A method and device for assessing the difficulty of removing an intracanal separation instrument

Abstract

The application relates to the technical field of medical evaluation, and discloses a root canal in-separation instrument taking-out difficulty evaluation method and device, which comprises the following steps: acquiring original case data, performing continuous variable grading processing on the original case data to obtain in-separation instrument taking-out factor categories; performing difficulty assignment on the in-separation instrument taking-out factor categories to determine a root canal in-separation instrument taking-out difficulty assignment table; acquiring measured case data, and based on the measured case data, using the root canal in-separation instrument taking-out difficulty assignment table and grading thresholds to evaluate the root canal in-separation instrument taking-out difficulty and obtaining a root canal in-separation instrument taking-out difficulty evaluation result. The application realizes objective and quantitative evaluation of the root canal in-separation instrument taking-out difficulty.

Description

Technical Field

[0001] This invention relates to the field of medical assessment technology, specifically to a method and device for assessing the difficulty of removing endovascular instruments. Background Technology

[0002] Intracanal instrument separation is a common complication in root canal treatment. It not only hinders the thorough cleaning and shaping of the root canal system, significantly increasing the risk of root canal treatment failure, but the difficulty of removing the separated instruments is also affected by a variety of factors, including tooth position, instrument material, and root canal anatomy, which further increases the difficulty of removing the separated instruments from the root canal.

[0003] Currently, the assessment of the difficulty in removing dissection instruments mainly relies on the doctor's clinical experience, lacking objective and quantitative assessment standards. Summary of the Invention

[0004] This invention provides a method and apparatus for assessing the difficulty of removing endoscopic instruments, in order to solve the problem that the assessment method for the difficulty of removing endoscopic instruments lacks objective and quantitative assessment standards.

[0005] In a first aspect, the present invention provides a method for assessing the difficulty of removing endodontic dissection instruments, the method comprising: Obtain the original case data, perform continuous variable classification on the original case data, and obtain the factor categories for the removal of separation instruments; Assign difficulty values ​​to the factors that influence the removal of dissecting instruments, and determine the difficulty scoring table for removing dissecting instruments from the root canal. Data from actual cases were obtained. Based on the data from actual cases, the difficulty of removing instruments from the root canal was assessed using a scoring table and grading thresholds. The assessment results of the difficulty of removing instruments from the root canal were obtained.

[0006] This invention provides a method for assessing the difficulty of removing endodontic instruments. By performing continuous variable grading on original case data, it systematically integrates multi-dimensional key factors affecting the difficulty of endodontic instrument removal, assigns difficulty values ​​to the categories of removal factors, and establishes a scoring table for the difficulty of endodontic instrument removal. This solidifies clinical experience into quantifiable scoring rules, eliminating subjectivity and arbitrariness in the assessment process. It ensures high consistency and repeatability of assessment results from different doctors for the same case. By using the scoring table for the difficulty of endodontic instrument removal to assess the difficulty and grading thresholds, it achieves an objective and quantitative assessment of the difficulty of endodontic instrument removal. This allows preoperative assessment to more realistically reflect the actual complexity of the intraoperative situation, resulting in a more comprehensive and accurate assessment of the difficulty of endodontic instrument removal.

[0007] In one optional implementation, the original case data is subjected to continuous variable hierarchical processing to obtain the separation device removal factor category, including: Distribution analysis was performed on the continuous variables in the original case data to obtain the distribution curves of the continuous variables; among them, the continuous variables included root canal curvature, dissection instrument depth, minimum root canal wall thickness at the cut end, and dissection instrument length; By using the distribution curve of the continuous variable, the threshold optimization calculation is performed on the continuous variable to obtain the optimal cutoff value; By classifying continuous variables using the optimal cutoff value, the categories of factors removed by the separation device can be obtained.

[0008] This invention provides a method for assessing the difficulty of removing endodontic instruments. It performs distribution analysis on continuous variables in the original case data, avoiding bias caused by subjective experience-based grouping, resulting in more objective and reliable results. By optimizing the threshold to determine the optimal cutoff value, the method maximizes the distinguishing and predictive ability of continuous variables. Furthermore, by using the optimal cutoff value to classify continuous variables, it scientifically transforms them into categorical variables, preserving data information while facilitating clinical understanding and practical application. This lays the foundation for subsequent objective quantitative assessment of the difficulty of removing endodontic instruments.

[0009] In one optional implementation, distribution analysis is performed on the continuous variables in the original case data to obtain the distribution curves of the continuous variables, including: Descriptive statistics are calculated for continuous variables to obtain statistical indicators; Draw frequency distribution histograms based on continuous variables and statistical indicators; By overlaying the kernel density curve onto the frequency distribution histogram, the distribution curve of the continuous variable is obtained.

[0010] This invention provides a method for assessing the difficulty of removing endovascular instruments. It calculates descriptive statistics for continuous variables to obtain statistical indicators, which comprehensively and quantitatively describe the central tendency and dispersion of the continuous variables. Based on the continuous variables and statistical indicators, a frequency distribution histogram is plotted, which visually displays the data distribution pattern. Furthermore, a kernel density curve is superimposed on the frequency distribution histogram to more closely approximate the true probability distribution of the data. The superposition of the frequency distribution histogram and the kernel density curve not only displays the actual frequency but also the overall distribution trend, significantly improving the accuracy of judging the data distribution characteristics and laying a solid data foundation for subsequent threshold optimization and variable classification.

[0011] In one optional implementation, a difficulty rating is assigned to the factors affecting the removal of dissecting instruments, and a difficulty rating table for removing dissecting instruments from the root canal is determined, including: Obtain the historical case dataset corresponding to the factor categories removed by the separation instrument; Using the category of separation instrument removal factor in the historical case dataset as the independent variable and the separation instrument removal result as the dependent variable, the regression analysis model was used to fit the regression coefficients corresponding to the separation instrument removal factor category. The regression coefficients are mapped to scores indicating the difficulty of removing instruments from the root canal. A scoring table for the difficulty of removing instruments from the root canal was established based on the categories of factors affecting instrument removal and the difficulty score for removing instruments from the root canal.

[0012] This invention provides a method for assessing the difficulty of removing endodontic instruments. By using regression analysis to quantify the true correlation between various influencing factors and the removal outcome, it avoids the subjectivity and bias caused by relying solely on experience to formulate scoring standards, making the assessment results more clinically authentic and scientific. Furthermore, by using regression coefficients, it transforms the complex multi-factor influences into an intuitive, calculable, and clinically applicable difficulty scoring system, facilitating rapid assessment by clinicians, preoperative prediction, and teaching promotion, and providing a reliable basis for preoperative risk assessment.

[0013] In one optional implementation, based on actual case data, the difficulty of removing intracanal dissecting instruments is assessed using a scoring scale and grading thresholds to obtain the assessment result, including: The actual case data were matched with the scoring table for the difficulty of removing instruments from the root canal to obtain the total score for the difficulty of removing instruments from the root canal. Obtain the grading threshold, compare the total score of the difficulty in removing the dissecting instrument from the root canal with the grading threshold, and obtain the difficulty level of removing the dissecting instrument from the root canal. Based on the difficulty level of removing instruments from the root canal, the text of the instrument removal operation strategy is determined using a clinical strategy knowledge base. The assessment results for the difficulty of removing instruments from the root canal were determined based on the total score of the difficulty of removing instruments from the root canal, the difficulty level of removing instruments from the root canal, and the text of the instrument removal operation strategy.

[0014] This invention provides a method for assessing the difficulty of removing intracanal dissecting instruments. It utilizes a scoring scale for the difficulty of removing intracanal dissecting instruments, achieving an objective and quantitative assessment of the difficulty. A grading threshold is used to classify the total difficulty score, ensuring consistent, comparable, and repeatable assessment standards across different doctors and cases, thus improving the standardization and reliability of the assessment results. Based on the difficulty levels, a clinical strategy knowledge base is used to define the instrument removal operation strategy text, linking the difficulty level to a clearly defined clinical operation path. This provides a scientific basis for implementing tiered medical services, helps optimize resource allocation, and improves overall medical quality and safety. Furthermore, the clinical strategy knowledge base can accurately identify and alert potential complication risks preoperatively, enabling doctors to prepare contingency plans in advance, choose safer technical approaches, and shift from passive response to proactive management, providing forward-looking risk warnings.

[0015] In one alternative implementation, it further includes: An effectiveness analysis was performed on the assessment results of the difficulty of removing instruments from the root canal to obtain the true level of difficulty in removing instruments from the root canal.

[0016] This invention provides a method for assessing the difficulty of removing instruments from the root canal. By performing efficacy analysis on the assessment results, the assessment results are made closer to the actual clinical situation, improving the credibility and clinical value of the assessment system, and making the assessment results of the difficulty of removing instruments from the root canal more accurate and effective.

[0017] Secondly, the present invention provides a device for assessing the difficulty of removing endodontic dissection instruments, the device comprising: The grading module is used to acquire raw case data, perform continuous variable grading on the raw case data, and obtain the separation instrument retrieval factor category; The assignment module is used to assign difficulty values ​​to the factors that enable the removal of dissecting instruments, and to determine the difficulty scoring table for removing dissecting instruments from the root canal. The assessment module is used to acquire actual case data. Based on the actual case data, the difficulty of removing instruments from the root canal is assessed using a scoring table and grading thresholds, resulting in an assessment result for the difficulty of removing instruments from the root canal.

[0018] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the method for assessing the difficulty of removing endocanal dissection instruments as described in the first aspect or any corresponding embodiment.

[0019] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the method for assessing the difficulty of retrieval of endocanal dissecting instruments described in the first aspect or any corresponding embodiment thereof.

[0020] Fifthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the method for assessing the difficulty of removing endocanal dissection instruments described in the first aspect or any corresponding embodiment. Attached Figure Description

[0021] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the first step in a method for assessing the difficulty of removing an intracanal dissection instrument according to an embodiment of the present invention. Figure 3 This is a schematic diagram of the second process of a method for assessing the difficulty of removing an intracanal dissection instrument according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the third process of a method for assessing the difficulty of removing an intracanal dissection instrument according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the fourth process of a method for assessing the difficulty of removing an intracanal dissection instrument according to an embodiment of the present invention; Figure 6 This is a structural block diagram of a device for assessing the difficulty of removing an intracanal dissection instrument according to an embodiment of the present invention; Figure 7 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0025] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0026] As an optional application scenario of this invention, such as Figure 1 As shown, application 101 is installed in terminal device 110, and user 130 can interact with application 101 through terminal device 110 and / or access device of terminal device 110.

[0027] For example, application 101 can be any application that provides question-and-answer related services. For instance, application 101 could be a question-and-answer interactive application, such as a text-to-text application, an image-to-text application, etc. Figure 1 In the application scenario shown, if application 101 is active, the terminal device 110 can display the interface 102 of application 101. The interface 102 may include various pages that application 101 can provide, such as interactive pages, settings pages, query pages, etc.

[0028] In some embodiments, terminal device 110 is communicatively connected to server 120 to provide services to application 101. Terminal device 110 may be a mobile terminal, fixed terminal, or portable terminal, etc., including but not limited to mobile phones, desktop computers, laptop computers, multimedia tablets, e-book devices, gaming devices, or any combination thereof, including accessories and peripherals of these devices or any combination thereof. In some embodiments, terminal device 110 may also support any type of interface, and server 120 may be various types of computing systems or servers capable of providing computing power, including but not limited to mainframes, edge computing nodes, computing devices in cloud environments, etc.

[0029] It should be noted that, Figure 1 This is merely an example of an application scenario and does not limit the scope of protection of this invention.

[0030] The embodiments of the present invention will now be described with reference to the accompanying drawings. It should be understood that the pages shown in the drawings are merely examples, and various page designs are possible in practice. The various graphic elements on the page may have different arrangements and different visual representations; one or more elements may be omitted or replaced, and one or more other elements may also be present, without any limitation in the embodiments of the present invention. Furthermore, the embodiments described below primarily pertain to terminal device 110. It should be understood that the actions described relative to terminal device 110 can be performed by application 101 on terminal device 110, or can be performed by application 101 in conjunction with its server (e.g., server 120).

[0031] Currently, the assessment of the difficulty of removing dissecting instruments is mainly based on imaging assessment and experience judgment: anatomical factors such as the position of the instrument, root canal curvature, and root canal wall thickness are analyzed through imaging methods such as periapical radiographs and cone-beam computed tomography (CBE). Physicians judge the difficulty of removing dissecting instruments based on their own experience with previous cases.

[0032] Methods that predict the difficulty of instrument retrieval based on a single or a few factors, such as instrument depth and root canal curvature, often neglect the influence of other important factors, resulting in incomplete and inaccurate predictions.

[0033] Furthermore, the lack of a systematic and standardized assessment process for evaluating the difficulty of dissecting instruments leads to potentially differing conclusions among physicians when faced with the same case, thus affecting treatment planning. Therefore, developing an objective assessment tool that comprehensively considers multiple factors to evaluate the difficulty of dissecting instrument removal is a pressing issue that needs to be addressed.

[0034] In summary, the methods for assessing the difficulty of retrieving relevant separation instruments have the following shortcomings: First, it is highly subjective and lacks objective standards: the results of relevant assessment methods are highly dependent on the doctor's personal experience and skill level. Different doctors may have significant differences in their judgment of the difficulty of the same case, leading to inconsistent treatment options.

[0035] Second, the assessment is one-sided and cannot take a comprehensive view: Doctors usually only focus on one or two prominent factors (such as the curvature of the root canal), and it is difficult to simultaneously weigh the interaction of multiple factors such as instrument position, root canal wall thickness, and instrument material, resulting in an incomplete assessment and an inconsistency between the estimated difficulty and the actual operation difficulty.

[0036] Third, lack of proactive risk warning: It is impossible to systematically predict and warn of possible intraoperative complications (such as root canal perforation, secondary separation of instruments, instruments being pushed out of the apical foramen, etc.) before the operation, and doctors can only respond passively during the operation, which increases medical risks.

[0037] Fourth, lack of standardized decision support pathways: Due to the lack of quantitative difficulty grading, it is impossible to effectively link the difficulty of cases with the corresponding technical choices, surgeon qualification requirements, and referral recommendations, which is not conducive to the implementation of hierarchical diagnosis and treatment and the optimal allocation of medical resources.

[0038] Therefore, the assessment methods for the difficulty of removing related dissection instruments are mostly focused on the independent effect of a single influencing factor (such as root canal curvature), and a multi-factor integrated assessment system has not yet been formed. Although the relevant assessment system has screened out key indicators, it has not constructed an operable grading standard, nor has it formed a standardized tool in combination with actual clinical needs. It cannot provide a reliable basis for tiered diagnosis and treatment, and clinicians lack objective data support when formulating treatment plans.

[0039] This invention provides a method for assessing the difficulty of retrieving endodontic instruments, relating to the fields of medical devices and clinical decision support systems. Specifically, it is applicable to the scientific assessment of the difficulty of instrument retrieval in endodontic clinical practice, assisting dentists in making more rational treatment decisions. This invention constructs a quantitative assessment model for the difficulty of endodontic instrument retrieval by analyzing and quantifying multiple factors, including root canal curvature, instrument depth, minimum root canal wall thickness at the fracture end, instrument length, tooth position, instrument material, and whether it extends beyond the apical foramen. Through retrospective construction and prospective validation, the difficulty of endodontic instrument retrieval is categorized into low, medium, and high levels. By incorporating warnings for individual risk values, it indicates the risk of clinical complications and provides reference clinical strategies for cases with corresponding retrieval difficulties.

[0040] According to an embodiment of the present invention, an embodiment of a method for assessing the difficulty of removing an intracanal dissection instrument is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0041] This embodiment provides a method for assessing the difficulty of retrieving endodontic instruments, which can be used with the aforementioned terminal equipment. Figure 2 This is a flowchart of a method for assessing the difficulty of removing endodontic dissection instruments according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps: Step S201: Obtain the original case data, perform continuous variable classification processing on the original case data, and obtain the separation instrument removal factor category.

[0042] Specifically, the original case data included: root canal curvature, dissection instrument depth, minimum root canal wall thickness at the cut end, dissection instrument length, tooth position, dissection instrument material, and whether it extended beyond the apical foramen. Root canal curvature was measured using cone-beam computed tomography (CBCT) images, in degrees (°). The dissection instrument depth was defined as the straight-line distance from the coronal edge of the dissection instrument cut end to the root canal orifice, measured using CBCT, in millimeters (mm). On the axial plane of the CBCT, the thickness of the thinnest point of the root canal wall at the location of the instrument cut end was precisely measured, i.e., the minimum root canal wall thickness at the cut end. The tube wall thickness is measured in millimeters (mm); the length of the dissecting instrument is the actual length of the dissecting instrument fragment itself, estimated by CBCT measurement, and measured in millimeters (mm); based on the anatomical location and complexity of the affected tooth, the tooth position is divided into three categories: anterior teeth; premolars and maxillary first molars; maxillary second molars and mandibular molars; based on treatment history or imaging characteristics, the dissecting instrument material is mainly divided into nickel-titanium instruments or stainless steel instruments; based on a comprehensive assessment of CBCT images, whether the instrument fragment has broken through the anatomical boundary of the apical foramen is a binary variable (yes / no).

[0043] Furthermore, through the human-computer interaction interface, the system receives raw case data input by the user, i.e., data input based on the graphical user interface, which includes a series of standardized input controls, such as: numeric input boxes for inputting values ​​such as "root canal curvature" and "depth", drop-down selection menus for selecting "tooth position" and "material", and checkboxes for selecting options such as "whether it exceeds the apical foramen", etc. The system then collects the data of the seven assessment factors input by the user, transforming the unstructured clinical description into structured data that can be processed by the engine.

[0044] Furthermore, the input data is processed and analyzed using the core processing engine (rule engine). As the computing and decision-making center of the system, the core processing engine is the intelligent core of the product and runs on the server or locally.

[0045] Step S202: Assign difficulty values ​​to the factors that determine the removal of dissecting instruments in the root canal, and determine the difficulty scoring table for removing dissecting instruments in the root canal.

[0046] Step S203: Obtain actual case data. Based on the actual case data, use the scoring table and grading threshold of the difficulty of removing the internal canal dissecting instrument to evaluate the difficulty of removing the internal canal dissecting instrument and obtain the evaluation result of the difficulty of removing the internal canal dissecting instrument.

[0047] Specifically, the decision support output module generates and presents a structured assessment report based on the assessment results of the difficulty in removing the dissecting instruments from the root canal.

[0048] Furthermore, the data flow during the assessment of the difficulty of removing instruments from the root canal is as follows: the user submits case information through the human-computer interaction interface, the case information is transmitted to the core processing engine for core calculation, the core processing engine sends the assessment result of the difficulty of removing instruments from the root canal to the decision support output module, and the decision support output module generates the final assessment report and returns it to the user.

[0049] Furthermore, an effectiveness analysis was performed on the assessment results of the difficulty in removing instruments from the root canal to obtain the true level of difficulty in removing instruments from the root canal.

[0050] Furthermore, a new "intrinsic difficulty" standard is defined to validate the effectiveness of the assessment of the difficulty of removing intracanal dissecting instruments: To objectively verify whether the assessment results of the difficulty of removing intracanal dissecting instruments truly reflect the complexity of the removal, a new validation standard independent of the predictive model is defined. This standard combines two core dimensions of intraoperative performance: Operational outcome: ultimately "successful removal" or "failure," and Operational efficiency and process complexity: measured by "operation time" and "treatment quality." Combining these two, three levels of "intrinsic difficulty" are defined through the following logic: Intrinsic - Low difficulty: Complete removal without pulp chamber wall perforation, operation time ≤ 45 minutes, and root canal morphology showing no significant change in the filling film. Intrinsic - Moderate difficulty: Complete removal without pulp chamber wall perforation, operation time > 45 minutes, and root canal morphology showing significant changes in the filling film (steps, excessively thin root canal walls, etc.). Intrinsic - High difficulty: Meets any of the following criteria: ① Not removed or not completely removed; ② Intraoperative pulp chamber wall perforation; ③ Operation time > 90 minutes.

[0051] Furthermore, the "predicted grade" (i.e., the difficulty level of removing the dissecting instrument from the root canal) of each case was compared with the "true grade": using receiver operating characteristic (ROC) curve analysis, the three-class problem was decomposed into two binary classification tasks: "high-level vs. non-high-level" and "low-level vs. non-low-level". ROC curves were plotted for each task, and the area under the curve (AUC) was calculated to evaluate the model's discriminative ability. An AUC value greater than 0.8 was considered to indicate that the model had good discriminative ability.

[0052] Furthermore, taking the binary classification task of "high difficulty vs. non-high difficulty" as an example, the calculation steps of the area under the curve are as follows: Sort the total difficulty of removing the endodontic instruments from all cases by total score from high to low, iterate through each possible threshold (taking the total score of each sample as the threshold), and for each threshold, calculate the True Positive Rate (TPR) and False Positive Rate (FPR); where, True Positive Rate = Number of samples correctly predicted as high difficulty / Total number of true high difficulty samples; False Positive Rate = Number of samples incorrectly predicted as high difficulty / Total number of true non-high difficulty samples; Plot an ROC curve with False Positive Rate on the x-axis and True Positive Rate on the y-axis, and sort the points on the ROC curve by False Positive Rate from small to large to obtain the point set:

[0053] in, , .

[0054] Therefore, the formula for calculating the area under the curve is as follows:

[0055] Furthermore, the precision, recall, and F1 score (an indicator used to evaluate the performance of binary classification models) for each prediction level are calculated to comprehensively evaluate classification performance and ultimately construct an accurate and effective preoperative assessment and decision support system for the difficulty of removing endodontic instruments.

[0056] This embodiment provides a method for assessing the difficulty of removing endodontic instruments. By performing continuous variable grading on the original case data, it systematically integrates multi-dimensional key factors affecting the difficulty of removing endodontic instruments, assigns difficulty values ​​to the categories of instrument removal factors, and establishes a scoring table for the difficulty of removing endodontic instruments. This solidifies clinical experience into quantifiable scoring rules, eliminating subjectivity and arbitrariness in the assessment process. It ensures high consistency and repeatability of assessment results from different doctors for the same case. By using the scoring table and grading thresholds to assess the difficulty of removing endodontic instruments, it achieves an objective and quantitative assessment of the difficulty of removing endodontic instruments. This allows the preoperative assessment to more realistically reflect the actual complexity of the intraoperative situation, resulting in a more comprehensive and accurate assessment of the difficulty of removing endodontic instruments.

[0057] This embodiment provides a method for assessing the difficulty of retrieving endodontic instruments, which can be used with the aforementioned terminal equipment. Figure 3 This is a flowchart of a method for assessing the difficulty of removing endodontic dissection instruments according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps: Step S301: Obtain the original case data, perform continuous variable classification processing on the original case data, and obtain the separation instrument removal factor category.

[0058] Specifically, step S301 includes: Step S3011: Perform distribution analysis on the continuous variables in the original case data to obtain the distribution curve of the continuous variables; among which, the continuous variables include root canal curvature, dissection instrument depth, minimum root canal wall thickness at the cut end, and dissection instrument length.

[0059] Specifically, a distribution analysis was performed on each continuous variable (root canal curvature, dissection instrument depth, minimum root canal wall thickness at the cut end, and dissection instrument length) in the original case data. That is, using the original observation data of the continuous variables as the object, the minimum and maximum values ​​were used to determine the range of the horizontal axis of the histogram, and the interquartile range and standard deviation were combined to determine the reasonable grouping and group interval. The frequency of data in each interval was counted and a frequency distribution histogram was drawn with the interval as the horizontal axis and the frequency as the vertical axis. At the same time, the distribution pattern was labeled and verified by indicators such as mean, median, skewness, and kurtosis, and a kernel density estimation curve was superimposed to achieve a visual display of the data distribution.

[0060] In some optional implementations, step S3011 above includes: Step a1: Calculate descriptive statistics for continuous variables to obtain statistical indicators.

[0061] Specifically, the following statistical indicators are automatically calculated for each continuous variable: central tendency: mean, median; dispersion: standard deviation, variance, interquartile range (IQR); extreme values: minimum, maximum; distribution shape: skewness and kurtosis.

[0062] Furthermore, by comparing the mean and median, we can initially determine whether the data is skewed. Skewness and kurtosis quantify the asymmetry and steepness of the distribution, providing a reference for subsequent selection of threshold optimization methods.

[0063] Step a2: Draw a frequency distribution histogram based on continuous variables and statistical indicators.

[0064] Specifically, using all the original observations of a single continuous variable as the analysis data, the range of values ​​on the horizontal axis is determined based on the minimum and maximum values ​​of the continuous variable (the minimum value is used as the starting point of the horizontal axis of the histogram, and the maximum value is used as the ending point of the horizontal axis). Combining the sample size, interquartile range, standard deviation, and other dispersion indicators of the original observations of the continuous variable, the above extreme value intervals are divided into several equal-width, continuous, and non-overlapping group intervals. The number of observations falling into each interval is counted, i.e., the frequency of that group. Adjacent rectangular bars are drawn with the group intervals as the horizontal axis and the frequency as the vertical axis, with the width of the rectangle being the group interval and the height being the corresponding frequency, forming a frequency distribution histogram.

[0065] Furthermore, the mean, median, and quartiles are marked on the frequency distribution histogram to intuitively reflect the central tendency and dispersion characteristics. At the same time, the shape of the graph is corroborated with skewness and kurtosis. That is, when the skewness is ≈0, the graph is approximately symmetrical; when the skewness is ≠0, the graph is left-skewed or right-skewed. Kurtosis reflects whether the distribution is steep or flat, thus achieving unified verification of quantitative statistical indicators and visual distribution.

[0066] Step a3: Overlay the kernel density curve onto the frequency distribution histogram to obtain the distribution curve of the continuous variable.

[0067] Specifically, by overlaying a kernel density curve onto the frequency distribution histogram, the distribution pattern (such as symmetrical, left-skewed, right-skewed, bimodal, etc.) can be intuitively determined, providing important clues for subsequent threshold selection.

[0068] Furthermore, using all the original values ​​of continuous variables as the base data, for each data point, a smooth distribution is generated using a kernel function (such as the Gaussian kernel function) centered on it. The kernel functions corresponding to all data points are superimposed, summed, and normalized to obtain a smooth density curve covering the entire numerical range, namely the kernel density curve. The kernel density curve is then superimposed on the frequency distribution histogram to further smooth out the data distribution pattern.

[0069] Step S3012: Using the distribution curve of the continuous variable, perform threshold optimization calculation on the continuous variable to obtain the optimal cutoff value.

[0070] Specifically, for each continuous variable to be classified, it is used as the test variable, and the "success / failure" result is used as the state variable. Statistical methods such as receiver operating characteristic curve analysis are used to calculate one or more optimal cutoff values ​​that can best distinguish between success and failure.

[0071] Furthermore, using the continuous variable to be graded (such as root canal curvature, dissection instrument depth, etc.) as the test variable, and "successful / failed retrieval" as the binary classification state variable; based on the frequency distribution histogram and kernel density estimation curve (i.e., the continuous variable distribution curve) of the continuous variable, the data distribution pattern is observed: if it is a unimodal distribution, a single threshold is used for grading; if it is a bimodal or multimodal distribution, multiple cutoff values ​​are used to achieve multi-level division; at the same time, the approximate range of the threshold value is preliminarily predicted by combining the clustering areas and boundary points of the curve; different values ​​of the test variable are used as candidate cutoff values, and the corresponding sensitivity and specificity are calculated respectively; then, the receiver operating characteristic curve is plotted and the area under the curve is calculated to evaluate the ability of the continuous variable to distinguish the outcome; the Youden index (sensitivity + specificity) is used. 1) Using the maximum as the criterion, search for and determine the optimal cutoff value so that the threshold can distinguish between the two outcomes of success and failure to the greatest extent.

[0072] Furthermore, the optimal cutoff value obtained from the receiver operating characteristic curve analysis was plotted on the frequency distribution histogram and kernel density estimation curve to verify whether the cutoff value was located at a position where the data distribution was clearly demarcated and the differences between groups were significant.

[0073] Step S3013: Use the optimal cutoff value to classify the continuous variables to obtain the separation device extraction factor category.

[0074] Specifically, based on the calculated optimal cutoff value, each continuous variable is transformed into a categorical variable with clinical predictive significance, and this categorical variable is used as the factor category for the separation device.

[0075] Furthermore, the specific segmentation thresholds are set as follows: root canal curvature is divided into five segments: 0-10°, 11-20°, 21-30°, 31-40°, and >40°; dissection instrument depth is divided into three segments: 0-4 mm, 4.1-10 mm, and >10 mm; minimum root canal wall thickness at the fracture end is divided into three segments: 0-0.5 mm, 0.6-0.9 mm, and ≥1.0 mm; and dissection instrument length is divided into two segments: 0-5 mm and >5 mm.

[0076] Step S302: Assign difficulty values ​​to the factors affecting the removal of dissecting instruments, and determine the difficulty scoring table for removing dissecting instruments from the root canal. For details, please refer to [link to relevant documentation]. Figure 2 Step S202 of the illustrated embodiment will not be described again here.

[0077] Step S303: Obtain actual case data. Based on the actual case data, assess the difficulty of removing the internal canal dissecting instruments using a scoring table and grading thresholds, and obtain the assessment result of the difficulty of removing the internal canal dissecting instruments. For details, please refer to... Figure 2 Step S203 of the illustrated embodiment will not be described again here.

[0078] This embodiment provides a method for assessing the difficulty of removing endodontic instruments. It performs distribution analysis on continuous variables in the original case data to avoid bias caused by subjective experience grouping, resulting in more objective and reliable results. By optimizing the threshold to determine the optimal cutoff value, the ability of continuous variables to distinguish and predict results can be maximized. Furthermore, the optimal cutoff value is used to classify continuous variables, scientifically transforming them into categorical variables. This preserves data information and facilitates clinical understanding and practical application, laying the foundation for subsequent objective quantitative assessment of the difficulty of removing endodontic instruments.

[0079] This embodiment provides a method for assessing the difficulty of retrieving endodontic instruments, which can be used with the aforementioned terminal equipment. Figure 4 This is a flowchart of a method for assessing the difficulty of removing endodontic dissection instruments according to an embodiment of the present invention, such as... Figure 4 As shown, the process includes the following steps: Step S401: Obtain the original case data, perform continuous variable classification processing on the original case data, and obtain the factor categories for dissection instrument removal. For details, please refer to [link to relevant documentation]. Figure 3 Step S301 of the illustrated embodiment will not be described again here.

[0080] Step S402: Assign difficulty values ​​to the factors that determine the removal of dissecting instruments in the root canal, and determine the difficulty scoring table for removing dissecting instruments in the root canal.

[0081] Specifically, step S402 includes: Step S4021: Obtain the historical case dataset corresponding to the factor category extracted by the separation instrument.

[0082] Specifically, the historical case dataset includes root canal curvature, dissection instrument depth, minimum root canal wall thickness at the cut end, dissection instrument length, tooth position, dissection instrument material and whether it extends beyond the apical foramen, and the final "successful / failed" result.

[0083] Step S4022: Using the category of separation instrument removal factor in the historical case dataset as the independent variable and the separation instrument removal result as the dependent variable, a regression analysis model is used to fit the data to obtain the regression coefficients corresponding to the separation instrument removal factor category.

[0084] Specifically, with "successful / failed retrieval" as the dependent variable and the retrieval factor category of the separation device as the independent variable, a binary logistic regression analysis (a generalized linear regression analysis model) was used for fitting. This model outputs the regression coefficient of each independent variable (i.e., each category of each factor), which statistically quantifies the degree of independent contribution of that particular category relative to the reference category to the risk of "retrieval failure".

[0085] Step S4023: Map the regression coefficients to the difficulty score of removing the dissecting instruments from the root canal.

[0086] Specifically, the calculated regression coefficients are standardized through linear transformation and rounding, and mapped to a set of difficulty scores that are easy to remember and use clinically. For example, the category with the largest regression coefficient (i.e. the highest risk) (such as "dissection instrument depth > 10 mm") is assigned the highest score (e.g., 31 points), and the category with the lowest risk (such as "bending degree 0-10°") is assigned 0 points. Finally, a scoring table for the difficulty of removing dissection instruments in the root canal is established, which clearly specifies the unique score corresponding to each factor under each specific category.

[0087] Step S4024: Establish a scoring table for the difficulty of removing instruments from the root canal based on the category of instrument removal factors and the difficulty score of removing instruments from the root canal.

[0088] Specifically, the difficulty scoring table for removing instruments from the root canal defines the difficulty scores corresponding to different levels of each assessment factor.

[0089] For example, the scoring table for the difficulty of removing instruments from the root canal is shown in Table 1 below.

[0090] Table 1. Scoring Table for Difficulty of Removing Dissecting Instruments from Root Canals:

[0091] Step S403: Obtain actual case data. Based on the actual case data, assess the difficulty of removing the internal canal dissecting instruments using a scoring table and grading thresholds, and obtain the assessment result of the difficulty of removing the internal canal dissecting instruments. For details, please refer to... Figure 3 Step S303 of the illustrated embodiment will not be described again here.

[0092] This embodiment provides a method for assessing the difficulty of removing endodontic instruments. By using regression analysis to quantify the true correlation between various influencing factors and the removal outcome, it avoids the subjectivity and bias caused by relying solely on experience to formulate scoring standards, making the assessment results more clinically authentic and scientific. Furthermore, by using regression coefficients, it transforms the complex multi-factor influences into an intuitive, calculable, and clinically applicable difficulty scoring system, facilitating rapid assessment by clinicians, preoperative prediction, and teaching promotion, and providing a reliable basis for preoperative risk assessment.

[0093] This embodiment provides a method for assessing the difficulty of retrieving endodontic instruments, which can be used with the aforementioned terminal equipment. Figure 5 This is a flowchart of a method for assessing the difficulty of removing endodontic dissection instruments according to an embodiment of the present invention, such as... Figure 5 As shown, the process includes the following steps: Step S501: Obtain the original case data, perform continuous variable classification processing on the original case data, and obtain the factor categories for dissection instrument removal. For details, please refer to [link to relevant documentation]. Figure 4 Step S401 of the illustrated embodiment will not be described again here.

[0094] Step S502: Assign difficulty values ​​to the factors affecting the removal of dissecting instruments, and determine the difficulty scoring table for removing dissecting instruments from the root canal. For details, please refer to [link to relevant documentation]. Figure 4 Step S402 of the illustrated embodiment will not be described again here.

[0095] Step S503: Obtain actual case data. Based on the actual case data, use the scoring table and grading threshold of the difficulty of removing the internal canal dissecting instrument to evaluate the difficulty of removing the internal canal dissecting instrument and obtain the evaluation result of the difficulty of removing the internal canal dissecting instrument.

[0096] Specifically, step S503 includes: Step S5031: Match the measured case data with the scoring table for the difficulty of removing instruments from the root canal to obtain the total score for the difficulty of removing instruments from the root canal.

[0097] Specifically, for the above-mentioned actual case data, based on the specific measured values ​​or categories of each factor, the scoring table for the difficulty of removing the dissecting instruments in the root canal is consulted to obtain the score for each item. The scores of all seven factors are then summed algebraically using an adder to obtain the total score for the difficulty of removing the dissecting instruments in the root canal for that case.

[0098] Step S5032: Obtain the grading threshold. Compare the total score of the difficulty in removing the dissecting instrument from the root canal with the grading threshold to obtain the difficulty level of removing the dissecting instrument from the root canal.

[0099] Specifically, based on statistical analysis of the total score distribution of a large number of historical cases (such as normal distribution), two fixed grading thresholds are set to divide the continuous total score into three ordered intervals, corresponding to three preoperative predicted difficulty levels (i.e., difficulty levels of removing dissecting instruments from the root canal): Furthermore, the threshold comparator compares the total difficulty score of removing instruments from the root canal with preset grading thresholds (such as constant threshold A and constant threshold B), and outputs a three-level difficulty classification: "low", "medium", and "high": predicted as low difficulty: total difficulty score of removing instruments from the root canal < 9.5; predicted as medium difficulty: 9.5 ≤ total difficulty score of removing instruments from the root canal ≤ 36.5; predicted as high difficulty: total difficulty score of removing instruments from the root canal > 36.5.

[0100] Step S5033: Based on the difficulty level of removing the dissecting instruments from the root canal, determine the dissecting instrument removal operation strategy text using the clinical strategy knowledge base.

[0101] Specifically, the abstract total score and difficulty level of removing instruments from the root canal are transformed into intuitive and actionable clinical decision support information.

[0102] Furthermore, the clinical strategy knowledge base stores corresponding clinical operation strategy texts (i.e., instrument removal operation strategy texts) indexed by "difficulty level" and "key risk factors". Then, based on the difficulty level and risk factors of removing instruments from the root canal, the corresponding strategy texts are retrieved and called from the clinical strategy knowledge base.

[0103] Furthermore, the clinical strategy knowledge base stores specific rules and their binding relationship with difficulty levels. The specific rules are as follows: Low difficulty: Clinical recommendation: It is recommended that the operator be a licensed dentist or endodontist who has received training in endodontics.

[0104] Medium difficulty: Clinical recommendation: It is recommended that the operator be a physician with 3 or more years of experience in removing dissecting instruments, or who has removed more than 50 instruments.

[0105] Advanced Difficulty: Clinical Recommendation: Prioritize alternative treatments and avoid attempting removal unless absolutely necessary. If removal of the dissecting device is required, it is strongly recommended that the operator be a physician with 5 or more years of experience in removing dissecting devices, or with more than 100 such cases.

[0106] Furthermore, the specific rules in the clinical strategy knowledge base and their binding relationships with risk factors are as follows: Risk warning when the length of the dissection instrument is greater than 5mm and it is a nickel-titanium instrument: Secondary dissection risk: The case has a high risk of secondary dissection (factor: the dissection instrument is long and made of nickel-titanium material). Suggestion: Mechanical removal methods such as slings / cannulas should be preferred; if ultrasound is used, be sure to use a low power and intermittent oscillation mode.

[0107] Risk warning when the root canal wall thickness is less than 0.5mm: Perforation risk: The root wall of the case is thin, and the risk of perforation is high (factor: the root canal wall thickness is too thin). Tip: Cutting should be avoided as much as possible in thin root canal walls; if cutting is necessary, a fine working tip should be selected, and the cutting should be precise and minimal to reduce the risk of perforation.

[0108] Risk warning when the dissecting instrument extends beyond the apical foramen: Risk of dissecting instrument being pushed out of the apex: There is a risk that the dissecting instrument may be further or completely pushed out of the apex. Note: Throughout the procedure, the positional relationship between the retrieval device and the dissecting instrument must be clearly identified to avoid blind operation; simultaneously, the patient should be informed of this risk before the procedure, and informed consent obtained.

[0109] Step S5034: Determine the assessment result of the difficulty of removing the internal canal dissecting instrument based on the total score of the difficulty of removing the internal canal dissecting instrument, the difficulty level of removing the internal canal dissecting instrument, and the text of the dissecting instrument removal operation strategy.

[0110] Specifically, the assessment results of the difficulty of removing instruments from the root canal include the specific scores of each factor, the total score of the difficulty of removing instruments from the root canal, the difficulty level of removing instruments from the root canal, risk warnings, and clinical recommendations.

[0111] Furthermore, for cases requiring evaluation, after obtaining information through CBCT and medical history, the seven evaluation factors for the target case are fully filled in or selected. Clicking on the case for evaluation sends the input data to the core processing engine, which sequentially executes: scoring query → total score calculation and grading → strategy retrieval. Ultimately, the difficulty level of removing the dissecting instrument from the root canal and the corresponding dissecting instrument removal operation strategy text are obtained. The evaluation results of the difficulty of removing the dissecting instrument from the root canal are filled into the template, and a structured evaluation report is generated instantly and displayed to the user, providing a quantitative basis for their preoperative decision-making.

[0112] Furthermore, the decision support output module is a software report generator. This module receives the "scores of each factor", "total score", "difficulty level" and "clinical strategy text" from the core processing engine, automatically fills them into a predefined report template, generates a complete "Preoperative Assessment Report for Removal of Intracanal Dissection Instruments", and presents it to the user (displayed on the screen or generated as a PDF file).

[0113] This embodiment provides a method for assessing the difficulty of removing intracanal dissecting instruments. It utilizes a scoring table to assess the difficulty of instrument removal, achieving an objective and quantitative evaluation. A grading threshold is used to classify the total difficulty score, ensuring consistent, comparable, and repeatable assessment standards across different doctors and cases, thus improving the standardization and reliability of the assessment results. Based on the difficulty levels, a clinical strategy knowledge base is used to define the instrument removal operation strategy text, linking the difficulty level to a clear clinical operation path. This provides a scientific basis for implementing tiered medical services, helps optimize resource allocation, and improves overall medical quality and safety. Furthermore, the clinical strategy knowledge base can accurately identify and alert potential complication risks preoperatively, enabling doctors to prepare contingency plans in advance, choose safer technical approaches, and shift from passive response to proactive management, providing forward-looking risk warnings.

[0114] The following specific embodiment illustrates the steps of a method for assessing the difficulty of removing endodontic instruments.

[0115] Example 1: A method for assessing the difficulty of removing endodontic instruments is applied to a software system for assessing the difficulty of removing endodontic instruments. Its core logic follows a data flow of "input-processing-output", forming a complete decision support closed loop.

[0116] The logical structure of the software system for assessing the difficulty of removing instruments from the root canal is as follows: (1) Data input module: Provides a human-computer interaction interface to receive the original case data input by the user. The data input module is based on a graphical user interface and includes a series of standardized input controls, such as: a numeric input box for inputting values ​​such as "root canal curvature" and "depth"; a drop-down selection menu for selecting "tooth position" and "material"; and a checkbox for selecting options such as "whether it exceeds the apical foramen".

[0117] Its core function is to collect data on seven assessment factors input by the user and transform unstructured clinical descriptions into structured data that can be processed by the engine.

[0118] For example, the case parameter input data includes: tooth position: maxillary second molar and mandibular molar; instrument material: nickel-titanium instrument; minimum root canal wall thickness at the fracture end: 0.4; root canal curvature: 31; instrument length: 6; instrument depth: 7; whether it exceeds the apical foramen: no.

[0119] (2) Core processing engine (rule engine): As the calculation and decision-making center of the system, it processes and analyzes the input data.

[0120] The core processing engine is the intelligent core of the product, running on a server or locally, and contains three sequentially executed sub-units: The scoring query subunit has the following function: it embeds a static "Difficulty Scoring Table for Removing Intracanal Dissection Instruments," which defines the difficulty scores corresponding to different levels of various assessment factors. This unit queries this table based on the input data and returns the scores for each factor; the specific scoring content of this scoring table is new data reflecting the clinical difficulty level.

[0121] The total score calculation and classification subunit includes an adder and a threshold comparator. The adder sums the scores of all factors to obtain the "total difficulty score". The threshold comparator compares the total score with preset constant thresholds (such as threshold A and threshold B) and outputs a three-level difficulty classification of "low", "medium" and "high". The specific threshold parameters set (such as 9.5, 36.5, etc.) are new designs based on specific statistical analysis.

[0122] The risk assessment and strategy mapping subunit contains a clinical strategy knowledge base. This knowledge base is indexed by "difficulty level" and "key risk factors" and stores the corresponding clinical operation strategy texts. This unit retrieves and calls the corresponding strategy content from the knowledge base according to the classification results. The knowledge base stores specific rule content and its binding relationship with difficulty level and risk factors.

[0123] (3) Decision support output module: Based on the processing results, generate and present a structured evaluation report.

[0124] The decision support output module is a software report generator. It outputs "scores for each factor", "total score", "difficulty level" and "clinical strategy text", which are automatically filled into a predefined report template to generate a complete "Preoperative Assessment Report for Removal of Intracanal Dissection Instruments" and presented to the user (either displayed on screen or generated as a PDF file).

[0125] The preoperative assessment report for removal of endodontic instruments includes: Specific scores for each factor: Tooth position: 1 point; Dissection instrument material: 2.5 points; Minimum root canal wall thickness at the fracture end: 0 points; Root canal curvature: 19 points; Dissection instrument length: 12.5 points; Dissection instrument depth: 16.5 points; Whether it exceeds the apical foramen: 0 points.

[0126] Total difficulty score and difficulty level: The total difficulty score is 51.5 points, and the difficulty level of removing the dissecting instruments from the root canal is high. The difficulty level of removing the dissecting instruments from the root canal can also be visualized.

[0127] Clinical strategy text: Risk Warnings: ① Risk of Secondary Separation: The case has a high risk of secondary separation (factor: long separation instrument made of nickel-titanium material). Recommendation: Mechanical removal methods such as slings / cannulas should be preferred; if ultrasonic methods are used, be sure to use low power and intermittent oscillation mode; ② Risk of Perforation: The root wall of the case is thin, with a high risk of perforation (factor: root canal wall thickness is too thin). Recommendation: Cutting should be avoided as much as possible in thin root canal walls; if cutting is necessary, a fine working tip should be used for precise positioning and minimal cutting to reduce the risk of perforation.

[0128] Clinical recommendations: Prioritize alternative treatments and avoid attempting removal unless absolutely necessary. If removal of the dissecting device is necessary, it is strongly recommended that the operator be a physician with 5 or more years of experience in removing dissecting devices, or with more than 100 cases of such removal.

[0129] This embodiment also provides a device for assessing the difficulty of removing endovascular instruments. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0130] This embodiment provides a device for assessing the difficulty of removing endodontic instruments, such as... Figure 6 As shown, it includes: The hierarchical processing module 601 is used to acquire the original case data, perform continuous variable hierarchical processing on the original case data, and obtain the separation instrument removal factor category. The assignment module 602 is used to assign difficulty values ​​to the factors of instrument retrieval and to determine the difficulty scoring table for instrument retrieval in the root canal. The assessment module 603 is used to acquire actual case data. Based on the actual case data, the difficulty of removing the internal dissecting instruments is assessed using a scoring table and grading thresholds, and the assessment result of the difficulty of removing the internal dissecting instruments is obtained.

[0131] In some alternative implementations, the hierarchical processing module 601 includes: The distribution analysis unit is used to perform distribution analysis on continuous variables in the original case data to obtain the distribution curves of continuous variables; among them, continuous variables include root canal curvature, dissection instrument depth, minimum root canal wall thickness at the cut end, and dissection instrument length; The calculation unit is used to perform threshold optimization calculations on continuous variables using the distribution curve of the continuous variable to obtain the optimal cutoff value; The grading unit is used to categorize continuous variables using the optimal cutoff value to obtain the factor categories for separation instruments.

[0132] In some optional implementations, the distribution analysis unit includes: The calculation subunit is used to calculate descriptive statistics for continuous variables and obtain statistical indicators; Draw sub-cells to create frequency distribution histograms based on continuous variables and statistical indicators; The superposition subunit is used to superimpose kernel density curves onto the frequency distribution histogram to obtain the distribution curve of the continuous variable.

[0133] In some alternative implementations, the assignment module 602 includes: The acquisition unit is used to acquire historical case datasets corresponding to the factor categories removed by the separation instruments. The fitting unit is used to fit the separation instrument removal factor category in the historical case dataset as the independent variable and the separation instrument removal result as the dependent variable, and to obtain the regression coefficients corresponding to the separation instrument removal factor category by using a regression analysis model. The mapping unit is used to map regression coefficients to scores indicating the difficulty of removing instruments from the root canal. A unit is established to create a scoring table for the difficulty of removing instruments from the root canal, based on the category of instrument removal factors and the difficulty score of removing instruments from the root canal.

[0134] In some alternative implementations, the evaluation module 603 includes: The matching unit is used to match the measured case data with the scoring table for the difficulty of removing instruments from the root canal to obtain the total score for the difficulty of removing instruments from the root canal. The comparison unit is used to obtain the grading threshold. It compares the total score of the difficulty of removing the dissecting instrument in the root canal with the grading threshold to obtain the difficulty level of removing the dissecting instrument in the root canal. The first determining unit is used to determine the operation strategy text for removing the dissecting instruments based on the difficulty level of removing the dissecting instruments from the root canal using a clinical strategy knowledge base. The second determining unit is used to determine the assessment result of the difficulty of removing the internal canal dissecting instrument based on the total score of the difficulty of removing the internal canal dissecting instrument, the difficulty level of removing the internal canal dissecting instrument, and the text of the dissecting instrument removal operation strategy.

[0135] In some alternative implementations, it also includes: The efficacy analysis module is used to perform efficacy analysis on the assessment results of the difficulty of removing instruments from the root canal, and to obtain the true level of difficulty of removing instruments from the root canal.

[0136] The root canal dissection instrument removal difficulty assessment device provided in this embodiment of the invention can execute the root canal dissection instrument removal difficulty assessment method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0137] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0138] The following is a detailed reference. Figure 7This diagram illustrates a suitable structural schematic for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor 701, such as a central processing unit (CPU), a graphics processing unit (GPU), etc., which can perform various appropriate actions and processes based on programs stored in ROM 702 (read-only memory) or programs loaded from memory 708 into RAM 703 (random access memory). RAM 703 also stores various programs and data required for the operation of the electronic device. The processor 701, ROM 702, and RAM 703 are interconnected via bus 704. An input / output (I / O) interface 705 is also connected to bus 704.

[0139] Typically, the following devices can be connected to I / O interface 705: input devices 706 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 707 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 708 including, for example, magnetic tapes, hard disks, etc.; and communication devices 709. Communication device 709 allows electronic devices to exchange data via wireless or wired communication with other devices. Although Figure 7 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0140] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 709, or installed from a memory 708, or installed from a ROM 702. When the computer program is executed by the processor 701, it performs the functions defined in the method for assessing the difficulty of retrieval of an intracanal dissecting instrument according to embodiments of the present invention.

[0141] Figure 7 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0142] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, it implements the method for assessing the difficulty of removing endodontic instruments shown in the above embodiments.

[0143] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0144] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for assessing the difficulty of removing endodontic instruments, characterized in that, The method includes: Obtain the original case data, perform continuous variable classification processing on the original case data, and obtain the factor categories for the removal of separation instruments; Assign difficulty values ​​to the factors that facilitate the removal of the dissecting instruments, and determine the difficulty scoring table for removing dissecting instruments from the root canal; Obtain actual case data, and based on the actual case data, use the scoring table and grading threshold of the difficulty of removing the internal canal dissecting instrument to evaluate the difficulty of removing the internal canal dissecting instrument, and obtain the evaluation result of the difficulty of removing the internal canal dissecting instrument. The continuous variable hierarchical processing of the original case data yields the following categories of factors related to the removal of dissection instruments: Distribution analysis was performed on the continuous variables in the original case data to obtain the distribution curves of the continuous variables; wherein, the continuous variables include root canal curvature, dissection instrument depth, minimum root canal wall thickness at the cut end, and dissection instrument length; Using the distribution curve of the continuous variable, a threshold optimization calculation is performed on the continuous variable to obtain the optimal cutoff value; The continuous variables are classified using the optimal cutoff value to obtain the factor categories for the separation device.

2. The method according to claim 1, characterized in that, The distribution analysis of continuous variables in the original case data to obtain continuous variable distribution curves includes: Descriptive statistics are calculated for the continuous variables to obtain statistical indicators; Draw a frequency distribution histogram based on the continuous variables and the statistical indicators; The kernel density curve is superimposed on the frequency distribution histogram to obtain the distribution curve of the continuous variable.

3. The method according to claim 1, characterized in that, The process of assigning difficulty scores to the factors affecting the removal of the dissecting instruments, and determining the difficulty scoring table for removing dissecting instruments from the root canal, includes: Obtain the historical case dataset corresponding to the factor category extracted by the separation instrument; Using the category of separation instrument removal factor in the historical case dataset as the independent variable and the separation instrument removal result as the dependent variable, a regression analysis model is used to fit the regression coefficients corresponding to the category of separation instrument removal factor. The regression coefficients are mapped to scores indicating the difficulty of removing endodontic instruments. A scoring table for the difficulty of removing endodontic instruments is established based on the categories of factors for removing the instruments and the difficulty score for removing the instruments within the root canal.

4. The method according to claim 1, characterized in that, Based on the measured case data, the difficulty of removing the intracanal dissecting instrument is assessed using the scoring table and grading thresholds, resulting in an assessment of the difficulty of removing the intracanal dissecting instrument, including: The measured case data were matched with the scoring table for the difficulty of removing the endodontic dissecting instrument to obtain the total score for the difficulty of removing the endodontic dissecting instrument. The grading threshold is obtained, and the total score of the difficulty in removing the endocanal dissecting instrument is compared with the grading threshold to obtain the difficulty level of removing the endocanal dissecting instrument. Based on the difficulty level of removing the endodontic dissecting instrument, the text of the dissecting instrument removal operation strategy is determined using a clinical strategy knowledge base. The difficulty assessment result for removing the intracanal dissecting instrument is determined based on the total score of the difficulty of removing the intracanal dissecting instrument, the difficulty level of removing the intracanal dissecting instrument, and the text of the dissecting instrument removal operation strategy.

5. The method according to claim 1, characterized in that, Also includes: An effectiveness analysis was performed on the assessment results of the difficulty of removing the intracanal dissecting instruments to obtain the true level of difficulty in removing the intracanal dissecting instruments.

6. A device for assessing the difficulty of removing endodontic instruments, characterized in that, The device includes: The grading processing module is used to acquire the original case data, perform continuous variable grading processing on the original case data, and obtain the separation instrument removal factor category; The assignment module is used to assign difficulty values ​​to the factors of the removal of the dissecting instruments and to determine the difficulty scoring table for the removal of dissecting instruments in the root canal. The assessment module is used to acquire actual case data, and based on the actual case data, to assess the difficulty of removing the internal canal dissecting instruments using a scoring table and grading thresholds, thereby obtaining the assessment result of the difficulty of removing the internal canal dissecting instruments. The hierarchical processing module includes: The distribution analysis unit is used to perform distribution analysis on continuous variables in the original case data to obtain the distribution curves of continuous variables; among them, continuous variables include root canal curvature, dissection instrument depth, minimum root canal wall thickness at the cut end, and dissection instrument length; The calculation unit is used to perform threshold optimization calculations on continuous variables using the distribution curve of the continuous variable to obtain the optimal cutoff value; The grading unit is used to categorize continuous variables using the optimal cutoff value to obtain the factor categories for separation instruments.

7. An electronic device, characterized in that, include: The device includes a memory and a processor, which are interconnected and the memory stores computer instructions. The processor executes the computer instructions to perform the method for assessing the difficulty of removing endocanal dissecting instruments as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the method for assessing the difficulty of removing endocanal dissecting instruments as described in any one of claims 1 to 5.

9. A computer program product, characterized in that, Includes computer instructions for causing a computer to perform the method for assessing the difficulty of removing endodontic dissecting instruments as described in any one of claims 1 to 5.

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