, drug nursing effect and complication nursing effect are analyzed and improved;

[0072] S523, medium nursing effect means that the nursing effect is medium, there are needs for improvement in many aspects, and detailed analysis of patient status, drug care and complication sub-scores is required to conduct nursing regulation;

[0073] S524. Low nursing effectiveness means that the nursing effect is poor and there are serious problems. Notify the medical team immediately and recommend re-evaluation of the nursing plan, including patient monitoring, medication use and complication control.

[0074] Example 2

[0075] like Figure 3 As shown, a brain critical care analysis system based on multi-data fusion is implemented based on the above-mentioned brain critical care analysis method based on multi-data fusion, and specifically includes a data acquisition module, a patient status evaluation module, a drug care effect evaluation module, a complication care effect evaluation module and a comprehensive care effect evaluation module. The data acquisition module is used to acquire patient condition data and care data; the patient status evaluation module is used to evaluate the patient status through physiological monitoring parameters; the drug care effect evaluation module is used to evaluate the drug care effect through drug adaptability and cerebral hemodynamics; the complication care effect evaluation module is used to evaluate the complication care effect through the severity of the complication and the correlation between the complication care actions; the comprehensive care effect evaluation module is used to evaluate the comprehensive care effect of the patient.

[0076] Example 3

[0077] 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;

[0078] The processor executes the above-mentioned brain critical care analysis method based on multi-data fusion by calling the computer program stored in the memory.

[0079] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central, Processing, Units, CPU) and one or more memories, wherein at least one computer program is stored in the memory, and the computer program is loaded and executed by the processor to implement the brain critical care analysis method based on multi-data fusion 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 and output interface, so as to input and output data. This embodiment will not be described in detail here.

[0080] Example 4

[0081] This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon;

[0082] When the computer program is run on a computer device, the computer device executes the above-mentioned brain critical care analysis method based on multi-data fusion.

[0083] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0084] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0085] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0086] 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 invention 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 (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0087] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0088] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0089] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only one way of division, and there may be other ways of division in actual implementation, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0090] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0091] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0092] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0093] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A brain critical care analysis method based on multi-data fusion, characterized in that: It includes the following specific steps: Obtain patient condition data and nursing data; Construct a patient status assessment model, and import physiological monitoring parameters into the patient status assessment model to conduct patient status assessment; Construct a drug nursing effect evaluation model, and introduce drug compatibility and cerebral hemodynamics into the drug nursing effect model to evaluate the drug nursing effect; Construct a complication nursing effect evaluation model, and import the severity of complications and the correlation between complication nursing actions into the complication nursing effect evaluation model to evaluate the complication nursing effect; Construct a comprehensive nursing effect evaluation model to evaluate the comprehensive nursing effect of patients.

2. The brain critical care analysis method based on multi-data fusion according to claim 1, characterized in that: The construction of the patient status assessment model and the introduction of the physiological monitoring parameters into the patient status assessment model for patient status assessment include the following specific steps: S21. Substituting the patient's physiological monitoring parameters into the parameter standardization calculation formula to calculate the standardized parameters, wherein the calculation formula for the i-th standardized parameter is: Among them, A i is the real-time monitoring value of the ith physiological parameter, H i is the standard value of the ith physiological parameter; S22. Substituting the standardized parameters into the patient monitoring status calculation formula to calculate the patient monitoring status, wherein the patient monitoring status calculation formula is: Among them, C i is the i-th standardized parameter, ω i is the weight of the i-th standardized parameter, and n is the total number of physiological monitoring parameters.

3. The brain critical care analysis method based on multi-data fusion according to claim 2, characterized in that: The construction of the drug nursing effect evaluation model and the introduction of drug compatibility and cerebral hemodynamics into the drug nursing effect model for drug nursing effect evaluation include the following specific steps: S31. Substituting the drug dosage used by the patient into the drug compatibility evaluation formula to calculate the compatibility between the drug and the patient, wherein the compatibility evaluation formula between the drug used by the patient and the i-th physiological parameter is: Among them, F j , is the amount of the jth drug added, B j is the standard addition amount of the jth drug, λ j is the weight of the effect of the jth drug on the ith physiological parameter, A i is the real-time monitoring value of the ith physiological parameter, A i ′ is the monitoring value of the physiological parameter without taking drugs, H i is the standard value of the ith physiological parameter, and o is a number that is infinitely close to 0 but not 0; S32. Substituting the intracranial pressure of the patient into the intracranial pressure change degree calculation formula to calculate the degree of change of the intracranial pressure of the patient, wherein the intracranial pressure change degree calculation formula of the patient is: Among them, ICP k , is the intracranial pressure after fluid infusion, ICP z , is the normal value of intracranial pressure, and the patient's cerebral perfusion pressure is substituted into the calculation formula of the degree of change of cerebral perfusion pressure to calculate the degree of change of the patient's cerebral perfusion pressure, where the calculation formula of the degree of change of the patient's cerebral perfusion pressure is: Among them, CPP k , is the cerebral perfusion pressure after fluid infusion, CPP z , is the normal value of cerebral perfusion pressure. Substitute the degree of change of intracranial pressure and cerebral perfusion pressure into the cerebral hemodynamics evaluation formula to evaluate the cerebral hemodynamics after fluid infusion. The cerebral hemodynamics evaluation formula is: S = S ICP +S CPP ; S33. Substitute the drug compatibility and cerebral hemodynamics into the patient drug care effect evaluation formula to evaluate the patient drug care effect. The patient drug care effect evaluation formula is: Among them, R i , is the compatibility between the drug used and the i-th physiological parameter, S, is the cerebral hemodynamics, Y, is the probability of severe brain disease in the patient's age group, and GCS, is the Glasgow Coma Scale.

4. The brain critical care analysis method based on multi-data fusion according to claim 3, characterized in that: The construction of the complication nursing effect evaluation model and the introduction of the complication severity and the complication nursing action correlation into the complication nursing effect evaluation model to evaluate the complication nursing effect include the following specific steps: S41. Substitute the severity level of complications defined by the doctor into the complication severity calculation formula to calculate the complication severity, where the complication severity calculation formula is: Among them, G α , is the severity level of the patient's αth complication, β is the number of complications that occur in the patient, and μ α , is the probability of occurrence of the αth complication, G max , is the maximum severity level of complications; S42. Substitute the nursing actions that affect the complications into the nursing action correlation calculation formula to calculate the nursing action correlation, wherein the nursing action correlation calculation formula for the αth complication is: Among them, G α , is the severity level of the patient's αth complication, θ σ,α , is the influence of the σth nursing action on the αth complication, , is the execution frequency of the th nursing action; S43. Substitute the severity of complications and the correlation between complication nursing actions into the complication nursing effect calculation formula to calculate the complication nursing effect, wherein the complication nursing effect calculation formula is: Among them, G′ is the severity of complications, Q α , is the nursing action correlation of the αth complication, and β is the number of complications occurring in patients.

5. The brain critical care analysis method based on multi-data fusion according to claim 4, characterized in that: The construction of the comprehensive nursing effect evaluation model to evaluate the comprehensive nursing effect of patients includes the following specific steps: S51. Substitute the patient monitoring status, drug nursing effect and complication nursing effect into the comprehensive nursing effect evaluation formula to evaluate the comprehensive nursing effect, wherein the comprehensive nursing effect evaluation formula is: Z=D×(L+P)×ζ, wherein ζ is the patient's critical care scene level; S52. Import the comprehensive nursing effect evaluation value into the pre-trained deep learning model to obtain the threshold value. According to the nursing effect threshold value output by the model, compare it with the current comprehensive nursing effect evaluation value, and grade the comprehensive nursing effect evaluation value. The higher the comprehensive nursing effect evaluation value, the better the nursing effect.

6. A brain critical care analysis system based on multi-data fusion, which is implemented based on the brain critical care analysis method based on multi-data fusion as claimed in any one of claims 1 to 5, characterized in that: Specifically include: A data acquisition module is used to acquire patient condition data and nursing data; A patient status assessment module, used to assess the patient status through physiological monitoring parameters; Drug care effect evaluation module, used to evaluate drug care effect through drug compatibility and cerebral hemodynamics; The complication nursing effect evaluation module is used to evaluate the complication nursing effect through the severity of the complication and the correlation between the complication nursing actions; Comprehensive nursing effectiveness evaluation module is used to evaluate the comprehensive nursing effectiveness of patients.

7. 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 brain critical care analysis method based on multi-data fusion as described in any one of claims 1 to 5 by calling the computer program stored in the memory.

8. 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 brain critical care analysis method based on multi-data fusion as described in any one of claims 1 to 5.

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