Prenatal oral health examination management system and method

Abstract

The present application relates to the technical field of oral health, and particularly relates to a pregnant woman oral health examination management system and method, the system comprising: a gestational week physiological characteristic analysis module for constructing a corresponding oral sensitivity characteristic vector of each gestational week; a morning sickness characteristic analysis module for constructing a gastric acid erosion risk characteristic vector; a tooth characteristic analysis module for constructing a tooth acid resistance characteristic vector; an erosion risk assessment module for coupling analysis of the gastric acid erosion risk characteristic vector and the tooth acid resistance characteristic vector, and evaluating the tooth surface acid erosion risk caused by vomiting; and an oral health risk assessment module for joint modeling based on the oral sensitivity characteristic vector and the tooth surface acid erosion risk evaluation result, and generating a pregnant woman individualized oral health risk assessment result. The present application quantifies the gastric acid erosion risk characteristic caused by morning sickness, the tooth acid resistance characteristic, and the gestational week oral sensitivity characteristic, and effectively improves the prediction accuracy and reliability of the oral health risk during pregnancy.

Description

Technical Field

[0001] This invention relates to the field of oral health technology, and more particularly to an oral health examination management system and method for pregnant women. Background Technology

[0002] Current methods for managing oral health during pregnancy largely rely on routine dental checkups, typically focusing only on common oral problems such as gingivitis and cavities. They lack systematic and individualized assessment methods to address the unique physiological changes and oral health risk factors associated with pregnancy. Furthermore, routine dental checkups often fail to adequately consider the impact of gestational changes on oral sensitivity and fail to couple the frequency of morning sickness, the physicochemical properties of vomit acid, and the structural characteristics of the pregnant woman's teeth. Therefore, current technologies struggle to accurately quantify the evolving trends of oral health risks at different stages of pregnancy and cannot provide early warnings of oral health risks in pregnant women under the coupled influence of gestational oral sensitivity and acid erosion risk. Summary of the Invention

[0003] To overcome the defects and shortcomings of existing technologies, this invention provides an oral health examination management system and method for pregnant women. By quantifying the risk characteristics of gastric acid erosion caused by morning sickness, the acid resistance characteristics of teeth, and the oral sensitivity characteristics caused by physiological changes during pregnancy, the system effectively improves the accuracy and reliability of predicting oral health risks during pregnancy.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides an oral health examination and management system for pregnant women, including a gestational age physiological characteristic analysis module, a morning sickness characteristic analysis module, a tooth characteristic analysis module, an erosion risk assessment module, and an oral health risk assessment module. Among them, the gestational week physiological characteristic analysis module is used to obtain progesterone level data, immune response data and saliva composition data of pregnant women at each gestational week, and construct oral sensitivity feature vectors corresponding to each gestational week. The morning sickness feature analysis module is used to obtain the frequency of morning sickness, the time of occurrence of morning sickness, the duration of morning sickness, the pH value of vomit acid, and to construct a feature vector of gastric acid erosion risk. The tooth feature analysis module is used to obtain tooth feature data of pregnant women, including enamel thickness, microcrack morphology, degree of tooth surface mineralization, distribution of tooth sensitivity areas, demineralization trend of tooth surface, dentition morphology and tooth surface exposure, and to construct a tooth acid resistance feature vector. The erosion risk assessment module is used to couple and analyze the gastric acid erosion risk feature vector with the tooth acid resistance feature vector, and assess the risk of tooth surface acid erosion caused by vomiting based on the exposure degree and local mineralization degree of different tooth surface areas. The oral health risk assessment module is used to jointly model based on oral sensitivity feature vectors and tooth surface acid erosion risk assessment results to generate personalized oral health risk assessment results for pregnant women.

[0005] Furthermore, the specific execution steps of the gestational age physiological characteristic analysis module include: Based on progesterone level data, progesterone fluctuation trend analysis was performed, and the rate of change of peak progesterone was used as the progesterone perturbation parameter for each gestation week. Based on immune response data, parameters of local oral immunosuppression were extracted, including parameters of decreased immune cell activity, parameters of susceptibility to inflammation, and parameters of decreased oral barrier function. Based on saliva composition data, salivary buffering characteristic parameters were extracted, including saliva buffering capacity parameters, mineral concentration parameters, saliva viscosity parameters, and saliva secretion cycle parameters. The parameters of progesterone perturbation, oral local immunosuppression, and salivary buffering were normalized, and an oral sensitivity feature vector was constructed to reflect changes in oral sensitivity at different gestational weeks.

[0006] Furthermore, the specific execution steps of the morning sickness feature analysis module include: The gastric acid exposure window is determined based on the timing of morning sickness. The gastric acid exposure window describes the period of time that gastric acid is exposed in the oral cavity. A cumulative acid exposure parameter is generated based on the frequency and duration of morning sickness. This cumulative acid exposure parameter is used to reflect the total amount of gastric acid exposure during a specific period. The gastric acid erosion intensity parameter is calculated based on the pH value of the vomit acid. This parameter is used to describe the theoretical demineralization capacity of acidic liquids on tooth enamel. A gastric acid erosion risk feature vector is constructed based on the acid exposure window, cumulative acid exposure parameters, and gastric acid erosion intensity parameters to provide input data for the erosion risk assessment module.

[0007] Furthermore, the specific execution steps of the tooth feature analysis module include: The enamel acid resistance decay parameter is calculated based on enamel thickness and the degree of tooth surface mineralization, which is used to characterize the tooth's resistance to acidic environments. Potential acid-erosion vulnerable areas were identified based on the morphology of microcracks on the tooth surface and the trend of demineralization on the tooth surface, and the local fragility parameters of the tooth surface in the acid-erosion vulnerable areas were evaluated. The probability of tooth surface contact is assessed based on tooth surface exposure and tooth arch morphology, which is used to describe the actual probability of tooth surface contact with vomit acid during vomiting. A tooth acid resistance feature vector is constructed based on enamel acid resistance decay parameters, tooth surface local fragility parameters, and tooth surface contact probability.

[0008] Furthermore, the specific execution steps of the erosion risk assessment module include: The gastric acid erosion risk feature vector is coupled with the tooth acid resistance feature vector to generate acid erosion risk prediction values ​​for each tooth surface region, including acid erosion rate prediction values ​​and acid erosion depth prediction values. The spatial distribution coefficient of the actual contact intensity between vomiting acid and the tooth surface was evaluated based on the exposure angle of different tooth surface regions. An acid etching cumulative model was constructed based on the predicted acid etching risk value and spatial distribution coefficient to assess the acid etching risk level of different tooth surface regions and generate an individualized acid etching risk level map for pregnant women.

[0009] Furthermore, the specific execution steps of the oral health risk assessment module include: Obtain the oral sensitivity feature vector output by the gestational age physiological characteristic analysis module and the acid erosion risk level map output by the erosion risk assessment module, and extract the acid erosion risk level corresponding to different tooth surface areas. Based on oral sensitivity feature vector analysis, dynamics of morning sickness frequency, trends in salivary buffering capacity, and local demineralization rate of tooth surface are analyzed to generate time-series-based oral health degradation curves. Based on the oral health degradation curve and acid erosion risk level, an oral health risk assessment model was constructed under the coupled influence of gestational sensitivity and acid erosion risk. The oral sensitivity and acid erosion risk at different stages of pregnancy were fused to assess the comprehensive probability of damage to the oral mucosa, periodontal tissues and enamel. The overall probability of damage is used as the oral health risk, and the oral health risk assessment results are output.

[0010] Secondly, the present invention provides a method for managing oral health examinations in pregnant women, including: Data on progesterone levels, immune responses, and saliva composition of pregnant women at each gestational week were obtained, and oral sensitivity feature vectors corresponding to each gestational week were constructed. The frequency, timing, duration, and pH value of vomited acid in pregnant women were obtained, and a feature vector of gastric acid erosion risk was constructed. Acquire dental characteristic data of pregnant women, including enamel thickness, microcrack morphology, degree of mineralization, distribution of sensitive areas, demineralization trend, dentition morphology, and tooth surface exposure, and construct a feature vector of tooth acid resistance. The risk feature vector of gastric acid erosion was coupled with the feature vector of tooth acid resistance, and the risk of tooth surface acid erosion caused by vomiting was assessed based on the exposure degree and local mineralization degree of different tooth surface areas. Based on the joint modeling of oral sensitivity feature vectors and tooth surface acid erosion risk assessment results, individualized oral health risk assessment results for pregnant women are generated.

[0011] Thirdly, the present invention provides an electronic device, comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes a method for managing oral health examinations of pregnant women by calling the computer program stored in the memory.

[0012] Fourthly, the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform a method for managing oral health examinations of pregnant women.

[0013] Compared with the prior art, the present invention has the following advantages and beneficial effects: (1) By coupling the characteristics of morning sickness with the characteristics of tooth structure, this invention can quantitatively assess the risk of tooth surface erosion caused by vomiting, making the expression of the effect of gastric acid erosion in different tooth surface areas more accurate, and improving the accuracy of predicting the risk of tooth surface erosion caused by gastric acid.

[0014] (2) By introducing physiological characteristics of pregnancy, including fluctuations in progesterone, changes in immune response and dynamic changes in salivary buffering capacity, this invention realizes the quantitative expression of oral sensitivity of pregnant women at different stages of pregnancy. Based on the differences in pregnancy, the intensity of gastric acid erosion is dynamically adjusted, effectively reflecting the stage-by-stage changes in the decline of oral tissue resistance during pregnancy, and effectively improving the temporal accuracy of oral health risk assessment. Attached Figure Description

[0015] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a schematic diagram of the oral health examination and management system for pregnant women provided in an embodiment of the present invention; Figure 2 This is a flowchart illustrating the oral health examination and management method for pregnant women provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0016] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations thereof. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0017] Please see Figure 1 , Figure 1 This is a schematic diagram of the oral health examination and management system for pregnant women provided in an embodiment of the present invention, including: The gestational physiological characteristics analysis module 210 is used to obtain progesterone level data, immune response data and saliva composition data of pregnant women at each gestational week, and to construct oral sensitivity feature vectors corresponding to each gestational week. The morning sickness feature analysis module 220 is used to obtain the frequency of morning sickness, the time of occurrence of morning sickness, the duration of morning sickness, the pH value of vomit acid, and to construct a feature vector of gastric acid erosion risk. The tooth feature analysis module 230 is used to obtain tooth feature data of pregnant women, including enamel thickness, tooth surface microcrack morphology, tooth surface mineralization degree, distribution of tooth sensitive areas, tooth surface demineralization trend, tooth row morphology and tooth surface exposure, and to construct a tooth acid resistance feature vector. The erosion risk assessment module 240 is used to couple and analyze the gastric acid erosion risk feature vector with the tooth acid resistance feature vector, and assess the risk of tooth surface acid erosion caused by vomiting based on the exposure degree and local mineralization degree of different tooth surface areas. The oral health risk assessment module 250 is used to jointly model based on oral sensitivity feature vectors and tooth surface acid erosion risk assessment results to generate personalized oral health risk assessment results for pregnant women.

[0018] In this embodiment of the invention, the gestational physiological characteristic analysis module 210 is used to acquire progesterone level data, immune response data and saliva composition data of pregnant women at each gestational week, and to construct oral sensitivity feature vectors corresponding to each gestational week. The gestational physiological characteristics analysis module comprehensively acquires dynamic changes in progesterone levels, immune status, and saliva composition at different gestational weeks to construct a quantitative feature vector of oral sensitivity in pregnant women. This reveals the physiological mechanism of the gradual decline in oral resistance during pregnancy. Specifically, the rapid increase in progesterone (such as estrogen and progesterone) in early pregnancy leads to increased blood flow to the gums and enhanced capillary permeability, making the gums more prone to redness, swelling, congestion, and inflammation. The immune system is in a suppressed state during pregnancy to protect the embryo from rejection, but changes in immune status also reduce the oral tissue's resistance to bacteria and inflammatory stimuli. Furthermore, severe morning sickness in early pregnancy is often accompanied by reduced saliva secretion and decreased saliva buffering capacity, thus amplifying the risk of gastric acid erosion. The gestational age physiological characteristic analysis module accurately reflects the increased susceptibility to gingival inflammation caused by progesterone fluctuations, the decreased local anti-inflammatory and anti-infective capabilities due to immunosuppression during pregnancy, and the weakened acid resistance of tooth surfaces caused by reduced saliva secretion and decreased buffering capacity. This allows it to capture the significantly amplified characteristics of acid erosion from morning sickness, bacterial stimulation, and local inflammation at different stages of pregnancy. By dynamically adjusting for the risk of gastric acid erosion, the module enables the system to provide more realistic risk assessment results based on the phased characteristics of rapidly increasing sensitivity in early pregnancy, relative stability in mid-pregnancy, and a renewed decline in immunity in late pregnancy. This significantly improves the accuracy of oral health risk prediction throughout pregnancy. The specific execution steps of the gestational age physiological characteristic analysis module include: Based on progesterone level data, progesterone fluctuation trend analysis was performed, and the rate of change of peak progesterone was used as the progesterone perturbation parameter for each gestation week. Based on immune response data, parameters of local oral immunosuppression were extracted, including parameters of decreased immune cell activity, parameters of susceptibility to inflammation, and parameters of decreased oral barrier function. Based on saliva composition data, salivary buffering characteristic parameters were extracted, including saliva buffering capacity parameters, mineral concentration parameters, saliva viscosity parameters, and saliva secretion cycle parameters. The parameters of progesterone perturbation, oral local immunosuppression, and salivary buffering were normalized, and an oral sensitivity feature vector was constructed to reflect changes in oral sensitivity at different gestational weeks.

[0019] In this embodiment of the invention, the morning sickness feature analysis module 220 is used to obtain the frequency of morning sickness, the time of occurrence of morning sickness, the duration of morning sickness, the pH value of vomit acid, and to construct a gastric acid erosion risk feature vector. Morning sickness causes highly acidic stomach contents to repeatedly come into contact with the oral cavity. The pH value of the vomit acid is lower than the critical pH for enamel demineralization; therefore, reflux will cause acid erosion of the enamel. When morning sickness is frequent or prolonged, the cumulative effect of acid exposure on the enamel increases, making it prone to chalky spots, early decalcification, tooth sensitivity, thinning of the tooth surface, and even wedge-shaped defects. Simultaneously, reduced saliva secretion and decreased saliva buffering capacity during pregnancy make the acidic environment more difficult to neutralize, further exacerbating the risk of tooth erosion and sensitivity. The morning sickness characteristic analysis module is used to quantitatively describe the vomiting behavior of pregnant women and the resulting biochemical characteristics of repeated gastric acid entering the oral cavity. By characterizing the time window and intensity of oral exposure to the acidic environment, it assesses the acid erosion load on the pregnant woman's oral cavity during pregnancy, providing data support for subsequent assessment of the risk of gastric acid erosion. The specific execution steps of the morning sickness characteristic analysis module include: The gastric acid exposure window is determined based on the timing of morning sickness. The gastric acid exposure window describes the period of time that gastric acid is exposed in the oral cavity. A cumulative acid exposure parameter is generated based on the frequency and duration of morning sickness. This cumulative acid exposure parameter is used to reflect the total amount of gastric acid exposure during a specific period. The gastric acid erosion intensity parameter is calculated based on the pH value of the vomit acid. This parameter is used to describe the theoretical demineralization capacity of acidic liquids on tooth enamel. A gastric acid erosion risk feature vector is constructed based on the acid exposure window, cumulative acid exposure parameters, and gastric acid erosion intensity parameters to provide input data for the erosion risk assessment module.

[0020] In this embodiment of the invention, the tooth feature analysis module 230 is used to acquire the tooth feature data of pregnant women, including enamel thickness, tooth surface microcrack morphology, tooth surface mineralization degree, distribution of tooth sensitive areas, tooth surface demineralization trend, tooth row morphology and tooth surface exposure, and to construct a tooth acid resistance feature vector. Because there are significant differences in enamel thickness, tooth surface mineralization levels, and the number and depth of microcracks on the tooth surface among pregnant women, the degree of acid erosion varies among individuals even with the same intensity of gastric acid contact. The erosion risk assessment module identifies potentially acid-erosion-vulnerable areas on the tooth surface. For example, areas with thinner enamel and concentrated microcracks are more susceptible to acid erosion during morning sickness. If local weaknesses are not identified in time, progressive damage such as accelerated demineralization, tooth surface depression, and increased sensitivity will occur as the frequency of morning sickness increases. By quantifying the local vulnerability parameters of acid-erosion-vulnerable areas, a refined prediction of acid erosion risk can be achieved. At the same time, the actual probability of tooth surface contact with vomiting acid is assessed through tooth morphology and tooth surface exposure, making the acid erosion risk prediction closer to the real scenario. The specific execution steps of the tooth feature analysis module include: Enamel acid attenuation parameters are calculated based on enamel thickness and tooth surface mineralization to characterize the tooth's resistance to acidic environments. Specifically, tooth surface structure data are acquired using three-dimensional scanning or optical imaging technology, and enamel thickness in each tooth surface region is measured at micron-level resolution. Quantitative optical density analysis is used to assess the degree of tooth surface mineralization, including hydroxyapatite content and mineral uniformity. The enamel thickness and tooth surface mineralization are combined, and a weighted linear function is used to calculate the corresponding acid attenuation parameters for each tooth surface region. Potential acid-etch-vulnerable areas are identified based on the morphology of microcracks and the trend of demineralization on the tooth surface. Local vulnerability parameters of these areas are then assessed. Specifically, the distribution of microcracks, including crack density, depth, and spatial aggregation characteristics, is obtained through tooth surface scanning. Demineralization trends are identified through tooth surface mineralization gradient analysis, and areas of accelerated demineralization are marked as acid-etch-vulnerable areas. Weighted calculations of microcrack density, depth, and demineralization trend are used to generate local vulnerability parameters for these acid-etch-vulnerable areas, reflecting their likelihood of being more susceptible to acid etch damage during the erosion process. This study assesses tooth surface contact probability based on tooth surface exposure and dentition morphology, describing the actual contact probability of tooth surfaces with vomiting acid during vomiting. Specifically, a dentition morphology model is obtained through 3D oral scanning, and the 3D coordinate position and orientation of each tooth in the oral cavity are calibrated, including tilt angle, rotation angle, and occlusal gap. A 3D vector model of the vomiting acid spray path during morning sickness is established. The intersection area between each tooth surface region and the vomiting acid spray path is calculated. Tooth surface orientation, exposure angle, and dentition occlusion relationship are incorporated into spatial geometric constraints to assess the probability of actual contact of each tooth surface under acid spray. Monte Carlo simulation is used to combine the tooth surface exposure area with the intersection area of ​​the spray path to generate contact probability parameters for each tooth surface region. A tooth acid resistance feature vector is constructed based on enamel acid resistance decay parameters, tooth surface local fragility parameters, and tooth surface contact probability.

[0021] In this embodiment of the invention, the erosion risk assessment module 240 is used to couple and analyze the gastric acid erosion risk feature vector with the tooth acid resistance feature vector, and assess the risk of tooth surface acid erosion caused by vomiting based on the exposure degree and local mineralization degree of different tooth surface areas. In real-life morning sickness scenarios, the degree of tooth surface damage from gastric acid is not solely determined by the intensity or frequency of gastric acid exposure, but rather by the combined effect of acid exposure intensity and the tooth's own acid resistance. For example, under the same gastric acid exposure, areas with thinner enamel, lower mineralization, or concentrated microcracks will experience significantly higher acid erosion rates than areas with good mineralization or thicker enamel. By introducing the exposure angles and spatial contact structures of different tooth surface areas, a spatial model of the acid contact intensity for each tooth surface area is constructed. For instance, the labial surfaces of anterior teeth are more likely to directly contact acid in the vomiting jet path, resulting in a higher spatial distribution coefficient; while the occlusal surfaces of posterior teeth may experience prolonged contact time due to brief acid retention. The erosion risk assessment module significantly improves the accuracy of erosion risk prediction through spatial, regional, and cumulative multidimensional risk analysis. The specific execution steps of the erosion risk assessment module include: The gastric acid erosion risk feature vector is coupled with the tooth acid resistance feature vector to generate acid erosion risk prediction values ​​for each tooth surface region, including acid erosion rate prediction values ​​and acid erosion depth prediction values. Specifically, the gastric acid erosion risk feature vector and the tooth acid resistance feature vector are matched element-wise, and the acid erosion rate prediction value and acid erosion depth prediction value are calculated for each tooth surface region. Either a weighted product model or a linear coupling model can be used. The spatial distribution coefficient of the actual contact intensity between vomiting acid and tooth surface is evaluated based on the exposure angle of different tooth surface areas. Specifically, a three-dimensional spatial model of the dental arch is established, and each tooth and its surface area are divided into unit surfaces. According to the acid spray path during morning sickness, the contact intensity between each tooth surface unit surface and acid is calculated by ray tracing or geometric projection method to obtain the spatial distribution coefficient of each tooth surface area. An acid erosion accumulation model is constructed based on the predicted acid erosion risk value and the spatial distribution coefficient to assess the acid erosion risk level of different tooth surface regions and generate an individualized acid erosion risk level map for pregnant women. Specifically, the predicted acid erosion risk value of each tooth surface region is weighted and combined with the corresponding spatial distribution coefficient to obtain the local acid erosion load of a single morning sickness event; the acid erosion load of multiple morning sickness events in a pregnant woman within a specific cycle is accumulated; and the accumulated acid erosion results of each tooth surface region are mapped to the acid erosion risk level interval to form an individualized acid erosion risk level map for pregnant women.

[0022] In this embodiment of the invention, the oral health risk assessment module 250 is used to perform joint modeling based on the oral sensitivity feature vector and the tooth surface acid erosion risk assessment result to generate individualized oral health risk assessment results for pregnant women. Because oral sensitivity varies significantly among pregnant women at different gestational weeks, relying solely on morning sickness or dental hard tissue data is insufficient to fully reflect the actual risks. Therefore, the oral health risk assessment module introduces the interaction between oral sensitivity feature vectors and acid erosion risk level maps. This allows it to reveal the dynamic degradation process of oral health during pregnancy over time, thereby constructing a risk assessment model that better reflects individual differences among pregnant women. This results in individualized risk assessments for different gestational weeks, oral structures, and morning sickness characteristics, providing clear and interpretable health risk assessment data for pregnant women. The specific implementation steps of the oral health risk assessment module include: Obtain the oral sensitivity feature vector output by the gestational age physiological characteristic analysis module and the acid erosion risk level map output by the erosion risk assessment module, and extract the acid erosion risk level corresponding to different tooth surface areas. Based on the analysis of oral sensitivity feature vectors, the dynamics of morning sickness frequency, the changing trend of salivary buffering capacity, and the local demineralization rate of the tooth surface are analyzed, an oral health degradation curve based on time series is generated. Specifically, the frequency, duration, and acid exposure window of the pregnant woman's morning sickness are combined with the oral sensitivity feature vector to calculate the tooth surface acid erosion rate and local demineralization rate for each gestational week. The tooth surface remineralization capacity and acid erosion accumulation rate are corrected based on the salivary buffering capacity parameter. The local tooth surface demineralization rate and sensitivity changes for each gestational week are quantified into a continuous numerical sequence with gestational week as the time axis, forming an oral health degradation curve based on time series. Based on oral health degradation curves and acid erosion risk levels, an oral health risk assessment model is constructed to assess the combined influence of gestational sensitivity and acid erosion risk. This model integrates the characteristics of oral sensitivity and acid erosion risk at different stages of pregnancy to evaluate the overall probability of damage to the oral mucosa, periodontal tissues, and enamel. Specifically, the time-series data in the oral health degradation curve are spatially matched with the acid erosion risk levels of each tooth surface region output by the erosion risk assessment module. For each tooth surface region, an oral health risk assessment model based on logistic regression is constructed to perform coupled analysis of gestational sensitivity and acid erosion risk levels and output the overall probability of damage. The overall probability of damage is used as the oral health risk, and the oral health risk assessment results are output.

[0023] Please see Figure 2 , Figure 2 This is a schematic diagram of the overall process of the oral health examination and management method for pregnant women provided in this embodiment of the invention, which specifically includes the following steps: S100. Obtain progesterone level data, immune response data, and saliva composition data for each gestational week of the pregnant woman, and construct oral sensitivity feature vectors corresponding to each gestational week, including: Based on progesterone level data, progesterone fluctuation trend analysis was performed, and the rate of change of peak progesterone was used as the progesterone perturbation parameter for each gestation week. Based on immune response data, parameters of local oral immunosuppression were extracted, including parameters of decreased immune cell activity, parameters of susceptibility to inflammation, and parameters of decreased oral barrier function. Based on saliva composition data, salivary buffering characteristic parameters were extracted, including saliva buffering capacity parameters, mineral concentration parameters, saliva viscosity parameters, and saliva secretion cycle parameters. The parameters of progesterone perturbation, oral local immunosuppression, and salivary buffering were normalized, and an oral sensitivity feature vector was constructed to reflect changes in oral sensitivity at different gestational weeks.

[0024] S200: Obtain the frequency, timing, duration, and pH value of vomited acid in pregnant women, and construct a feature vector for the risk of gastric acid erosion, including: The gastric acid exposure window is determined based on the timing of morning sickness. The gastric acid exposure window describes the period of time that gastric acid is exposed in the oral cavity. A cumulative acid exposure parameter is generated based on the frequency and duration of morning sickness. This cumulative acid exposure parameter is used to reflect the total amount of gastric acid exposure during a specific period. The gastric acid erosion intensity parameter is calculated based on the pH value of the vomit acid. This parameter is used to describe the theoretical demineralization capacity of acidic liquids on tooth enamel. A gastric acid erosion risk feature vector is constructed based on the acid exposure window, cumulative acid exposure parameters, and gastric acid erosion intensity parameters to provide input data for the erosion risk assessment module.

[0025] S300. Obtain dental characteristic data of pregnant women, including enamel thickness, microcrack morphology, degree of tooth surface mineralization, distribution of sensitive areas, demineralization trend of tooth surface, dentition morphology, and tooth surface exposure, and construct a tooth acid resistance feature vector, including: The enamel acid resistance decay parameter is calculated based on enamel thickness and the degree of tooth surface mineralization, which is used to characterize the tooth's resistance to acidic environments. Potential acid-erosion vulnerable areas were identified based on the morphology of microcracks on the tooth surface and the trend of demineralization on the tooth surface, and the local fragility parameters of the tooth surface in the acid-erosion vulnerable areas were evaluated. The probability of tooth surface contact is assessed based on tooth surface exposure and tooth arch morphology, which is used to describe the actual probability of tooth surface contact with vomit acid during vomiting. A tooth acid resistance feature vector is constructed based on enamel acid resistance decay parameters, tooth surface local fragility parameters, and tooth surface contact probability.

[0026] S400. Couple the gastric acid erosion risk feature vector with the tooth acid resistance feature vector for analysis, and assess the risk of tooth surface acid erosion caused by vomiting based on the exposure degree and local mineralization degree of different tooth surface areas, including: The gastric acid erosion risk feature vector is coupled with the tooth acid resistance feature vector to generate acid erosion risk prediction values ​​for each tooth surface region, including acid erosion rate prediction values ​​and acid erosion depth prediction values. The spatial distribution coefficient of the actual contact intensity between vomiting acid and the tooth surface was evaluated based on the exposure angle of different tooth surface regions. An acid etching cumulative model was constructed based on the predicted acid etching risk value and spatial distribution coefficient to assess the acid etching risk level of different tooth surface regions and generate an individualized acid etching risk level map for pregnant women.

[0027] S500, based on joint modeling of oral sensitivity feature vectors and tooth surface acid erosion risk assessment results, generates individualized oral health risk assessment results for pregnant women, including: Obtain the oral sensitivity feature vector output by the gestational age physiological characteristic analysis module and the acid erosion risk level map output by the erosion risk assessment module, and extract the acid erosion risk level corresponding to different tooth surface areas. Based on oral sensitivity feature vector analysis, dynamics of morning sickness frequency, trends in salivary buffering capacity, and local demineralization rate of tooth surface are analyzed to generate time-series-based oral health degradation curves. Based on the oral health degradation curve and acid erosion risk level, an oral health risk assessment model was constructed under the coupled influence of gestational sensitivity and acid erosion risk. The oral sensitivity and acid erosion risk at different stages of pregnancy were fused to assess the comprehensive probability of damage to the oral mucosa, periodontal tissues and enamel. The overall probability of damage is used as the oral health risk, and the oral health risk assessment results are output.

[0028] The parameters and steps in the above embodiments of the oral health examination and management method for pregnant women of the present invention can be referred to the parameters and steps of each unit module of the oral health examination and management system for pregnant women to achieve the corresponding functions, and will not be repeated here.

[0029] Please refer to Figure 3 The present invention also provides an electronic device, which includes a processor, an internal bus, a network interface, an internal memory, a memory, and a program or instructions stored in the memory and executable on the processor. When the program or instructions are executed by the processor, they implement any of the oral health examination and management methods for pregnant women as described in the embodiments of the present invention. The processor can be a general-purpose central processing unit (CPU), microprocessor, application-specific integrated circuit (ASIC), graphics processing unit (GPU), or one or more integrated circuits, used to execute relevant programs to implement any of the oral health examination and management methods for pregnant women as described in the embodiments of the present invention.

[0030] The processor can also be an integrated circuit electronic device with signal processing capabilities. In implementation, each step of any of the oral health examination and management methods for pregnant women in this invention can be completed through integrated logic circuits in the processor's hardware or through software instructions.

[0031] The aforementioned processor can also be a general-purpose processor, digital signal processor, application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the functions required by the units included in the data processing apparatus of the embodiments of this invention, or executes any of the oral health examination and management methods for pregnant women in the embodiments of this invention.

[0032] An internal bus may include a pathway for transmitting information between the aforementioned components. The internal bus can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Internal buses can be divided into address buses, data buses, control buses, etc. For ease of representation, Figure 3 The symbol is represented by a single double arrow, but this does not mean that there is only one bus or one type of bus.

[0033] A network interface is used to enable data interaction between electronic devices and external communication networks. The network interface can be an Ethernet interface, an optical fiber interface, or a wireless communication interface.

[0034] Internal memory provides temporary data read and write space for electronic devices. Internal memory can adopt random access memory (RAM), cache, or other storage structures with fast read and write capabilities. Internal memory exchanges data with the processor at high speed through an internal bus.

[0035] The memory is used to store the operating system, computer program, and database of the electronic device for a long time, ensuring that the system can maintain the integrity and reliability of the data in the event of power failure or restart. The operating system can be embedded Linux, real-time operating system (RTOS), or other software platform that can manage system resources and support secure communication protocols. The computer program is used to implement any of the oral health examination management methods for pregnant women as described in the embodiments of the present invention. The database is used to store the running data of the computer program.

[0036] This invention provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed as described in the above embodiments for managing oral health examinations of pregnant women.

[0037] In this embodiment of the invention, the computer-readable storage medium can be a tangible device that holds and stores instructions used by an instruction execution device. The computer-readable storage medium can be, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof. Specifically, the computer-readable storage medium can be a portable computer disk, a hard disk, a USB flash drive, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), lectern random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory stick, floppy disk, optical disk, magnetic disk, mechanical encoding device, or any combination thereof.

[0038] The terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0039] The above description is merely a preferred embodiment of the present invention and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this application is not limited to the technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions claimed in this invention.

Claims

1. A prenatal oral health check and management system, characterized in that, It includes modules for analyzing the physiological characteristics of gestational age, analyzing the characteristics of morning sickness, analyzing the characteristics of teeth, assessing the risk of erosion, and assessing the risk of oral health. Among them, the gestational week physiological characteristic analysis module is used to obtain progesterone level data, immune response data and saliva composition data of pregnant women at each gestational week, and construct oral sensitivity feature vectors corresponding to each gestational week. The morning sickness feature analysis module is used to obtain the frequency of morning sickness, the time of occurrence of morning sickness, the duration of morning sickness, the pH value of vomit acid, and to construct a feature vector of gastric acid erosion risk. The tooth feature analysis module is used to obtain tooth feature data of pregnant women, including enamel thickness, microcrack morphology, degree of tooth surface mineralization, distribution of tooth sensitivity areas, demineralization trend of tooth surface, dentition morphology and tooth surface exposure, and to construct a tooth acid resistance feature vector. The erosion risk assessment module is used to couple and analyze the gastric acid erosion risk feature vector with the tooth acid resistance feature vector, and assess the risk of tooth surface acid erosion caused by vomiting based on the exposure degree and local mineralization degree of different tooth surface areas. The oral health risk assessment module is used to jointly model based on oral sensitivity feature vectors and tooth surface acid erosion risk assessment results to generate personalized oral health risk assessment results for pregnant women.

2. The oral health examination and management system for pregnant women according to claim 1, characterized in that, The specific execution steps of the gestational age physiological characteristic analysis module include: Based on progesterone level data, progesterone fluctuation trend analysis was performed, and the rate of change of peak progesterone was used as the progesterone perturbation parameter for each gestation week. Based on immune response data, parameters of local oral immunosuppression were extracted, including parameters of decreased immune cell activity, parameters of susceptibility to inflammation, and parameters of decreased oral barrier function. Based on saliva composition data, salivary buffering characteristic parameters were extracted, including saliva buffering capacity parameters, mineral concentration parameters, saliva viscosity parameters, and saliva secretion cycle parameters. The parameters of progesterone perturbation, oral local immunosuppression, and salivary buffering were normalized, and an oral sensitivity feature vector was constructed to reflect changes in oral sensitivity at different gestational weeks.

3. The oral health examination and management system for pregnant women according to claim 1, characterized in that, The specific execution steps of the morning sickness feature analysis module include: The gastric acid exposure window is determined based on the timing of morning sickness. The gastric acid exposure window describes the period of time that gastric acid is exposed in the oral cavity. A cumulative acid exposure parameter is generated based on the frequency and duration of morning sickness. This cumulative acid exposure parameter is used to reflect the total amount of gastric acid exposure during a specific period. The gastric acid erosion intensity parameter is calculated based on the pH value of the vomit acid. This parameter is used to describe the theoretical demineralization capacity of acidic liquids on tooth enamel. A gastric acid erosion risk feature vector is constructed based on the acid exposure window, cumulative acid exposure parameters, and gastric acid erosion intensity parameters to provide input data for the erosion risk assessment module.

4. The oral health examination and management system for pregnant women according to claim 1, characterized in that, The specific execution steps of the tooth feature analysis module include: The enamel acid resistance decay parameter is calculated based on enamel thickness and the degree of tooth surface mineralization, which is used to characterize the tooth's resistance to acidic environments. Potential acid-erosion vulnerable areas were identified based on the morphology of microcracks on the tooth surface and the trend of demineralization on the tooth surface, and the local fragility parameters of the tooth surface in the acid-erosion vulnerable areas were evaluated. The probability of tooth surface contact is assessed based on tooth surface exposure and tooth arch morphology, which is used to describe the actual probability of tooth surface contact with vomit acid during vomiting. A tooth acid resistance feature vector is constructed based on enamel acid resistance decay parameters, tooth surface local fragility parameters, and tooth surface contact probability.

5. The oral health examination and management system for pregnant women according to claim 1, characterized in that, The specific execution steps of the erosion risk assessment module include: The gastric acid erosion risk feature vector is coupled with the tooth acid resistance feature vector to generate acid erosion risk prediction values ​​for each tooth surface region, including acid erosion rate prediction values ​​and acid erosion depth prediction values. The spatial distribution coefficient of the actual contact intensity between vomiting acid and the tooth surface was evaluated based on the exposure angle of different tooth surface regions. An acid etching cumulative model was constructed based on the predicted acid etching risk value and spatial distribution coefficient to assess the acid etching risk level of different tooth surface regions and generate an individualized acid etching risk level map for pregnant women.

6. The oral health examination and management system for pregnant women according to claim 1, characterized in that, The specific execution steps of the oral health risk assessment module include: Obtain the oral sensitivity feature vector output by the gestational age physiological characteristic analysis module and the acid erosion risk level map output by the erosion risk assessment module, and extract the acid erosion risk level corresponding to different tooth surface areas. Based on oral sensitivity feature vector analysis, dynamics of morning sickness frequency, trends in salivary buffering capacity, and local demineralization rate of tooth surface are analyzed to generate time-series-based oral health degradation curves. Based on the oral health degradation curve and acid erosion risk level, an oral health risk assessment model was constructed under the coupled influence of gestational sensitivity and acid erosion risk. The oral sensitivity and acid erosion risk at different stages of pregnancy were fused to assess the comprehensive probability of damage to the oral mucosa, periodontal tissues and enamel. The overall probability of damage is used as the oral health risk, and the oral health risk assessment results are output.

7. A method for managing oral health examinations of pregnant women, applied to the oral health examination management system for pregnant women as described in any one of claims 1-6, characterized in that, The method includes: Data on progesterone levels, immune responses, and saliva composition of pregnant women at each gestational week were obtained, and oral sensitivity feature vectors corresponding to each gestational week were constructed. The frequency, timing, duration, and pH value of vomited acid in pregnant women were obtained, and a feature vector of gastric acid erosion risk was constructed. Acquire dental characteristic data of pregnant women, including enamel thickness, microcrack morphology, degree of mineralization, distribution of sensitive areas, demineralization trend, dentition morphology, and tooth surface exposure, and construct a feature vector of tooth acid resistance. The risk feature vector of gastric acid erosion was coupled with the feature vector of tooth acid resistance, and the risk of tooth surface acid erosion caused by vomiting was assessed based on the exposure degree and local mineralization degree of different tooth surface areas. Based on the joint modeling of oral sensitivity feature vectors and tooth surface acid erosion risk assessment results, individualized oral health risk assessment results for pregnant women are generated.

8. An electronic device, comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; characterized in that the processor executes the oral health examination and management method for pregnant women as described in claim 7 by calling the computer program stored in the memory.

9. A computer-readable storage medium, characterized in that, The system stores instructions that, when executed on a computer, cause the computer to perform the oral health examination management method for pregnant women as described in claim 7.

Images