Diabetes cognitive impairment effect analysis system and method based on brain function images

Abstract

The invention discloses a diabetes cognitive impairment effect analysis system and method based on a brain function image, belongs to the field of medical systems, and carries out cognitive abnormal change analysis based on an obtained brain function image change condition and a cognitive impairment score condition of a corresponding period. Diabetes abnormal development analysis is carried out based on illness state data of a diabetic patient, cognitive impairment development prediction is carried out based on a diabetes abnormal development analysis result and a cognitive abnormal change analysis result, and cognitive impairment early warning in a treatment process is carried out based on a cognitive impairment development prediction result. The change trend of the brain function images before and after treatment is compared, the cognitive function protection effect of the treatment scheme is evaluated by combining the change of cognitive impairment scores, then the diabetes disease control effect of the treatment scheme is evaluated, the brain function images, the cognitive scores and diabetes disease data are comprehensively analyzed, the overall matching degree of the treatment scheme is evaluated, and the treatment effect of the treatment scheme is evaluated. And the accuracy of matching analysis is effectively improved.

Description

Technical Field

[0001] This application belongs to the field of medical systems, specifically a system and method for analyzing the effects of diabetes-related cognitive impairment based on brain functional imaging. Background Art

[0002] With the continuous increase in the prevalence of diabetes, the research on diabetes complications has gradually become a key focus in the medical field. Diabetes not only causes a series of systemic complications but is also closely related to cognitive dysfunction. Research shows that the risk of cognitive impairment and dementia in diabetic patients is significantly increased. The cognitive impairment caused by diabetes (diabetic cognitive disorder, DCD) has become an important issue affecting the quality of life and long-term health of patients.

[0003] In the prior art, the diagnosis and evaluation of diabetes mainly rely on biochemical indicators such as blood glucose and glycated hemoglobin (HbA1c), while the evaluation of the cognitive function of diabetic patients is still in its infancy. Traditional methods for evaluating cognitive impairment rely on the observation of clinical symptoms and simple psychological assessments, lacking dynamic monitoring and accurate evaluation of cognitive function. In addition, current treatment plans attach great importance to the control of diabetes, but lack effective intervention and monitoring means for concurrent cognitive impairment, resulting in limitations in the personalization and accuracy of treatment effects.

[0004] In view of the above problems, a system and method for analyzing the effects of diabetes-related cognitive impairment based on brain functional imaging are proposed. By comprehensively analyzing changes in brain functional imaging, cognitive impairment scores, and diabetes condition data, this system enables early identification, dynamic monitoring, and prediction of cognitive impairment in diabetic patients, providing a scientific basis for optimizing treatment plans and personalization. Summary of the Invention

[0005] To address the deficiencies in the prior art mentioned in the background art, this application proposes a system and method for analyzing the effects of diabetes-related cognitive impairment based on brain functional imaging. This application conducts an analysis of abnormal cognitive changes based on obtaining the changes in brain functional imaging and the cognitive impairment scores for corresponding periods, conducts an analysis of abnormal diabetes development based on the condition data of diabetic patients, conducts a prediction of the development of cognitive impairment based on the results of the analysis of abnormal diabetes development and the analysis of abnormal cognitive changes, issues a warning of cognitive impairment during the treatment process based on the prediction results of the development of cognitive impairment, compares the change trends of brain functional imaging before and after treatment, and combines the changes in cognitive impairment scores to evaluate the effect of the treatment plan on protecting cognitive function, and further evaluates the effect of the treatment plan on controlling diabetes. By comprehensively analyzing brain functional imaging, cognitive scores, and diabetes condition data, the overall matching degree of the treatment plan is evaluated, effectively improving the accuracy of the matching analysis.

[0006] To achieve the above object, the present application provides the following technical solutions: In the first aspect, the present application provides a method for analyzing the effect of diabetes cognitive impairment based on brain functional imaging, which includes the following specific steps: Step 1: Obtain the changes in brain functional imaging during the treatment process, the cognitive impairment score situation corresponding to the cycle, and the condition data of diabetic patients; Step 2: Conduct an analysis of abnormal cognitive changes based on the obtained changes in brain functional imaging and the cognitive impairment score situation corresponding to the cycle; Step 3: Conduct an analysis of abnormal diabetes development based on the condition data of diabetic patients; Step 4: Predict the development of cognitive impairment based on the results of the analysis of abnormal diabetes development and the results of the analysis of abnormal cognitive changes; Step 5: Give an early warning of cognitive impairment during the treatment process based on the results of the prediction of the development of cognitive impairment.

[0007] Preferably, based on the above solution, the specific content of obtaining the changes in brain functional imaging during the treatment process, the cognitive impairment score situation corresponding to the cycle, and the condition data of diabetic patients is as follows: Step 101: Collect brain tissue image data corresponding to the cycle through the corresponding brain functional imaging acquisition terminal during the treatment process. Among them, during the treatment process, it is necessary to regularly collect brain images to analyze the impact of diabetes on each functional area of the patient's brain; Step 102: Obtain the cognitive function score data of each corresponding brain functional area during the corresponding time period during the treatment process. Here, obtaining the cognitive function score data of each brain functional area is for differentiating the damage of each brain functional area; Step 103: Through the curve of the change in blood glucose concentration of diabetic patients, the blood glucose concentration here can be collected regularly through the corresponding blood glucose concentration collector, and the collected data and curve are stored in the corresponding storage component.

[0008] Preferably, based on the above solution, the analysis of abnormal cognitive changes based on the obtained changes in brain functional imaging and the cognitive impairment score situation corresponding to the cycle includes the following specific steps: Step 201: Obtain the changes in brain functional imaging of each functional area during the treatment process, and conduct an analysis of abnormal changes in the corresponding functional area based on the changes in brain functional imaging of each functional area. Among them, the formula for analyzing abnormal changes in the corresponding functional area is: , where mz is the result of the analysis of abnormal changes in the z-th functional area, n is the number of functional areas, xm is the set distance standard value, is the distance from the i-th functional area to the corresponding functional area, is the damage value of the i-th functional area. Among them, the distance from the i-th functional area to the corresponding functional area is the average value of the distances of each point between the two functional areas, and the distance from the corresponding functional area to the corresponding functional area is 0. Since it is necessary to analyze the abnormal change of the functional area, it is also necessary to analyze the influence of adjacent functional areas on the corresponding functional area. The closer to the corresponding functional area, the greater the influence on the corresponding functional area. The damage value of the functional area is analyzed through the change of the image; Step 202, obtain the change situation of the cognitive function score of the corresponding functional area, and conduct cognitive function abnormality analysis based on the change situation of the cognitive function score within the period. Among them, the cognitive function abnormality analysis formula for the i-th functional area is: , where exp() is the exponential power of the natural constant e, kiz is the cognitive function score of the i-th functional area at the starting moment of the period, kip is the cognitive function score of the i-th functional area at the end moment of the period, and kiq is the average cognitive function score of the i-th functional area of the current person. Through this formula, the change situation of the cognitive function score of the patient's functional area during the treatment process is analyzed. In order to avoid negative results affecting subsequent operations, the exponential power of the natural constant e is used to make the calculation result positive; Step 203, conduct cognitive abnormality change analysis according to the obtained abnormal change result of the corresponding functional area and the cognitive function abnormality analysis result of the functional area. Among them, the cognitive abnormality change analysis formula is: , where, is the influence coefficient of the i-th cognitive functional area, is the abnormal change analysis result of the i-th functional area. In this formula, the influence of the abnormal change of the unit functional area on the cognitive function abnormality is analyzed through the abnormal change result of the corresponding functional area and the cognitive function abnormality analysis result of the functional area. The influence coefficient of the i-th cognitive functional area here has different weights because different cognitive functions have different degrees of influence on the human body.

[0009] Preferably, based on the above solution, the abnormal development analysis of diabetes includes the following specific steps: Step 301, obtain the curve of the change situation of the blood glucose concentration of diabetic patients in the monitoring period; Step 302, conduct abnormal development analysis of diabetic patients based on the curve of the change situation of the blood glucose concentration of diabetic patients in the monitoring period. Among them, the abnormal development analysis formula of diabetes is: , where Qm is the median of the safe range of blood glucose concentration, $G_k$ is the blood glucose concentration collected for the $k$-th time within a period, $dt$ is the time integral, $T$ is the number of times of blood glucose concentration collection within a period, $b$ is the weight of the average abnormal proportion, $c$ is the weight of the change abnormal proportion, $Q_z$ is the average value of the blood glucose concentration in the second half of the monitoring period, $Q_c$ is the average value of the blood glucose concentration in the first half of the monitoring period. The average value of the blood glucose concentration in the second half of the monitoring period minus the average value of the blood glucose concentration in the first half of the monitoring period is the change amount of the blood glucose concentration. This change amount represents the magnitude of the change in blood glucose abnormality at the beginning and end of the previous operation period, and can reflect the change trend of blood glucose. Specifically, the previous formula only represents the average abnormal degree within one period and cannot reflect the change trend within the period. On the basis of comprehensively considering the average abnormal degree and the change amount of diabetes, the abnormal state of diabetes can be evaluated more comprehensively.

[0010] Preferably, on the basis of the above solution, the prediction of cognitive impairment development based on the analysis results of diabetes abnormal development and the analysis results of cognitive abnormal changes includes the following specific contents: Obtain the analysis results of diabetes abnormal development and the analysis results of cognitive abnormal changes obtained by evaluation, and obtain the prediction result of cognitive impairment development by performing weighted summation on the analysis results of diabetes abnormal development and the analysis results of cognitive abnormal changes.

[0011] Preferably, on the basis of the above solution, the early warning of cognitive impairment during the treatment process based on the prediction result of cognitive impairment development includes the following specific steps: Obtain the prediction result of cognitive impairment development, and compare the obtained prediction result of cognitive impairment development with the set prediction threshold of cognitive impairment development. If the prediction result of cognitive impairment development is greater than or equal to the set prediction threshold of cognitive impairment development, it means that the treatment process will cause cognitive impairment to the patient, and the treatment process does not match the patient, and a mismatch warning is performed, and the treatment method needs to be changed. If the prediction result of cognitive impairment development is less than the set prediction threshold of cognitive impairment development, it means that the treatment process matches the patient.

[0012] In a second aspect, the present application provides a system for analyzing the effect of diabetes-related cognitive impairment based on brain functional imaging, which is implemented based on the above-mentioned method for analyzing the effect of diabetes-related cognitive impairment based on brain functional imaging. Specifically, it includes a data acquisition module, a cognitive abnormality change analysis module, a diabetes abnormal development analysis module, a cognitive impairment development prediction module, and a cognitive impairment warning module. Among them, the data acquisition module acquires the changes in brain functional imaging during the treatment process, the cognitive impairment score situation in the corresponding period, and the condition data of diabetic patients. The cognitive abnormality change analysis module conducts an analysis of cognitive abnormality changes based on the acquired changes in brain functional imaging and the cognitive impairment score situation in the corresponding period. The diabetes abnormal development analysis module conducts an analysis of diabetes abnormal development based on the condition data of diabetic patients. The cognitive impairment development prediction module predicts the development of cognitive impairment based on the results of the diabetes abnormal development analysis and the results of the cognitive abnormality change analysis. The cognitive impairment warning module issues a warning of cognitive impairment during the treatment process based on the results of the cognitive impairment development prediction.

[0013] In a third aspect, the present application 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; The processor executes the above-mentioned method for analyzing the effect of diabetes-related cognitive impairment based on brain functional imaging by calling the computer program stored in the memory.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium storing instructions, which, when run on a computer, cause the computer to execute the method for analyzing the effect of diabetes-related cognitive impairment based on brain functional imaging as described above.

[0015] Meanwhile, compared with the prior art, the technical effects and advantages of the present application are as follows: The advantages of the present application are as follows: The present application conducts an analysis of cognitive abnormality changes based on the acquired changes in brain functional imaging and the cognitive impairment score situation in the corresponding period, conducts an analysis of diabetes abnormal development based on the condition data of diabetic patients, predicts the development of cognitive impairment based on the results of the diabetes abnormal development analysis and the results of the cognitive abnormality change analysis, and issues a warning of cognitive impairment during the treatment process based on the results of the cognitive impairment development prediction. By comparing the change trends of brain functional imaging before and after treatment and combining the changes in cognitive impairment scores, the effect of the treatment plan on protecting cognitive function is evaluated, and then the effect of the treatment plan on controlling the diabetes condition is evaluated. The brain functional imaging, cognitive scores, and diabetes condition data are comprehensively analyzed to evaluate the overall matching degree of the treatment plan, effectively improving the accuracy of the matching analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings; Figure 1 It is a schematic diagram of the overall process of the analysis method for the effect of diabetic cognitive impairment based on brain functional imaging; Figure 2 It is a schematic diagram of the specific process of step 2 of the analysis method for the effect of diabetic cognitive impairment based on brain functional imaging; Figure 3 It is a schematic diagram of the specific process of step 3 of the analysis method for the effect of diabetic cognitive impairment based on brain functional imaging; Figure 4 It is a schematic diagram of the module composition of the analysis system for the effect of diabetic cognitive impairment based on brain functional imaging; Figure 5 It is a schematic diagram of the electronic device of the present application. Detailed implementation manners

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. The description of at least one exemplary embodiment below is actually only illustrative and in no way limits the present application and its application or use.

[0018] In addition, the drawings are only schematic diagrams of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus repeated descriptions thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

[0019] It should be understood that although the terms "first", "second", etc. may be used here to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit can be called the second unit, and similarly the second unit can be called the first unit. The term "and / or" used here includes any and all combinations of one or more of the listed associated items.

[0020] To solve the technical problems raised in the background art: In the prior art, the diagnosis and evaluation of diabetes mainly rely on biochemical indicators such as blood glucose and glycated hemoglobin (HbA1c), while the evaluation of the cognitive function of diabetic patients is still in its infancy. Traditional methods for evaluating cognitive impairment rely on the observation of clinical symptoms and simple psychological assessments, lacking dynamic monitoring and precise evaluation of cognitive function. In addition, current treatment regimens attach great importance to the control of diabetes, but lack effective intervention and monitoring means for concurrent cognitive impairment, resulting in limitations in the personalization and precision of treatment effects. This application provides a preferred embodiment: As Figures 1 - 3 shown, a method for analyzing the effect of diabetic cognitive impairment based on brain functional imaging, which includes the following specific steps: Step 1, obtain the changes in brain functional imaging during the treatment process, the cognitive impairment score in the corresponding period, and the disease data of diabetic patients; In this embodiment, the specific content of obtaining the changes in brain functional imaging during the treatment process, the cognitive impairment score in the corresponding period, and the disease data of diabetic patients is as follows: Step 101, collect the brain tissue imaging data in the corresponding period through the corresponding brain functional imaging acquisition terminal during the treatment process. Among them, during the treatment process, the brain imaging needs to be collected regularly to analyze the impact of diabetes on each functional area of the patient's brain. Exemplarily, the corresponding brain functional imaging acquisition terminal includes brain image acquisition terminals such as MRI and CT, and obtain the image changes in each functional area of the brain from them; Step 102, obtain the cognitive function score data of each corresponding brain functional area during the corresponding time period during the treatment process. Exemplarily, the cognitive function score can be the MMSE (Mini-Mental State Examination) scoring standard. Among them, MMSE is a widely used standardized test tool for evaluating the cognitive function status of individuals. It mainly covers the cognitive functions in several key areas, including orientation, memory, attention, calculation ability, language function, visuospatial ability, etc. The full score of MMSE is 30 points, and the lower the score, the more severe the cognitive impairment. Here, obtaining the cognitive function score data of each brain functional area is for distinguishing the damage in each brain functional area; Step 103, through the curve of the blood glucose concentration change of diabetic patients, where the blood glucose concentration can be collected regularly through the corresponding blood glucose concentration collector. Exemplarily, for example, it is collected at a specified time every day within a month to make the data comparable and avoid errors, and store the collected data and curve in the corresponding storage component; Step 2, conduct an analysis of cognitive abnormal changes based on the obtained changes in brain functional imaging and the cognitive impairment score in the corresponding period; In this embodiment, the analysis of cognitive abnormality changes based on the changes in brain function images and the cognitive impairment scores of the corresponding period includes the following specific steps: Step 201, obtaining the changes of brain function images of each functional area during the treatment process, and performing abnormal analysis of changes in the corresponding functional area based on the changes of brain function images of each functional area, wherein the abnormal analysis formula of changes in the corresponding functional area is: , where mz is the abnormal analysis result of the change of the zth functional area, n is the number of functional areas, and xm is the set distance standard value. is the distance from the ith functional area to the corresponding functional area, is the damage value of the ith functional area, wherein the distance from the ith functional area to the corresponding functional area is the average of the distances between the two functional areas, and the distance from the corresponding functional area to the corresponding functional area is 0. Since the abnormal changes in the functional areas need to be analyzed, the influence of the adjacent functional areas on the corresponding functional areas should also be analyzed. The closer to the corresponding functional area, the greater the influence on the corresponding functional area. The damage value of the functional area is analyzed by the change of the image. For example, the damage value calculation formula of the ith functional area is: , where mi is the number of pixels in the ith functional area, is the pixel value of the jth pixel in the i-th functional area, is the pixel value of the jth pixel in the ith functional area at the previous monitoring moment, is the pixel value of the jth pixel point in the i-th functional area when it is not diseased. In this way, the damage of the functional area is analyzed by the change of pixels in this formula; Step 202: Obtain the change of cognitive function score of the corresponding functional area, and perform cognitive function abnormality analysis based on the change of cognitive function score within the cycle, wherein the cognitive function abnormality analysis formula of the ith functional area is: , where exp() is the power of the natural constant e, kiz is the cognitive function score of the ith functional area at the start of the cycle, kip is the cognitive function score of the ith functional area at the end of the cycle, and kiq is the average cognitive function score of the ith functional area of ​​the current person. This formula is used to analyze the changes in the cognitive function scores of the functional areas of patients during the treatment process. In order to avoid the result being a negative number and affecting subsequent calculations, the power of the natural constant e is used to make the calculation result positive; Step 203: Perform cognitive abnormality change analysis based on the obtained abnormal change results of the corresponding functional areas and the abnormal analysis results of the cognitive function of the functional areas, wherein the cognitive abnormality change analysis formula is: ,in, is the influence coefficient of the i-th cognitive function area, It is the analysis result of the change abnormality of the i-th functional area. In this formula, the influence of the change abnormality of the unit functional area on the cognitive function abnormality is analyzed through the corresponding change abnormality result of the functional area and the analysis result of the cognitive function abnormality of the functional area. The influence coefficient of the i-th cognitive functional area here has different weights because different cognitive functions have different degrees of influence on the human body. Exemplarily, for example, attention and calculation ability, so the weights are different. The acquisition method is that experts in this field obtain scores according to the needs of human cognitive functions; Step 3: Conduct an analysis of the abnormal development of diabetes based on the condition data of diabetic patients; In this embodiment, the analysis of the abnormal development of diabetes includes the following specific steps: Step 301: Obtain the curve of the blood glucose concentration change of diabetic patients in the monitoring period; Step 302: Conduct an analysis of the abnormal development of diabetes based on the curve of the blood glucose concentration change of diabetic patients in the monitoring period. Among them, the formula for the analysis of the abnormal development of diabetes is: , where Qm is the median of the safe range of blood glucose concentration, is the blood glucose concentration collected for the k-th time within the period, dt is the time integral, T is the number of blood glucose concentration collections within the period, b is the average abnormal proportion weight, c is the change abnormal proportion weight, Qz is the average blood glucose concentration in the second half of the monitoring period, Qc is the average blood glucose concentration in the first half of the monitoring period. The average blood glucose concentration in the second half of the monitoring period minus the average blood glucose concentration in the first half of the monitoring period is the blood glucose concentration change amount. This change amount represents the change amount of the blood glucose abnormality degree at the beginning and end of the previous operation cycle, and can reflect the change trend of blood glucose. Specifically, the previous formula only represents the average abnormal degree within one cycle and cannot reflect the change trend within the cycle. On the basis of comprehensively considering the average abnormal degree and change amount of diabetes, the abnormal state of diabetes can be evaluated more comprehensively; Step 4: Predict the development of cognitive impairment based on the analysis result of the abnormal development of diabetes and the analysis result of the cognitive abnormality change; In this embodiment, predicting the development of cognitive impairment based on the analysis result of the abnormal development of diabetes and the analysis result of the cognitive abnormality change includes the following specific contents: Obtain the analysis result of the abnormal development of diabetes and the analysis result of the cognitive abnormality change obtained through evaluation, and obtain the prediction result of the development of cognitive impairment by performing weighted summation on the analysis result of the abnormal development of diabetes and the analysis result of the cognitive abnormality change; Step 5: Give a warning of cognitive impairment during the treatment process based on the prediction result of the development of cognitive impairment; In this embodiment, the cognitive impairment warning during the treatment process based on the prediction result of cognitive impairment development includes the following specific steps: Obtain the prediction result of cognitive impairment development, compare the obtained prediction result of cognitive impairment development with the set prediction threshold of cognitive impairment development. If the prediction result of cognitive impairment development is greater than or equal to the set prediction threshold of cognitive impairment development, it indicates that the treatment process will cause cognitive impairment to the patient, the treatment process does not match the patient, and a mismatch warning is given, and the treatment method needs to be changed. If the prediction result of cognitive impairment development is less than the set prediction threshold of cognitive impairment development, it indicates that the treatment process matches the patient.

[0021] Furthermore, the value-taking method of the set parameters (such as thresholds and weights of each set parameter) in this embodiment is: obtained through historical data experiments. The specific experimental methods are, for example: obtain the changes in brain function images during the historical treatment process, the cognitive impairment score situation in the corresponding period, and the condition data of diabetic patients, obtain the judgment result on whether the cognitive impairment after the historical patient's treatment is within the safe range, substitute the historical data into each step of this embodiment to obtain the calculation result on whether the treatment process matches the patient, import the calculation result and the judgment result into the fitting software, and output the value-taking of the set parameters (such as thresholds and weights of each set parameter) that meets the maximum judgment result accuracy rate.

[0022] Furthermore, the advantages of this embodiment are explained here. This embodiment conducts cognitive abnormality change analysis based on the obtained changes in brain function images and the cognitive impairment score situation in the corresponding period, conducts diabetes abnormal development analysis based on the condition data of diabetic patients, conducts cognitive impairment development prediction based on the diabetes abnormal development analysis result and the cognitive abnormality change analysis result, conducts cognitive impairment warning during the treatment process based on the cognitive impairment development prediction result, compares the change trends of brain function images before and after treatment, combines the changes in cognitive impairment scores, evaluates the effect of the treatment plan on protecting cognitive function, and further evaluates the effect of the treatment plan on controlling the diabetes condition. The brain function images, cognitive scores, and diabetes condition data are comprehensively analyzed to evaluate the overall matching degree of the treatment plan, effectively improving the accuracy of the matching analysis.

[0023] Secondly, as Figure 4As shown in the figure, this embodiment also provides a system for analyzing the effect of diabetes cognitive impairment based on brain functional imaging, which specifically includes a data acquisition module, a cognitive abnormality change analysis module, a diabetes abnormal development analysis module, a cognitive impairment development prediction module, and a cognitive impairment warning module. Among them, the data acquisition module acquires the changes in brain functional imaging during the treatment process, the cognitive impairment score situation in the corresponding period, and the condition data of diabetes patients. The cognitive abnormality change analysis module conducts cognitive abnormality change analysis based on the acquired changes in brain functional imaging and the cognitive impairment score situation in the corresponding period. The diabetes abnormal development analysis module conducts diabetes abnormal development analysis based on the condition data of diabetes patients. The cognitive impairment development prediction module conducts cognitive impairment development prediction based on the results of diabetes abnormal development analysis and cognitive abnormality change analysis. The cognitive impairment warning module conducts cognitive impairment warning during the treatment process based on the results of cognitive impairment development prediction. Among them, the connection relationship of the data acquisition module, the cognitive abnormality change analysis module, the diabetes abnormal development analysis module, the cognitive impairment development prediction module, and the cognitive impairment warning module is as Figure 4 shown.

[0024] Then, as Figure 5 shown, this embodiment also provides an electronic device, including: a processor and a memory. Among them, a computer program that can be called by the processor is stored in the memory. The processor executes the above-mentioned method for analyzing the effect of diabetes cognitive impairment based on brain functional imaging by calling the computer program stored in the memory.

[0025] This electronic device may have relatively large differences 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 analyzing the effect of diabetes cognitive impairment based on brain functional imaging provided by 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.

[0026] Finally, this embodiment proposes a computer-readable storage medium, on which a rewritable computer program is stored. When the computer program runs on a computer device, it enables the computer device to execute the above-mentioned method for analyzing the effect of diabetes cognitive impairment based on brain functional imaging.

[0027] For example, the computer-readable storage medium can be a read-only memory, a random access memory, a read-only optical disc, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0028] Those skilled in the art should understand that the embodiments of the present invention can provide a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0029] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can also be implemented. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices generate means for implementing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0030] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0031] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0032] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0033] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media.

[0034] A computer-readable medium includes permanent and non-permanent, removable and non-removable media and can implement information storage by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic tape disk storage or other magnetic storage devices, or any other non-transitory media that can be used to store information accessible by a computing device. As defined herein, a computer-readable medium does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0035] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

[0036] The above are only embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the scope of the claims of the present invention.

Claims

1. A method for analyzing the effect of diabetes cognitive impairment based on brain functional imaging, characterized in that, It includes the following specific steps: Step 1: Obtain the changes in brain function images during the treatment process, the cognitive impairment score in the corresponding period, and the condition data of diabetic patients; Step 2: Conduct an analysis of abnormal cognitive changes based on the obtained changes in brain function images and the cognitive impairment score in the corresponding period; Step 3: Conduct an analysis of abnormal diabetes development based on the condition data of diabetic patients; Step 4: Predict the development of cognitive impairment based on the results of the analysis of abnormal diabetes development and the analysis of abnormal cognitive changes; Step 5: Issue a warning of cognitive impairment during the treatment process based on the prediction result of the development of cognitive impairment.

2. The method for analyzing the effect of diabetes cognitive impairment based on brain functional imaging according to claim 1, wherein The specific content of obtaining the changes in brain function images during the treatment process, the cognitive impairment score in the corresponding period, and the condition data of diabetic patients is as follows: Step 101: During the treatment process, collect brain tissue image data in the corresponding period through the corresponding brain function image acquisition terminal; Step 102: Obtain the cognitive function score data of each corresponding brain function area in the corresponding time period during the treatment process; Step 103: Through the curve of the blood glucose concentration change of diabetic patients, and store the collected data and curve in the corresponding storage component.

3. The method for analyzing the effect of diabetes cognitive impairment based on brain functional imaging according to claim 2, wherein, The analysis of abnormal cognitive changes based on the obtained changes in brain function images and the cognitive impairment score in the corresponding period includes the following specific steps: Step 201, obtain the changes in brain function images of each functional area during the treatment process, and perform abnormal change analysis on the corresponding functional areas based on the changes in brain function images of each functional area. Among them, the formula for abnormal change analysis of the corresponding functional area is: , where mz is the result of abnormal change analysis of the z-th functional area, n is the number of functional areas, xm is the set distance standard value, is the distance from the i-th functional area to the corresponding functional area, is the damage value of the i-th functional area. Among them, the distance from the i-th functional area to the corresponding functional area is the average value of the distances between each point between the two functional areas; Step 202: Obtain the change in the cognitive function score of the corresponding functional area, and perform an analysis of abnormal cognitive function based on the change in the cognitive function score within the period. Among them, the formula for analyzing abnormal cognitive function in the i-th functional area is: , where exp() is the exponential power of the natural constant e, kiz is the cognitive function score of the i-th functional area at the start time of the period, kip is the cognitive function score of the i-th functional area at the end time of the period, and kiq is the average cognitive function score of the i-th functional area of the current person; Step 203: Perform cognitive abnormality change analysis based on the obtained abnormal results of corresponding functional area changes and the abnormal analysis results of cognitive functions in the functional area. The cognitive abnormality change analysis formula is as follows: , where is the influence coefficient of the i-th cognitive function area, is the abnormal analysis result of the change in the i-th functional area.

4. The method for analyzing the effect of diabetes cognitive impairment based on brain functional imaging according to claim 3, wherein The analysis of abnormal diabetes development includes the following specific steps: Step 301: Obtain the curve of the blood glucose concentration change of diabetic patients in the monitoring period; Step 302: Analyze the abnormal development of diabetes in diabetic patients based on the curve of the change in blood glucose concentration of diabetic patients during the monitoring period. The formula for analyzing the abnormal development of diabetes is as follows: , where Qm is the median of the safe range of blood glucose concentration, is the blood glucose concentration collected for the kth time within the period, dt is the time integral, T is the number of blood glucose concentration collections within the period, b is the weight of the average abnormal proportion, c is the weight of the change abnormal proportion, Qz is the average blood glucose concentration in the second half of the monitoring period, and Qc is the average blood glucose concentration in the first half of the monitoring period.

5. The method for analyzing the effect of diabetes cognitive impairment based on brain functional imaging according to claim 4, wherein The prediction of the development of cognitive impairment based on the results of the analysis of abnormal diabetes development and the analysis of abnormal cognitive changes includes the following specific content: Obtain the results of the analysis of abnormal diabetes development and the analysis of abnormal cognitive changes obtained through evaluation, and obtain the prediction result of the development of cognitive impairment by performing weighted summation on the results of the analysis of abnormal diabetes development and the analysis of abnormal cognitive changes.

6. The method for analyzing the effect of diabetes cognitive impairment based on brain functional imaging according to claim 5, wherein The warning of cognitive impairment during the treatment process based on the prediction result of the development of cognitive impairment includes the following specific steps: Obtain the prediction result of the development of cognitive impairment obtained, compare the obtained prediction result of the development of cognitive impairment with the set prediction threshold for the development of cognitive impairment. If the prediction result of the development of cognitive impairment is greater than or equal to the set prediction threshold for the development of cognitive impairment, it indicates that the treatment process will cause cognitive impairment to the patient, the treatment process does not match the patient, and a mismatch warning is issued, and the treatment method needs to be changed. If the prediction result of the development of cognitive impairment is less than the set prediction threshold for the development of cognitive impairment, it indicates that the treatment process matches the patient.

7. A system for analyzing the effect of diabetes-related cognitive impairment based on brain functional imaging, which is implemented based on the method for analyzing the effect of diabetes-related cognitive impairment based on brain functional imaging according to any one of claims 1-6, characterized in that Specifically, it includes a data acquisition module, a cognitive abnormality change analysis module, a diabetic abnormal development analysis module, a cognitive impairment development prediction module, and a cognitive impairment warning module; among them, the data acquisition module acquires the changes in brain functional images during the treatment process, the cognitive impairment score in the corresponding period, and the condition data of diabetic patients; the cognitive abnormality change analysis module conducts cognitive abnormality change analysis based on the acquired changes in brain functional images and the cognitive impairment score in the corresponding period; the diabetic abnormal development analysis module conducts diabetic abnormal development analysis based on the condition data of diabetic patients; the cognitive impairment development prediction module conducts cognitive impairment development prediction based on the results of diabetic abnormal development analysis and cognitive abnormality change analysis; the cognitive impairment warning module conducts cognitive impairment warning during the treatment process based on the results of cognitive impairment development prediction.

8. 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 method for analyzing the effect of diabetic cognitive impairment based on brain functional images according to any one of claims 1-6 by calling the computer program stored in the memory.

9. A computer-readable storage medium, characterized in that, Stores instructions that, when the instructions run on a computer, cause the computer to execute the method for analyzing the effect of diabetic cognitive impairment based on brain functional images according to any one of claims 1-6.

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