Multi-mode intelligent matching method for allergic rhinitis allergens

Abstract

The invention relates to the technical field of allergen analysis, in particular to an allergic rhinitis allergen multi-mode intelligent matching method. The seasonal sensitivity is obtained according to the seasonal distribution of the allergy cycles corresponding to the example allergens and the anaphylaxis disease similarity degree of every two allergy cycles corresponding to the example allergens; marking the allergy cycle with at least two contact allergens as a target cycle, and obtaining the contact sensitivity according to the number of target cycles with example allergens in the contact allergens in the target cycle and the number of target cycles with actual allergens as the example allergens; obtaining concurrent sensitivity according to a complication occurrence condition and a complication severity condition in an allergy cycle corresponding to the example allergen; and determining an allergen matching result of the patient by combining the three sensitivities. According to the method, the allergen characteristics are quantified in combination with three dimensions of seasonal concentration, contact correlation and complication existence, and the allergen matching accuracy is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of allergen analysis technology, specifically to a multimodal intelligent matching method for allergens in allergic rhinitis. Background Technology

[0002] Allergic rhinitis is a common immune system disorder, mainly caused by airborne allergens such as dust mites, pollen, mold, and animal dander. With the influence of environmental pollution and climate change, the incidence of allergic rhinitis is rising year by year, becoming a global public health issue. Clinical manifestations of allergic rhinitis typically include nasal congestion, sneezing, runny nose, and itchy eyes. In severe cases, it can affect a patient's quality of life and work efficiency.

[0003] The prior art patent document with publication number CN117688454B discloses an auxiliary method and system for allergen analysis. Specifically, it acquires symptom information and detection data of multiple possible allergens, determines the matching degree data of each possible allergen based on the symptom information, and classifies and processes the possible allergens based on the matching degree data. However, patients with allergic rhinitis may have the same symptom reaction to different allergens, leading to misidentification of allergens and thus lower accuracy of allergen detection for allergic rhinitis. Summary of the Invention

[0004] To address the technical problem of misidentification of allergens due to patients with allergic rhinitis experiencing the same symptom response to different allergens, this invention aims to provide a multimodal intelligent matching method for allergens in allergic rhinitis. The specific technical solution adopted is as follows: This invention proposes a multimodal intelligent matching method for allergens in allergic rhinitis, the method comprising: Obtain the actual allergens and contact allergens of allergic rhinitis patients for each allergy cycle during the historical analysis period; select one actual allergen and record it as the example allergen; The seasonal sensitivity of the example allergen is obtained by comparing the seasonal distribution of the allergy cycle corresponding to the example allergen with the similarity of allergic symptoms in each pair of allergy cycles corresponding to the example allergen. The allergy cycle with at least two exposures to the allergen is defined as the target cycle. The exposure sensitivity of the example allergen is obtained based on the number of target cycles in which the allergen is an example allergen and the number of target cycles in which the actual allergen is an example allergen. Based on the occurrence and severity of complications during the allergic cycle corresponding to the example allergen, the concurrent susceptibility of the example allergen is obtained; By combining the seasonal sensitivity, the contact sensitivity, and the concurrent sensitivity, the allergen matching results for the patient are obtained.

[0005] Furthermore, obtaining the seasonal sensitivity of the example allergen includes: Obtain symptom data for each allergy cycle of patients with allergic rhinitis within the historical analysis period; obtain the severity of allergic symptoms based on the symptom data of allergy cycles; and record the sum of the differences in the severity of allergic symptoms between all pairs of allergy cycles corresponding to the example allergen as the symptom difference degree. Obtain the peak incidence period for each actual allergen; sum the overlap time between each allergy cycle corresponding to the example allergen and the peak incidence period, and record it as the seasonal overlap degree; Based on the seasonal overlap and the difference in symptoms, the seasonal sensitivity of the example allergen is obtained.

[0006] Furthermore, obtaining the contact sensitivity of the example allergen includes: The ratio of the number of target cycles containing example allergens to the total number of target cycles is denoted as the disease participation rate. The percentage of actual allergens and example allergens in the target period is denoted as the disease concordance rate. Based on the disease participation rate and the disease conformity rate, the exposure sensitivity to the example allergen is obtained.

[0007] Furthermore, the acquisition of concurrent susceptibility to the example allergen includes: Obtain physiological data for each allergy cycle in patients with allergic rhinitis during the historical analysis period; based on the physiological data of the allergy cycles, obtain the severity of complications; The cycle in which complications occurred is selected from the allergy cycle and recorded as the concurrent cycle; the proportion of concurrent cycles in the allergy cycle is recorded as the concurrent occurrence rate; the average of the concurrent severity rates of all concurrent cycles corresponding to the example allergen is used as the overall severity. The concurrent susceptibility of the example allergen is obtained based on the concurrent occurrence and the overall severity.

[0008] Further, obtaining the allergen matching results for the patient includes: The seasonal sensitivity, the contact sensitivity, and the concurrent sensitivity are denoted as the example sensitivity. Based on the example sensitivity of the same type of all actual allergens, the example sensitivity of the corresponding type of example allergen is normalized to obtain the sensitivity weight of each type of example sensitivity of the example allergen. The sum of the sensitivity weights of all types of example allergens is used as the matching priority of the example allergen; All actual allergens of the patient during the historical analysis period are arranged in descending order of matching priority to obtain the allergen matching sequence.

[0009] Furthermore, the acquisition of the severity of allergic symptoms includes: Symptom data include: duration of nasal congestion and frequency of sneezing; The product of the duration of nasal congestion during an allergy cycle and the frequency of sneezing is used as the severity of allergy symptoms during the allergy cycle.

[0010] Furthermore, the acquisition of concurrency severity includes: Physiological data include: C-reactive protein concentration and inflammation score; The severity of the complication was determined by multiplying the difference between the C-reactive protein concentration and the preset standard C-reactive protein concentration by the inflammation score.

[0011] Further, obtaining the seasonal sensitivity of the example allergen based on the seasonal overlap and the symptom difference includes: The seasonal sensitivity of the example allergen is obtained by performing a negative correlation mapping on the symptom difference, and normalizing the product of the mapping result and the seasonal overlap.

[0012] Furthermore, the inflammation score is obtained using a semi-quantitative visual scoring technique.

[0013] Furthermore, the duration of the historical analysis period is one year.

[0014] The present invention has the following beneficial effects: In this embodiment of the invention, allergic reactions to allergens exhibit seasonal concentration, and allergens with strong seasonal characteristics show similar symptoms during peak periods. By combining the seasonal distribution of example allergens corresponding to allergy cycles with the similarity of allergic symptoms in different allergy cycles, the seasonality of the example allergens is analyzed to determine the sensitivity of the example allergens to seasonal concentration, i.e., seasonal sensitivity. The number of target cycles in which the example allergen is present and the number of target cycles in which the actual allergen is the example allergen are presented, respectively, show the frequency of contact between the example allergen and the patient, and the likelihood of sensitization. This can present the contact-related characteristic strength of the example allergens, and determine the sensitivity of the example allergens to contact-related factors, i.e., contact sensitivity. Touch sensitivity; Allergic rhinitis may lead to complications. The occurrence and severity of complications during the allergic cycle corresponding to the example allergen reflect the pathogenicity of the example allergen. By analyzing the intensity of the complication characteristics of the example allergen, the sensitivity of the example allergen to the presence of complications is determined, i.e., the complication sensitivity. This solution quantifies allergen characteristics through three dimensions: seasonal concentration, contact relevance, and complication presence. It uses these three dimensions to comprehensively analyze the patient's sensitivity to different allergens and perform allergen matching, effectively solving the problem of misidentification of allergens caused by patients having the same symptom reaction to different allergens, improving the accuracy of allergen matching, and assisting doctors in quickly identifying the core allergen. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 The flowchart illustrates the steps of a multimodal intelligent matching method for allergens in allergic rhinitis, as provided in one embodiment of the present invention. Figure 2 A flowchart illustrating a method for obtaining seasonal sensitivity according to an embodiment of the present invention; Figure 3 This is a system structure diagram of a multimodal intelligent matching system for allergens in allergic rhinitis, provided in one embodiment of the present invention. Figure 4 This is a schematic diagram of a computer device for a multimodal intelligent matching device for allergens in allergic rhinitis, provided as an embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a multimodal intelligent matching method for allergens in allergic rhinitis proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The following description, in conjunction with the accompanying drawings, details the specific scheme of the multimodal intelligent matching method for allergens in allergic rhinitis provided by this invention.

[0020] Example 1: This invention proposes a multimodal intelligent matching method for allergens in allergic rhinitis. Please refer to [link / reference]. Figure 1 The diagram illustrates a flowchart of a multimodal intelligent matching method for allergens in allergic rhinitis, provided by an embodiment of the present invention. The method includes: Step S1: Obtain the actual allergens and contact allergens of allergic rhinitis patients for each allergy cycle during the historical analysis period; select one actual allergen and record it as the example allergen.

[0021] The occurrence of allergic rhinitis is mainly related to individual exposure to allergens. Different allergens have different effects on the patient's immune response, and allergens also vary significantly across different regions, seasons, and individuals. To more comprehensively analyze allergens, this embodiment of the invention records the past year as the historical analysis period for allergic rhinitis patients. The symptom log of allergy history for allergic rhinitis patients during the historical analysis period is obtained, specifically including: Disease log data: onset date, recovery date. The time period between the onset date and recovery date of the same allergic disease is recorded as an allergy cycle. The allergen that causes the patient's allergic disease is the actual allergen. Allergens that the patient was exposed to within one day before the onset date of the corresponding allergy cycle are contact allergens.

[0022] Allergens causing allergic rhinitis mainly include dust mites, pollen, mold spores, biological secretions, chemical irritants, and certain foods. Different types of allergens cause different characteristics in allergic reactions. For example, pollen allergies have seasonal outbreaks, dust mite allergies have rapid onset of symptoms, and certain food allergies can easily lead to gastrointestinal or respiratory complications. This protocol subsequently determines three dimensions based on the differences in symptom characteristics of different allergens: seasonal concentration of onset, allergen exposure correlation, and the presence of complications. These three dimensions are then used for allergen matching, effectively improving the accuracy of allergen matching.

[0023] Step S2: Based on the seasonal distribution of the allergy cycle corresponding to the example allergen and the similarity of allergic symptoms between pairs of allergy cycles corresponding to the example allergen, obtain the seasonal sensitivity of the example allergen.

[0024] Allergic reactions to certain allergens exhibit seasonal concentrations. For example, pollen allergies are concentrated in spring and autumn, while dust mite allergies are concentrated in summer and autumn. Furthermore, allergens with strong seasonal characteristics often present similar symptoms during their peak seasons. Therefore, by combining the seasonal distribution of the allergy cycle corresponding to the example allergen with the similarity of allergic symptoms between pairs of allergy cycles corresponding to the example allergen, the seasonality of the example allergen can be analyzed to determine its sensitivity to seasonal concentrations and thus obtain seasonal sensitivity.

[0025] It should be noted that the actual allergen corresponding to the allergy cycle in the example allergen is the example allergen.

[0026] Step S3: Record the allergy cycle with at least two exposures to allergens as the target cycle. Based on the number of target cycles in which the exposure to allergens includes example allergens and the number of target cycles in which the actual allergen is an example allergen, obtain the exposure sensitivity of the example allergen.

[0027] Allergic rhinitis generally requires exposure to a specific allergen. However, patients may be exposed to multiple allergens at certain times, leading to overlapping allergic symptoms caused by different allergens. To analyze the contact-related characteristics of allergens, allergy cycles involving multiple allergen exposures are selected as target cycles. The number of target cycles in which the example allergen is present, and the number of target cycles in which the actual allergen is the example allergen, respectively, represent the frequency of patient exposure to the example allergen and the likelihood of sensitization. By combining these factors, the strength of the contact-related characteristics of the example allergen is analyzed. Contact sensitivity is obtained by assessing the sensitivity of the example allergen to this contact-related characteristic.

[0028] Step S4: Obtain the concurrent susceptibility of the example allergen based on the occurrence and severity of complications during the allergy cycle corresponding to the example allergen.

[0029] Allergic rhinitis is a local reaction, but if not treated promptly and effectively, it can lead to a series of complications, such as otitis media and allergic conjunctivitis. The occurrence and severity of complications corresponding to example allergens during the allergic cycle reflect the pathological invasiveness and immune response intensity triggered by the example allergen. Both reflect the pathogenicity of the example allergen. By analyzing the intensity of the complication characteristics of the example allergen, the sensitivity of the example allergen to the presence of complications can be determined, resulting in complication sensitivity.

[0030] Step S5: Combine seasonal sensitivity, contact sensitivity, and concurrent sensitivity to obtain the patient's allergen matching results.

[0031] This approach quantifies allergen characteristics through three dimensions: seasonal concentration, contact relevance, and presence of complications. By comprehensively analyzing multiple data sources, it determines the allergen matching results for patients with allergic rhinitis, assisting doctors in quickly identifying the core allergens and providing personalized treatment strategies. This provides a scientific basis for improving patients' treatment outcomes and quality of life.

[0032] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining seasonal sensitivity is described in [reference needed]. Figure 2 The diagram illustrates a flowchart of a method for obtaining seasonal sensitivity according to an embodiment of the present invention, the method comprising: Step S210: Obtain symptom data for each allergy cycle of allergic rhinitis patients within the historical analysis period; based on the symptom data of the allergy cycle, obtain the severity of allergic symptoms; the sum of the differences in the severity of allergic symptoms between all pairs of allergy cycles corresponding to the example allergen is recorded as the symptom difference degree. Here, the difference value refers to the absolute value of the difference.

[0033] The symptom data of allergic rhinitis patients for each allergy cycle is obtained from their allergy history logs during the historical analysis period. In this embodiment of the invention, the symptom data includes: the duration of nasal congestion and the frequency of sneezing in each allergy cycle. The product of the proportion of nasal congestion duration in the allergy cycle and the sneezing frequency is used as the severity of the allergy symptoms in the allergy cycle. It should be noted that the more frequently a patient sneezes and the longer the duration of nasal congestion during an allergy cycle, the more severe the allergy symptoms to the example allergen are during the allergy cycle. Therefore, both the duration of nasal congestion and the frequency of sneezing are positively correlated with the severity of allergy symptoms.

[0034] It should be noted that allergens with strong seasonal characteristics have similar symptoms during their peak season. The smaller the difference in symptoms, the more similar the symptoms are between pairs of allergy cycles corresponding to the example allergen. In this case, the seasonal characteristics of the example allergen are stronger and the seasonal sensitivity is greater.

[0035] Step S220: Obtain the peak time period for each actual allergen; sum the overlap time of all allergy cycles corresponding to the example allergen with the peak time period, and record it as the seasonal overlap degree.

[0036] It should be noted that the greater the seasonal overlap, the more synchronized the patient's exposure time to the sample allergen with its peak incidence period. This indicates that the seasonality of the sample allergen's prevalence is more consistent with the timing of the patient's allergy symptoms, thus the stronger the seasonality of the sample allergen and the greater its seasonal sensitivity. Conversely, if the seasonal overlap is less pronounced, it suggests that the patient's exposure time to the sample allergen is unrelated to its peak incidence period and may be accidental, indicating a weaker seasonality of the sample allergen. Because allergen-related illnesses exhibit seasonal patterns, the historical analysis period was divided into different seasonal periods.

[0037] In this embodiment of the invention, the method for obtaining the peak period of the actual allergen is as follows: obtain the allergy cycles of a large number of patients in the historical analysis period, count the total number of allergy cycles caused by each actual allergen in each seasonal period as the cycle occurrence value, and record the seasonal period corresponding to the two largest cycle occurrence values ​​as the peak period of the actual allergen.

[0038] In other embodiments of the present invention, for each actual allergen corresponding to an allergy cycle, the severity of allergic symptoms in each allergy cycle existing in each seasonal period is averaged and recorded as the overall severity of symptoms in each seasonal period. The seasonal period corresponding to the highest overall severity of symptoms is selected from all seasonal periods and recorded as the high incidence period of each actual allergen.

[0039] Step S230: Obtain the seasonal sensitivity of the example allergen based on the seasonal overlap and the difference in symptoms.

[0040] It should be noted that the greater the seasonal overlap and the smaller the symptom variability, the stronger the seasonality of the example allergen, and thus the greater the seasonal sensitivity. Therefore, seasonal overlap is positively correlated with seasonal sensitivity, while symptom variability is negatively correlated with seasonal sensitivity. In this embodiment of the invention, a negative correlation mapping is performed on the symptom variability, and the product of the mapping result and the seasonal overlap is normalized to obtain the seasonal sensitivity of the example allergen.

[0041] In this embodiment of the invention, the symptom difference is used as the exponent of an exponential function with the natural constant as the base, so as to realize the negative correlation mapping of the symptom difference. The Sigmoid function is used for normalization. Alternatively, negative correlation mapping methods such as taking the reciprocal, function transformation, and normalization methods such as maximum and minimum normalization can be selected. No limitation is made here.

[0042] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining contact sensitivity includes: recording the ratio of the number of target cycles in which the sample allergen is present to the total number of target cycles as the disease participation degree; recording the cycle proportion of the actual allergen and the sample allergen in the target cycle as the disease conformity degree; and obtaining the contact sensitivity of the sample allergen based on the disease participation degree and the disease conformity degree.

[0043] It should be noted that a higher disease involvement rate indicates a high degree of synchronization between the patient's allergic symptoms and exposure to the example allergen, thus indicating a stronger contact correlation between the example allergen and the allergy, and a higher contact sensitivity. Conversely, a higher disease concordance rate indicates a higher proportion of patients' allergic symptoms are diagnosed as being caused by the example allergen, indicating a higher sensitivity to the example allergen. When both disease involvement rate and disease concordance rate are high, the example allergen not only frequently contacts the patient but is also repeatedly identified as the actual trigger, resulting in a stronger contact correlation between the example allergen and the allergy, and a higher contact sensitivity. Therefore, both disease involvement rate and disease concordance rate are positively correlated with contact sensitivity. In this embodiment of the invention, the product of the disease involvement rate and disease concordance rate of the example allergen is normalized to obtain the contact sensitivity of the example allergen.

[0044] In this embodiment of the invention, the Sigmoid function is used for normalization. However, other normalization methods such as function transformation or max-min normalization can also be used, and no limitation is made here.

[0045] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining concurrency sensitivity includes: obtaining concurrency severity based on physiological data of allergy cycles; selecting cycles in which complications occur from the allergy cycles and recording them as concurrency cycles; recording the proportion of concurrency cycles in the allergy cycles as concurrency occurrence; taking the average concurrency severity of all concurrency cycles corresponding to the example allergen as the overall severity; and obtaining the concurrency sensitivity of the example allergen based on the concurrency occurrence and the overall severity. Specifically, whether complications occur in each allergy cycle is determined from the allergy history logs of allergy patients during the historical analysis period.

[0046] Since complications caused by allergens are generally inflammatory reactions, such as sinusitis, otitis media, and allergic conjunctivitis, C-reactive protein (CRP) is commonly used to monitor inflammatory responses in the body. Therefore, physiological data for each allergic cycle is obtained from the allergy history logs of allergy patients during the historical analysis period. In this embodiment of the invention, the physiological data includes: the CRP concentration and inflammation score of the patient in each allergic cycle. The inflammation score refers to the score obtained after a CT scan of the inflamed area, typically using semi-quantitative visual scoring techniques.

[0047] In this embodiment of the invention, the product of the difference between the C-reactive protein concentration and a preset standard C-reactive protein concentration and the inflammation score is used as the severity of the complication. It should be noted that the larger the difference between the C-reactive protein concentration and the preset standard C-reactive protein concentration, the more severe the inflammatory response in the patient's body. Simultaneously, a higher inflammation score indicates more severe complications during the allergic cycle, thus indicating a greater severity of the complication. It should be noted that the preset standard C-reactive protein concentration is the maximum value of the normal range for C-reactive protein in the patient's population. In this embodiment, the population is divided into pregnant women and non-pregnant women. If the patient is a non-pregnant woman (adult or child), the preset standard C-reactive protein concentration is 3 mg / L; if the patient is a pregnant woman, the preset standard C-reactive protein concentration is 20 mg / L.

[0048] In other embodiments, physiological data may also include respiratory rate, with a higher respiratory rate per respiratory cycle associated with more severe complications.

[0049] It should be noted that the overall severity reflects the overall severity level of complications across all cycles corresponding to the example allergen. A higher incidence of complications and a higher overall severity indicate that the example allergen is more likely to trigger complications during an allergic reaction. Furthermore, the more severe the clinical manifestations of complications during an allergic reaction, the stronger the likelihood of complications arising from the example allergen, and the greater the complication sensitivity. Therefore, both the incidence of complications and the overall severity are positively correlated with complication sensitivity. In this embodiment of the invention, the product of the incidence of complications and the overall severity of the example allergen is normalized to obtain the complication sensitivity.

[0050] In this embodiment of the invention, the Sigmoid function is used for normalization. However, other normalization methods such as function transformation or max-min normalization can also be used, and no limitation is made here.

[0051] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the allergen matching sequence includes: denoting seasonal sensitivity, contact sensitivity, and concurrent sensitivity as example sensitivity; normalizing the example sensitivity of the corresponding type of example allergen based on the example sensitivity of the same type of all actual allergens to obtain the sensitivity weight of each type of example sensitivity of the example allergen; using the sum of the sensitivity weights of all types of example sensitivity of the example allergen as the matching priority of the example allergen; and arranging all actual allergens of the patient in the historical analysis period from largest to smallest according to the matching priority to obtain the allergen matching sequence.

[0052] In one specific implementation of this invention, the matching priority is expressed by the formula: In the formula, The x-th actual allergen matching priority for the patient within the historical analysis period; K is the number of sample sensitivities for the actual allergen. Since the sample sensitivities include seasonal sensitivities, contact sensitivities, and concurrent sensitivities, K is equal to 3 in this embodiment. The sensitivity of the patient to the kth type of the xth actual allergen during the historical analysis period is given; N is the total number of actual allergens encountered by the patient during the historical analysis period. This represents the patient's sensitivity to the kth type of the nth actual allergen within the historical analysis period. The sensitivity weight is assigned to the sample sensitivity of the xth actual allergen and the kth type within the historical analysis period.

[0053] It is important to note that the seasonal sensitivity, contact sensitivity, and concurrent sensitivity of all actual allergens for patients during the historical analysis period were obtained using the same methods as those for the example allergens.

[0054] It should be noted that since actual allergens with higher matching priority are more likely to trigger allergic reactions in patients, all actual allergens in the patient's historical analysis period are sorted from highest to lowest matching priority to obtain an allergen matching sequence. The smaller the subscript of the actual allergen in the allergen matching sequence, the greater the likelihood that it will trigger allergic rhinitis in the patient again, and the higher the matching degree.

[0055] If a patient subsequently develops allergic rhinitis, medical personnel can perform skin prick tests from front to back based on allergen-matching sequences. This minimizes the cost of allergen detection and improves efficiency and timeliness. Furthermore, measuring the level of immunoglobulin E antibodies against specific allergens in the blood can identify the actual allergen, allowing for personalized treatment strategies.

[0056] This solution quantifies allergen characteristics through three dimensions: seasonal concentration of disease incidence, correlation with allergen exposure, and presence of complications. Finally, it prioritizes these characteristics based on matching criteria to help doctors quickly identify the core allergens.

[0057] This invention is now complete.

[0058] Example 2: This invention proposes a multimodal intelligent matching system for allergens in allergic rhinitis. Please refer to [link / reference]. Figure 3 The diagram illustrates a system structure of an intelligent multimodal matching system for allergens in allergic rhinitis, provided by an embodiment of the present invention. The system includes: The data acquisition module 610 is used to acquire the actual allergens and contact allergens of allergic rhinitis patients during each allergy cycle in the historical analysis period; one actual allergen is selected and recorded as the example allergen; The seasonal sensitivity analysis module 620 is used to obtain the seasonal sensitivity of a sample allergen based on the seasonal distribution of the allergy cycle corresponding to the sample allergen and the similarity of allergic symptoms between pairs of allergy cycles corresponding to the sample allergen. The contact sensitivity analysis module 630 is used to record allergy cycles with at least two contact allergens as target cycles, and to obtain the contact sensitivity of the example allergens based on the number of target cycles in which the contact allergens contain example allergens and the number of target cycles in which the actual allergens are example allergens. The concurrent sensitivity analysis module 640 is used to obtain the concurrent sensitivity of the example allergen based on the occurrence and severity of complications during the allergy cycle corresponding to the example allergen. The allergen matching module 650 is used to combine seasonal sensitivity, contact sensitivity, and concurrent sensitivity to obtain the patient's allergen matching results.

[0059] It should be noted that the devices provided in the above embodiments are only illustrative examples of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device can be divided into different functional modules to complete all or part of the functions described above. Furthermore, the allergic rhinitis allergen multimodal intelligent matching system and the allergic rhinitis allergen multimodal intelligent matching method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process is detailed in the method embodiments, and will not be repeated here.

[0060] Example 3: Figure 4 This is a schematic diagram of a computer device for a multimodal intelligent matching device for allergens in allergic rhinitis, provided as an embodiment of the present invention. For example,... Figure 4 As shown, the computer device includes: a memory 701, a processor 702, and a computer program 703 stored in the memory 701 and running on the processor 702, wherein when the processor 702 executes the computer program 703, the computer device can execute any of the aforementioned allergic rhinitis allergen multimodal intelligent matching methods.

[0061] Furthermore, embodiments of this application also protect an apparatus that may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to execute the multimodal intelligent matching method for allergens in allergic rhinitis provided in embodiments of this application.

[0062] This embodiment can divide the device into functional modules based on the above method example. For example, each module can correspond to a separate function, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0063] It should be understood that the device provided in this embodiment is used to execute the above-described intelligent multimodal matching method for allergic rhinitis allergens, and therefore can achieve the same effect as the above-described implementation method.

[0064] When using integrated units, the device may include a processing module and a storage module. When applied to a workpiece, the processing module can be used to control and manage the workpiece's operations. The storage module can be used to support the execution of program code by the workpiece.

[0065] The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits contained in conjunction with the disclosure of this application. The processor may also be a combination of functions that implement computing capabilities, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and microprocessors, etc., and the storage module may be a memory.

[0066] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0067] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0068] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A multimodal intelligent matching method for allergens in allergic rhinitis, characterized in that, The method includes: Obtain the actual allergens and contact allergens of allergic rhinitis patients for each allergy cycle during the historical analysis period; select one actual allergen and record it as the example allergen; The seasonal sensitivity of the example allergen is obtained by comparing the seasonal distribution of the allergy cycle corresponding to the example allergen with the similarity of allergic symptoms in each pair of allergy cycles corresponding to the example allergen. The allergy cycle with at least two exposures to the allergen is defined as the target cycle. The exposure sensitivity of the example allergen is obtained based on the number of target cycles in which the allergen is an example allergen and the number of target cycles in which the actual allergen is an example allergen. Based on the occurrence and severity of complications during the allergic cycle corresponding to the example allergen, the concurrent susceptibility of the example allergen is obtained; By combining the seasonal sensitivity, the contact sensitivity, and the concurrent sensitivity, the allergen matching results for the patient are obtained.

2. The method for multimodal intelligent matching of allergens in allergic rhinitis according to claim 1, characterized in that, The acquisition of seasonal sensitivity to example allergens includes: Obtain symptom data for each allergy cycle of patients with allergic rhinitis within the historical analysis period; obtain the severity of allergic symptoms based on the symptom data of allergy cycles; and record the sum of the differences in the severity of allergic symptoms between all pairs of allergy cycles corresponding to the example allergen as the symptom difference degree. Obtain the peak incidence period for each actual allergen; sum the overlap time between each allergy cycle corresponding to the example allergen and the peak incidence period, and record it as the seasonal overlap degree; Based on the seasonal overlap and the difference in symptoms, the seasonal sensitivity of the example allergen is obtained.

3. The method for multimodal intelligent matching of allergens in allergic rhinitis according to claim 1, characterized in that, The acquisition of contact sensitivity to example allergens includes: The ratio of the number of target cycles containing example allergens to the total number of target cycles is denoted as the disease participation rate. The percentage of actual allergens and example allergens in the target period is denoted as the disease concordance rate. Based on the disease participation rate and the disease conformity rate, the exposure sensitivity to the example allergen is obtained.

4. The method for multimodal intelligent matching of allergens in allergic rhinitis according to claim 1, characterized in that, The acquisition of concurrent susceptibility to the example allergen includes: Obtain physiological data for each allergy cycle in patients with allergic rhinitis during the historical analysis period; based on the physiological data of the allergy cycles, obtain the severity of complications; The cycle in which complications occurred is selected from the allergy cycle and recorded as the concurrent cycle; the proportion of concurrent cycles in the allergy cycle is recorded as the concurrent occurrence rate; the average of the concurrent severity rates of all concurrent cycles corresponding to the example allergen is used as the overall severity. The concurrent susceptibility of the example allergen is obtained based on the concurrent occurrence and the overall severity.

5. The intelligent multimodal matching method for allergens in allergic rhinitis according to claim 1, characterized in that, The process of obtaining the allergen matching results for the patient includes: The seasonal sensitivity, the contact sensitivity, and the concurrent sensitivity are denoted as the example sensitivity. Based on the example sensitivity of the same type of all actual allergens, the example sensitivity of the corresponding type of example allergen is normalized to obtain the sensitivity weight of each type of example sensitivity of the example allergen. The sum of the sensitivity weights of all types of example allergens is used as the matching priority of the example allergen; All actual allergens of the patient during the historical analysis period are arranged in descending order of matching priority to obtain the allergen matching sequence.

6. The method for multimodal intelligent matching of allergens in allergic rhinitis according to claim 2, characterized in that, The acquisition of the severity of allergic symptoms includes: Symptom data include: duration of nasal congestion and frequency of sneezing; The product of the duration of nasal congestion during an allergy cycle and the frequency of sneezing is used as the severity of allergy symptoms during the allergy cycle.

7. The intelligent multimodal matching method for allergens in allergic rhinitis according to claim 4, characterized in that, The acquisition of concurrency severity includes: Physiological data include: C-reactive protein concentration and inflammation score; The severity of the complication was determined by multiplying the difference between the C-reactive protein concentration and the preset standard C-reactive protein concentration by the inflammation score.

8. The method for multimodal intelligent matching of allergens in allergic rhinitis according to claim 2, characterized in that, The step of obtaining the seasonal sensitivity of an example allergen based on the seasonal overlap and the difference in symptoms includes: The seasonal sensitivity of the example allergen is obtained by performing a negative correlation mapping on the symptom difference, and normalizing the product of the mapping result and the seasonal overlap.

9. The multimodal intelligent matching method for allergens in allergic rhinitis according to claim 7, characterized in that, The inflammation score is obtained using a semi-quantitative visual scoring technique.

10. The method for multimodal intelligent matching of allergens in allergic rhinitis according to claim 1, characterized in that, The historical analysis period is one year in length.

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