Method and system for evaluating severity of ulcerative colitis
By performing multi-dimensional mining of the detection report data of ulcerative colitis and splicing of feature description sets, and using the compressed attention mechanism to generate derivative features, the problem of insufficient accuracy in severity assessment of ulcerative colitis in the prior art is solved, and more efficient and accurate evaluation results are achieved.
Patent Information
- Application Number
- CN202411581448.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-07
- Publication Date
- 2025-02-28
AI Technical Summary
The prior art is difficult to improve the accuracy of severity assessment of ulcerative colitis, especially in terms of automated judgments.
By performing multi-dimensional mining on the detection report data of ulcerative colitis, the original ulcerative colitis feature description set is generated, and based on the characteristic description set of two adjacent characteristic description sets of disease conditions, a derivative characteristic description set is generated through the compression attention mechanism, and finally the characteristic description set of the lowest degree of disease conditions is spliced to form a more accurate ulcerative colitis feature description set.
It improves the accuracy and accuracy of severity assessment of ulcerative colitis, reduces the workload of medical staff, and improves the evaluation efficiency through automated judgments.
Smart Images
Figure CN119541851A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of data acquisition, and in particular, to a method and system for assessing the severity of ulcerative colitis. Background Art
[0002] Ulcerative colitis is generally checked by equipment and then judged by relevant medical staff, and then the severity of the patient's ulcerative colitis can be determined. With the continuous development and progress of artificial intelligence, the application fields of artificial intelligence are becoming more and more extensive. After continuous thinking and research, the inventor has combined artificial intelligence with ulcerative colitis severity assessment technology. When the examination report comes out, the severity of ulcerative colitis can be intelligently judged. In this way, the workload of medical staff can be effectively reduced. However, how to improve the accuracy of the assessment is a technical problem that is difficult to solve at present. Summary of the invention
[0003] In order to improve the technical problems existing in the related technologies, the present application provides a method and system for assessing the severity of ulcerative colitis.
[0004] In a first aspect, a method for assessing the severity of ulcerative colitis is provided, comprising: Perform multi-dimensional mining on the ulcerative colitis test report data to be processed to obtain a number of original ulcerative colitis feature description sets, each of which corresponds to a disease severity level; For adjacent first disease condition levels and a second disease condition level higher than the first disease condition level, the ath ulcerative colitis feature description set of the first disease condition level is optimized based on the ath ulcerative colitis feature description set of the second disease condition level to obtain an optimized ulcerative colitis feature description set of the ath ulcerative colitis feature description set of the first disease condition level, and a mixed ulcerative colitis feature description set is generated based on the optimized ulcerative colitis feature description set and the ath ulcerative colitis feature description set of the second disease condition level, wherein a is a natural number greater than 1; Concatenate all ulcerative colitis feature description sets between the original ulcerative colitis feature description set of the first disease condition level and the a-th ulcerative colitis feature description set, as well as the mixed ulcerative colitis feature description set, to obtain the a+1-th ulcerative colitis feature description set corresponding to the first disease condition level; splicing the original ulcerative colitis feature description set and the derived ulcerative colitis feature description set in the lowest disease condition level among all disease condition levels to obtain the ulcerative colitis feature description set of the ulcerative colitis test report data that needs to be processed; The ulcerative colitis test report data that need to be processed are evaluated and processed according to the ulcerative colitis feature description set of the ulcerative colitis test report data that need to be processed.
[0005] In the present application, the mixed ulcerative colitis feature description set is generated according to the optimized ulcerative colitis feature description set and the ath ulcerative colitis feature description set of the second disease condition degree, including: Compressing the ath ulcerative colitis feature description set of the second disease condition level to obtain a compressed feature, or performing a comparison process on the ath ulcerative colitis feature description set of the second disease condition level to obtain a compressed feature, or performing a compression and comparison process on the ath ulcerative colitis feature description set of the second disease condition level to obtain a compressed feature; The optimized ulcerative colitis feature description set and the compressed features are spliced to obtain the mixed ulcerative colitis feature description set.
[0006] In the present application, the optimized ulcerative colitis feature description set and the compressed feature are spliced to obtain the mixed ulcerative colitis feature description set, including: Adding the feature attribute value corresponding to the optimized ulcerative colitis feature description set and the feature attribute value corresponding to the compressed feature to obtain the feature attribute value corresponding to the mixed ulcerative colitis feature description set; The mixed ulcerative colitis feature description set is generated according to the feature attribute values corresponding to the mixed ulcerative colitis feature description set.
[0007] In the present application, the ath ulcerative colitis feature description set of the first disease condition level is optimized based on the ath ulcerative colitis feature description set of the second disease condition level to obtain an optimized ulcerative colitis feature description set of the ath ulcerative colitis feature description set of the first disease condition level, including: Performing projection processing on the ath ulcerative colitis feature description set of the second disease condition degree to obtain a sample colitis feature projection result; Based on the sample enteritis feature projection result, the features in the ath ulcerative colitis feature description set of the first disease condition degree are optimized to obtain the optimized ulcerative colitis feature description set.
[0008] In the present application, the features in the ath ulcerative colitis feature description set of the first disease condition degree are optimized based on the sample enteritis feature projection result to obtain the optimized ulcerative colitis feature description set, including: Multiplying the sample enteritis feature projection result by the feature attribute value contained in the ath ulcerative colitis feature description set of the first disease condition degree to obtain an optimized feature attribute value; The optimized ulcerative colitis feature description set is generated according to the optimized feature attribute values.
[0009] In the present application, after the projection processing is performed on the ath ulcerative colitis feature description set of the second disease condition degree, the method further includes: The result of the projection processing is debugged to obtain the debugging result of the sample enteritis feature projection result.
[0010] In the present application, all ulcerative colitis feature description sets between the original ulcerative colitis feature description set of the first disease condition level and the a-th ulcerative colitis feature description set, as well as the mixed ulcerative colitis feature description set are spliced to obtain the a+1-th ulcerative colitis feature description set corresponding to the first disease condition level, including: Optimizing all ulcerative colitis feature description sets between the original ulcerative colitis feature description set of the first disease condition degree and the ath ulcerative colitis feature description set based on the data optimization thread to obtain an optimized ulcerative colitis feature description set; The optimized ulcerative colitis feature description set and the mixed ulcerative colitis feature description set are convolutionally concatenated to obtain the a+1th ulcerative colitis feature description set corresponding to the first disease condition degree.
[0011] In this application, multi-dimensional mining is performed on the ulcerative colitis test report data to be processed to obtain several original ulcerative colitis feature description sets, including: Preprocessing the ulcerative colitis test report data that needs to be processed to obtain a preprocessing result; Extracting target features corresponding to the preset analysis method in the preprocessing results; The target features are subjected to multi-dimensional mining processing to obtain a set of original ulcerative colitis feature descriptions corresponding to each degree of the disease condition.
[0012] In the present application, the ulcerative colitis test report data to be processed includes medical images; evaluating and processing the ulcerative colitis test report data to be processed according to the ulcerative colitis feature description set of the ulcerative colitis test report data to be processed includes: According to the ulcerative colitis feature description set of the ulcerative colitis test report data to be processed and the target intestinal condition to be processed, the medical image is evaluated and processed to obtain analysis data of the target intestinal condition.
[0013] In a second aspect, a system for assessing the severity of ulcerative colitis is provided, comprising a processor and a memory communicating with each other, wherein the processor is used to read a computer program from the memory and execute the computer program to implement the above method.
[0014] The embodiment of the present application provides a method and system for evaluating the severity of ulcerative colitis. The method and system perform multi-dimensional mining processing on the ulcerative colitis test report data that needs to be processed to obtain the original ulcerative colitis feature description set corresponding to each disease degree. Based on the original ulcerative colitis feature description set of two adjacent disease degrees, a derived ulcerative colitis feature description set of the lower disease degree of the two disease degrees is generated in sequence through a compressed attention mechanism. Finally, the original ulcerative colitis feature description set and the derived ulcerative colitis feature description set of the lowest disease degree among the disease degrees are concatenated to obtain the ulcerative colitis feature description set of the ulcerative colitis test report data that needs to be processed. Description set, so that based on the compressed attention mechanism, two adjacent ulcerative colitis feature description sets of the disease degree can be processed to obtain the ulcerative colitis feature description sets of each disease degree, and then several ulcerative colitis feature description sets of the lowest disease degree are spliced to obtain the ulcerative colitis feature description set of the ulcerative colitis test report data that needs to be processed. This processing method splices the features of several disease degrees, and thus can more effectively extract the important data of the ulcerative colitis test report data that needs to be processed, ensuring that a more accurate ulcerative colitis feature description set of the ulcerative colitis test report data that needs to be processed is obtained, thereby improving the accuracy and precision of data evaluation. BRIEF DESCRIPTION OF THE DRAWINGS
[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.
[0016] Figure 1 This is a flow chart of a method for assessing the severity of ulcerative colitis provided in an embodiment of the present application. DETAILED DESCRIPTION
[0017] In order to better understand the above technical scheme, the technical scheme of the present application is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical scheme of the present application, rather than limitations on the technical scheme of the present application. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.
[0018] See also Figure 1 , shows a method for assessing the severity of ulcerative colitis, which may include the technical solution described in the following steps S410-S440.
[0019] In step S410, multi-dimensional mining is performed on the ulcerative colitis test report data to be processed to obtain a plurality of original ulcerative colitis feature description sets, each of which corresponds to a disease condition degree.
[0020] In one embodiment of the present application, after obtaining the ulcerative colitis test report data that needs to be processed, the ulcerative colitis test report data that needs to be processed is first mined to obtain a set of ulcerative colitis feature descriptions of the ulcerative colitis test report data that needs to be processed. Among them, the mining process in this embodiment is a multi-dimensional mining process of the ulcerative colitis test report data that needs to be processed, so as to obtain a set of original ulcerative colitis feature descriptions of different feature depths, so that each original ulcerative colitis feature description set corresponds to a degree of disease condition, so as to extract more comprehensive and important data from the ulcerative colitis test report data that needs to be processed based on several levels of ulcerative colitis feature description sets.
[0021] It should be noted that the term "multiple times" in this embodiment is used to represent at least twice. In this embodiment, at least two original ulcerative colitis feature description sets are obtained by performing at least two mining processes at different scales, and the number of original ulcerative colitis feature description sets is the same as the number of disease degree. Each original ulcerative colitis feature description set is the first ulcerative colitis feature description set in the corresponding disease degree, and is used to obtain the remaining derived ulcerative colitis feature description sets in the disease degree based on the first ulcerative colitis feature description set in each disease degree.
[0022] In one embodiment of the present application, multi-dimensional mining is performed on the ulcerative colitis test report data to be processed to obtain a plurality of original ulcerative colitis feature description sets, each of which corresponds to a degree of disease condition, and specifically includes the following steps: Preprocessing the ulcerative colitis test report data that needs to be processed to obtain a preprocessing result; Extracting target features corresponding to the preset analysis method in the preprocessing results; The target features are subjected to multi-dimensional mining processing to obtain a set of original ulcerative colitis feature descriptions corresponding to each degree of the disease condition.
[0023] Specifically, the method of preprocessing the ulcerative colitis test report data to be processed in this embodiment is not described in detail here. After preprocessing the ulcerative colitis test report data to be processed to obtain the preprocessing result, the feature corresponding to the preset analysis method in the preprocessing result is extracted as the target feature, and the ulcerative colitis test report data to be processed is subjected to multi-dimensional mining processing based on the target feature to obtain the original ulcerative colitis feature description set corresponding to each degree of disease condition.
[0024] In step S420, based on the original ulcerative colitis feature description sets of two adjacent disease condition levels, a derived ulcerative colitis feature description set of the lower disease condition level among the two disease condition levels is sequentially generated through a compressed attention mechanism.
[0025] In one embodiment of the present application, each original ulcerative colitis feature description set corresponds to a disease condition level, and in each disease condition level, the original ulcerative colitis feature description set serves as the first ulcerative colitis feature description set in the disease condition level. In addition to the original ulcerative colitis feature description set, each disease condition level also includes a derived ulcerative colitis feature description set generated based on the original ulcerative colitis feature description set, so as to extract comprehensive and accurate features based on the original ulcerative colitis feature description set and the derived ulcerative colitis feature description set in all disease condition levels.
[0026] In this embodiment, when generating a derived ulcerative colitis feature description set in addition to the original ulcerative colitis feature description set in the disease condition level, based on the original ulcerative colitis feature description sets in two adjacent disease condition levels, a derived ulcerative colitis feature description set of the lower disease condition level of the two disease condition levels is generated in sequence through a compressed attention mechanism to obtain a derived ulcerative colitis feature description set corresponding to each disease condition level in addition to the original ulcerative colitis feature description set.
[0027] In one embodiment of the present application, based on two adjacent original ulcerative colitis feature description sets of disease conditions, a process of sequentially generating a derived ulcerative colitis feature description set of a lower disease condition degree among the two disease condition degrees through a compressed attention mechanism specifically includes the following steps S610 to S620, which are described in detail as follows: In step S610, for an adjacent first disease condition level and a second disease condition level higher than the first disease condition level, a mixed ulcerative colitis feature description set of the ath ulcerative colitis feature description set of the first disease condition level and the ath ulcerative colitis feature description set of the second disease condition level is generated based on a compressed attention mechanism, where a is a natural number greater than 1.
[0028] In one embodiment of the present application, among the disease condition levels corresponding to several original ulcerative colitis feature description sets, for adjacent first disease condition levels and second disease condition levels higher than the first disease condition levels, a mixed ulcerative colitis feature description set of the ath ulcerative colitis feature description set of the first disease condition level and the ath ulcerative colitis feature description set of the second disease condition level is generated based on a compressed attention mechanism, wherein d represents the number of levels of the disease condition level, and the larger the value of d is, the higher the number of levels of the disease condition level is; a is a natural number greater than 1, representing the number of ulcerative colitis feature description sets for each disease condition level.
[0029] Exemplarily, a mixed ulcerative colitis feature description set of a second ulcerative colitis feature description set at a first disease condition level and a second ulcerative colitis feature description set at a second disease condition level is generated based on a compressed attention mechanism.
[0030] In particular, for the ath ulcerative colitis feature description set of the first disease condition degree and the ath ulcerative colitis feature description set of the second disease condition degree, a mixed ulcerative colitis feature description set of the ath ulcerative colitis feature description set of the first disease condition degree and the ath ulcerative colitis feature description set of the second disease condition degree is generated based on the compressed attention mechanism, and the mixed ulcerative colitis feature description set and all ulcerative colitis feature description sets between the original ulcerative colitis feature description set of the first disease condition degree and the ath ulcerative colitis feature description set are spliced to obtain the a+1th ulcerative colitis feature description set of the first disease condition degree.
[0031] The ulcerative colitis feature description sets corresponding to each disease condition degree shown in this embodiment. In this embodiment, the original ulcerative colitis feature description set of the higher level of two adjacent disease condition degrees corresponds to the second ulcerative colitis feature description set of the lower level, and the subsequent ulcerative colitis feature description sets are pushed back in sequence, and the number of ulcerative colitis feature description sets of higher disease condition degrees is 1 less than the number of ulcerative colitis feature description sets of lower levels. And the original ulcerative colitis feature description sets corresponding to each disease condition degree, each original ulcerative colitis feature description set has its corresponding disease condition degree, thereby forming a multi-dimensional hierarchical structure of the ulcerative colitis feature description set.
[0032] Exemplarily, the first level of the disease condition level includes a ulcerative colitis feature description set, the second level of the disease condition level includes a ulcerative colitis feature description set, and so on. The fifth level of the disease condition level, i.e., the highest level of the disease condition level, includes a ulcerative colitis feature description set, i.e., the original ulcerative colitis feature description set corresponding to the fifth level of the disease condition level.
[0033] In one embodiment of the present application, for an adjacent first disease condition level and a second disease condition level higher than the first disease condition level, a process of generating a mixed ulcerative colitis feature description set of an ath ulcerative colitis feature description set of the first disease condition level and an ath ulcerative colitis feature description set of the second disease condition level based on a compressed attention mechanism specifically includes the following steps S810 to S820, which are described in detail as follows: In step S810, the ath ulcerative colitis feature description set of the first disease condition level is optimized based on the ath ulcerative colitis feature description set of the second disease condition level to obtain an optimized ulcerative colitis feature description set of the ath ulcerative colitis feature description set of the first disease condition level.
[0034] In one embodiment of the present application, in the process of obtaining a mixed ulcerative colitis feature description set based on the ulcerative colitis feature description set of the first disease condition degree and the second disease condition degree, the ath ulcerative colitis feature description set of the first disease condition degree is first optimized based on the ath ulcerative colitis feature description set of the second disease condition degree to obtain an optimized ulcerative colitis feature description set of the ath ulcerative colitis feature description set of the first disease condition degree. Based on the multi-dimensional hierarchical structure, high-level features, i.e., features of the second disease condition degree, more effectively guide low-level features for learning optimization.
[0035] Specifically, in the process of optimizing the ath ulcerative colitis feature description set of the first disease condition level based on the ath ulcerative colitis feature description set of the second disease condition level, steps S910 to S920 are included, which are described in detail as follows: In step S910, projection processing is performed on the ath ulcerative colitis feature description set of the second disease condition level to obtain a sample colitis feature projection result.
[0036] In addition to the method of obtaining the sample enteritis feature projection result in step S910, the ath ulcerative colitis feature description set of the second disease condition degree can also be projected and debugged, that is, the operator vector model is optimized by the debugging function to obtain the sample enteritis feature projection result.
[0037] In step S920, the features in the ath ulcerative colitis feature description set of the first disease condition level are optimized based on the sample enteritis feature projection result to obtain the optimized ulcerative colitis feature description set.
[0038] In step S820, the mixed ulcerative colitis feature description set is generated according to the optimized ulcerative colitis feature description set and the ath ulcerative colitis feature description set of the second disease condition degree.
[0039] After obtaining the optimized ulcerative colitis feature description set, the ath ulcerative colitis feature description set of the second disease condition level is convolved and compressed, and the obtained processing result is concatenated with the optimized ulcerative colitis feature description set to obtain a mixed ulcerative colitis feature description set.
[0040] In one embodiment of the present application, the process of generating the mixed ulcerative colitis feature description set according to the optimized ulcerative colitis feature description set and the ath ulcerative colitis feature description set of the second disease condition degree specifically includes the following steps S1110 to S1120, which are described in detail as follows: In step S1110, the ath ulcerative colitis feature description set of the second disease condition level is compressed to obtain a compressed feature, or the ath ulcerative colitis feature description set of the second disease condition level is compared to obtain a compressed feature, or the ath ulcerative colitis feature description set of the second disease condition level is compressed and compared to obtain the compressed feature.
[0041] In step S1120, the optimized ulcerative colitis feature description set and the compressed features are concatenated to obtain the mixed ulcerative colitis feature description set.
[0042] After obtaining the optimized ulcerative colitis feature description set corresponding to the a-th ulcerative colitis feature description set of the first disease condition level and the corresponding compressed features of the a-th ulcerative colitis feature description set of the second disease condition level, the optimized ulcerative colitis feature description set and the compressed features are spliced to obtain a mixed ulcerative colitis feature description set.
[0043] After obtaining the compressed features of the optimized ulcerative colitis feature description set, the feature attribute values corresponding to the optimized ulcerative colitis feature description set and the feature attribute values corresponding to the compressed features are added to obtain the feature attribute values corresponding to the mixed ulcerative colitis feature description set; based on the feature attribute values corresponding to the mixed ulcerative colitis feature description set, a mixed ulcerative colitis feature description set is generated.
[0044] In step S620, all ulcerative colitis feature description sets between the original ulcerative colitis feature description set of the first disease condition level and the a-th ulcerative colitis feature description set, as well as the mixed ulcerative colitis feature description set are spliced to obtain the a+1-th ulcerative colitis feature description set corresponding to the first disease condition level.
[0045] In one embodiment of the present application, after obtaining the ulcerative colitis feature description sets corresponding to each disease condition degree based on the above scheme, all ulcerative colitis feature description sets between the original ulcerative colitis feature description set of the first disease condition degree and the a-th ulcerative colitis feature description set, as well as the mixed ulcerative colitis feature description set, are spliced to obtain the a+1-th ulcerative colitis feature description set corresponding to the first disease condition degree. That is, in the ulcerative colitis feature description set of the same disease condition degree, an ulcerative colitis feature description set is obtained by splicing its corresponding mixed ulcerative colitis feature description set and all ulcerative colitis feature description sets prior to the ulcerative colitis feature description set.
[0046] In one embodiment of the present application, the process of concatenating all ulcerative colitis feature description sets between the original ulcerative colitis feature description set of the first disease condition level and the a-th ulcerative colitis feature description set, and the mixed ulcerative colitis feature description set to obtain the a+1-th ulcerative colitis feature description set corresponding to the first disease condition level specifically includes the following steps S6201 to S6202, which are described in detail as follows: In step S6201, all ulcerative colitis feature description sets between the original ulcerative colitis feature description set of the first disease condition level and the ath ulcerative colitis feature description set are optimized based on the data optimization thread to obtain an optimized ulcerative colitis feature description set.
[0047] In step S6202, the optimized ulcerative colitis feature description set and the mixed ulcerative colitis feature description set are convolutionally concatenated to obtain the a+1th ulcerative colitis feature description set corresponding to the first disease condition level.
[0048] In one embodiment of the present application, after obtaining the optimized ulcerative colitis feature description set, the optimized ulcerative colitis feature description set and the mixed ulcerative colitis feature description set are convolutionally concatenated to obtain the a+1th ulcerative colitis feature description set corresponding to the first disease condition degree.
[0049] In step S430, the original ulcerative colitis feature description set and the derived ulcerative colitis feature description set in the lowest disease condition level among all disease condition levels are spliced to obtain the ulcerative colitis feature description set of the ulcerative colitis test report data that needs to be processed.
[0050] In one embodiment of the present application, after compression processing based on the attention mechanism and splicing of the ulcerative colitis feature description set of the higher disease degree, a derived ulcerative colitis feature description set of the lowest disease degree is obtained. In the lowest disease degree, the original ulcerative colitis feature description set and the derived ulcerative colitis feature description set other than the original ulcerative colitis feature description set are included, wherein the number of the derived ulcerative colitis feature description set is at least one. By splicing the original ulcerative colitis feature description set and the derived ulcerative colitis feature description set in the lowest disease degree among all disease degrees, the ulcerative colitis feature description set of the ulcerative colitis test report data that needs to be processed is obtained.
[0051] Exemplarily, the ulcerative colitis feature description set of the ulcerative colitis test report data that needs to be processed is obtained by splicing the ulcerative colitis feature description set in the disease condition degree.
[0052] In step S440, the ulcerative colitis test report data to be processed is evaluated and processed according to the ulcerative colitis feature description set of the ulcerative colitis test report data to be processed.
[0053] The above scheme obtains several original ulcerative colitis feature description sets by performing multi-dimensional mining processing on the ulcerative colitis test report data that need to be processed, so that each original ulcerative colitis feature description set corresponds to a disease degree, and based on the original ulcerative colitis feature description sets of two adjacent disease degrees, generates a derived ulcerative colitis feature description set of the lower disease degree of the two disease degrees in sequence through a compressed attention mechanism, and finally concatenates the original ulcerative colitis feature description set and the derived ulcerative colitis feature description set of the lowest disease degree among the disease degrees to obtain the ulcerative colitis feature description set of the ulcerative colitis test report data that need to be processed, and evaluates the ulcerative colitis test report data that need to be processed according to the ulcerative colitis feature description set of the ulcerative colitis test report data that need to be processed. The technical solution of the embodiment of the present application compresses the feature description set of ulcerative colitis at each disease level based on the attention mechanism, and progressively aggregates the compression result with the feature description set of ulcerative colitis at the same disease level to obtain the spliced features, thereby more effectively extracting the important data of the ulcerative colitis test report data that needs to be processed, thereby improving the accuracy and precision of data evaluation.
[0054] Based on the above, a system for evaluating the severity of ulcerative colitis is shown, comprising a processor and a memory communicating with each other, wherein the processor is used to read a computer program from the memory and execute it to implement the above method.
[0055] Based on the above, a computer-readable storage medium is also provided, on which a computer program stored implements the above method when running.
[0056] In summary, based on the above scheme, the ulcerative colitis test report data that needs to be processed is subjected to multi-dimensional mining processing to obtain the original ulcerative colitis feature description set corresponding to each disease degree, and based on the original ulcerative colitis feature description set of two adjacent disease degrees, the compressed attention mechanism is used to generate the derived ulcerative colitis feature description set of the lower disease degree in the two disease degrees in turn, and finally the original ulcerative colitis feature description set and the derived ulcerative colitis feature description set of the lowest disease degree in the disease degree are concatenated to obtain the ulcerative colitis feature description set of the ulcerative colitis test report data that needs to be processed, so that it can be based on The compressed attention mechanism is used to process the ulcerative colitis feature description sets of two adjacent disease levels to obtain the ulcerative colitis feature description sets of each disease level, and then several ulcerative colitis feature description sets of the lowest disease level are spliced to obtain the ulcerative colitis feature description set of the ulcerative colitis test report data that needs to be processed. This processing method splices the features of several disease levels, and thus can more effectively extract the important data of the ulcerative colitis test report data that needs to be processed, ensuring that a more accurate ulcerative colitis feature description set of the ulcerative colitis test report data that needs to be processed is obtained, thereby improving the accuracy and precision of data evaluation.
[0057] It should be understood that the system and its modules shown above can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented by hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or a dedicated design hardware. Those skilled in the art will understand that the above methods and systems can be implemented using computer executable instructions and / or included in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules of the present application can not only be implemented by hardware circuits such as ultra-large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but can also be implemented by software such as executed by various types of processors, and can also be implemented by a combination of the above hardware circuits and software (e.g., firmware).
[0058] It should be noted that different embodiments may produce different beneficial effects. In different embodiments, the beneficial effects that may be produced may be any one or a combination of the above, or any other beneficial effects that may be obtained.
Claims
1. A method for assessing the severity of ulcerative colitis, characterized in that: include: Perform multi-dimensional mining on the ulcerative colitis test report data to be processed to obtain a number of original ulcerative colitis feature description sets, each of which corresponds to a disease severity level; For adjacent first disease condition levels and a second disease condition level higher than the first disease condition level, the ath ulcerative colitis feature description set of the first disease condition level is optimized based on the ath ulcerative colitis feature description set of the second disease condition level to obtain an optimized ulcerative colitis feature description set of the ath ulcerative colitis feature description set of the first disease condition level, and a mixed ulcerative colitis feature description set is generated based on the optimized ulcerative colitis feature description set and the ath ulcerative colitis feature description set of the second disease condition level, wherein a is a natural number greater than 1; Concatenate all ulcerative colitis feature description sets between the original ulcerative colitis feature description set of the first disease condition level and the a-th ulcerative colitis feature description set, as well as the mixed ulcerative colitis feature description set, to obtain the a+1-th ulcerative colitis feature description set corresponding to the first disease condition level; splicing the original ulcerative colitis feature description set and the derived ulcerative colitis feature description set in the lowest disease condition level among all disease condition levels to obtain the ulcerative colitis feature description set of the ulcerative colitis test report data that needs to be processed; The ulcerative colitis test report data that need to be processed are evaluated and processed according to the ulcerative colitis feature description set of the ulcerative colitis test report data that need to be processed.
2. The method according to claim 1, characterized in that Generating the mixed ulcerative colitis feature description set according to the optimized ulcerative colitis feature description set and the ath ulcerative colitis feature description set of the second disease condition degree includes: Compressing the ath ulcerative colitis feature description set of the second disease condition level to obtain a compressed feature, or performing a comparison process on the ath ulcerative colitis feature description set of the second disease condition level to obtain a compressed feature, or performing a compression and comparison process on the ath ulcerative colitis feature description set of the second disease condition level to obtain a compressed feature; The optimized ulcerative colitis feature description set and the compressed features are spliced to obtain the mixed ulcerative colitis feature description set.
3. The method according to claim 2, characterized in that The optimized ulcerative colitis feature description set and the compressed feature are spliced to obtain the mixed ulcerative colitis feature description set, including: Adding the feature attribute value corresponding to the optimized ulcerative colitis feature description set and the feature attribute value corresponding to the compressed feature to obtain the feature attribute value corresponding to the mixed ulcerative colitis feature description set; The mixed ulcerative colitis feature description set is generated according to the feature attribute values corresponding to the mixed ulcerative colitis feature description set.
4. The method according to claim 1, characterized in that: The ath ulcerative colitis feature description set of the first disease condition level is optimized based on the ath ulcerative colitis feature description set of the second disease condition level to obtain an optimized ulcerative colitis feature description set of the ath ulcerative colitis feature description set of the first disease condition level, including: Performing projection processing on the ath ulcerative colitis feature description set of the second disease condition degree to obtain a sample colitis feature projection result; Based on the sample enteritis feature projection result, the features in the ath ulcerative colitis feature description set of the first disease condition degree are optimized to obtain the optimized ulcerative colitis feature description set.
5. The method according to claim 4, characterized in that Based on the sample enteritis feature projection result, the features in the ath ulcerative colitis feature description set of the first disease condition degree are optimized to obtain the optimized ulcerative colitis feature description set, including: Multiplying the sample enteritis feature projection result by the feature attribute value contained in the ath ulcerative colitis feature description set of the first disease condition degree to obtain an optimized feature attribute value; The optimized ulcerative colitis feature description set is generated according to the optimized feature attribute values.
6. The method according to claim 4, characterized in that After the projection processing is performed on the ath ulcerative colitis feature description set of the second disease condition degree, the method further includes: The result of the projection processing is debugged to obtain the debugging result of the sample enteritis feature projection result.
7. The method according to claim 1, characterized in that All ulcerative colitis feature description sets between the original ulcerative colitis feature description set of the first disease condition level and the a-th ulcerative colitis feature description set, as well as the mixed ulcerative colitis feature description set, are concatenated to obtain the a+1-th ulcerative colitis feature description set corresponding to the first disease condition level, including: Optimizing all ulcerative colitis feature description sets between the original ulcerative colitis feature description set of the first disease condition degree and the ath ulcerative colitis feature description set based on the data optimization thread to obtain an optimized ulcerative colitis feature description set; The optimized ulcerative colitis feature description set and the mixed ulcerative colitis feature description set are convolutionally concatenated to obtain the a+1th ulcerative colitis feature description set corresponding to the first disease condition degree.
8. The method according to claim 1, characterized in that The ulcerative colitis test report data that needs to be processed is processed in multiple dimensions to obtain several original ulcerative colitis feature description sets, including: Preprocessing the ulcerative colitis test report data that needs to be processed to obtain a preprocessing result; Extracting target features corresponding to the preset analysis method in the preprocessing results; The target features are subjected to multi-dimensional mining processing to obtain a set of original ulcerative colitis feature descriptions corresponding to each degree of the disease condition.
9. The method according to any one of claims 1 to 8, characterized in that: The ulcerative colitis test report data to be processed includes medical images; evaluating and processing the ulcerative colitis test report data to be processed according to the ulcerative colitis feature description set of the ulcerative colitis test report data to be processed, including: According to the ulcerative colitis feature description set of the ulcerative colitis test report data to be processed and the target intestinal condition to be processed, the medical image is evaluated and processed to obtain analysis data of the target intestinal condition.
10. A system for assessing the severity of ulcerative colitis, characterized in that: The invention comprises a processor and a memory communicating with each other, wherein the processor is used to read a computer program from the memory and execute the computer program to implement the method according to any one of claims 1 to 9.