A health assessment method and system for osteoporosis clinical data

Abstract

The present invention relates to the field of medical data processing technology, and specifically to a health assessment method and system for osteoporosis clinical data, including: collecting bone density, content data and metabolic index data of each major part of each patient; obtaining the bone state expression of each major part of each patient according to the difference in bone density distribution between each patient and other patients in each major part; obtaining the degree of physical fitness and the degree of health expression of living habits of each patient, and obtaining the comprehensive physical fitness of each patient; clustering the comprehensive physical fitness of all patients to obtain several patient groups, and forming a health assessment data set with the clinical data of patients in each patient group as a reference for similar cases. The present invention aims to reduce the error existing in health assessment based on clinical data and improve the accuracy of health assessment of osteoporosis clinical data.

Description

Technical Field

[0001] The present invention relates to the technical field of medical data processing, and in particular to a health assessment method and system for osteoporosis clinical data. Background Art

[0002] Osteoporosis is a common bone disease. In the medical field, health assessment of osteoporosis clinical data is of great significance. By analyzing osteoporosis clinical data, it can provide doctors with auxiliary reference opinions, which helps to improve the efficiency of doctors' analysis of different patient conditions.

[0003] Typically, clustering algorithms are used to process clinical data of osteoporosis patients to obtain group clusters with different degrees of osteoporosis. However, when traditional clustering is performed by analyzing the bone density data of patients, differences in human fitness and bone density in different parts of the body, as well as individual living habits and health conditions, can also affect the manifestation of osteoporosis, leading to inaccurate clustering results of bone density for different people after clustering, and errors in health assessments based on clinical data. Summary of the invention

[0004] The present invention provides a health assessment method and system for osteoporosis clinical data to solve the existing problems.

[0005] The health assessment method and system for osteoporosis clinical data of the present invention adopts the following technical solutions:

[0006] An embodiment of the present invention provides a health assessment method for osteoporosis clinical data, the method comprising the following steps:

[0007] Collect bone density, content data and metabolic index data of each major part of each patient;

[0008] According to the difference of bone density distribution between each patient and other patients in each major part, the bone status expression of each major part of each patient is obtained;

[0009] Obtain the degree of physical fitness of each patient based on the consistency of the bone status of all major parts of each patient;

[0010] According to the similarity between each content data of each patient and the corresponding metabolic index data and the distribution deviation in all the respective data, the health performance of each patient's living habits is obtained;

[0011] Combine the physical condition of each patient and the health performance of their living habits to obtain the comprehensive physical condition of each patient;

[0012] The comprehensive physical fitness levels of all patients are clustered to obtain several patient groups, and the clinical data of patients in each patient group are used to form a health assessment data set as a reference for similar cases.

[0013] Furthermore, the specific steps for obtaining the bone status expression of each major part of each patient are as follows:

[0014] No. The patient's The calculation formula for the expression of the bone status of each major part is:

[0015] ;

[0016] in, Indicates The patient's The expression of bone status in each major part; Indicates The patient's Bone density in major areas; Indicates The patient's The density of bones in each major part; Indicates The patient's Consistency in the number of patients with bone density within the threshold range at each major site; Represents a linear normalization function that normalizes the data value to Within the range.

[0017] Furthermore, the specific steps for obtaining the bone density are as follows:

[0018] The first The patient's The sum of the number of people who fluctuate upward and the number of people who fluctuate downward in the main parts is recorded as The patient's The density of bones in the main parts of the body.

[0019] Furthermore, the specific steps for obtaining the upward fluctuation number and the downward fluctuation number are as follows:

[0020] Get the The bone density of each patient is The first patient of the patient other than The bone density difference of the main parts is set to be less than or equal to the absolute value of the bone density difference The number of patients whose bone density fluctuation thresholds of the first major parts of the body are greater than 0 is recorded as the number of patients with upward fluctuations, and the absolute value of the bone density difference is less than or equal to the preset first The number of patients whose bone density fluctuation thresholds of the main parts of the body and whose difference was less than or equal to 0 was recorded as the number of downward fluctuations.

[0021] Furthermore, the The patient's The specific steps to obtain the consistency of the number of patients with bone density within the threshold range in each major part are as follows:

[0022] The first The patient's The difference between the ratio of the number of people with upward fluctuations to the number of people with downward fluctuations in the first major part and 1 is recorded as The patient's There was agreement on the number of patients with bone density within the threshold range at each major site.

[0023] Furthermore, the specific steps for obtaining the physical condition of each patient are as follows:

[0024] No. The specific calculation method for the degree of physical fitness of a patient is:

[0025] ;

[0026] in, Indicates The patient's physical condition; Indicates The average value of the bone status expression of all major parts of each patient; Indicates The consistency of bone status expression among patients.

[0027] Furthermore, the specific steps for obtaining the consistency of the bone state expression are as follows:

[0028] The standard deviation of the skeletal status expression of all body parts of each patient was normalized. The normalized result of the standard deviation of the bone status expression of all body parts of the patient is recorded as The consistency of bone status expression among patients.

[0029] Furthermore, the specific steps for obtaining the health performance of each patient's living habits are as follows:

[0030] No. The calculation method of the health performance of a patient's lifestyle habits is:

[0031] ;

[0032] in, Indicates The health performance of each patient's lifestyle habits; Indicates the quantity of content data; Indicates The content data of each patient The content of the data; Indicates the maximum value of the content of all data in the content data; Indicates the number of metabolic index data; Indicates The metabolic index data of each patient The distribution deviation of the data is obtained by: The metabolic index data of each patient The difference between the metabolic index of the data and the minimum value of the metabolic index of all data in the metabolic index data, and The maximum value of all the data in the metabolic index data of the patient is The metabolic index data of each patient The ratio of the difference between the data is recorded as the The metabolic index data of each patient The distribution bias of the data; represents the absolute value function.

[0033] Furthermore, the specific steps for obtaining the comprehensive physical fitness level of each patient are as follows:

[0034] ;

[0035] in, Indicates The overall physical fitness of the patient; Indicates The patient's physical condition; Indicates The health performance of each patient's lifestyle habits; Indicates the preset threshold of health performance of living habits; Represents the preset hyperparameters; represents the absolute value function.

[0036] The present invention also proposes a health assessment system for osteoporosis clinical data, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program stored in the memory to implement the steps of the aforementioned health assessment method for osteoporosis clinical data.

[0037] The beneficial effects of the technical solution of the present invention are: collecting bone density, content data and metabolic index data of each major part of each patient, and obtaining the bone state expression of each major part of each patient according to the difference in bone density distribution between each patient and other patients in each major part. The level of bone state expression reflects the health status of the bones, and the higher the bone state expression means the healthier the bones; according to the physical fitness condition and the health expression of living habits of each patient, the comprehensive physical fitness degree of each patient is obtained, and the comprehensive physical fitness degree of each patient is obtained by comprehensively considering the physical fitness condition and the health expression of living habits, so as to comprehensively evaluate the overall health level of the individual; clustering the comprehensive physical fitness degrees of all patients to obtain several patient group sets, and by clustering the comprehensive physical fitness degrees of all patients, the patients can be divided into different group sets, which is helpful to identify similar cases and provide reference for medical decision-making, and the clinical data of patients in each patient group are used to form a health assessment data set as a reference for similar cases, thereby improving the accuracy of health assessment of osteoporosis clinical data. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 The present invention is a flowchart of the steps of a health assessment method for osteoporosis clinical data. DETAILED DESCRIPTION

[0040] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of a health assessment method and system for osteoporosis clinical data proposed by the present invention, its specific implementation method, structure, characteristics and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0041] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0042] The following is a detailed description of a specific scheme of a health assessment method and system for osteoporosis clinical data provided by the present invention in conjunction with the accompanying drawings.

[0043] See also Figure 1 , which shows a flowchart of a health assessment method for osteoporosis clinical data provided by an embodiment of the present invention, the method comprising the following steps:

[0044] Step S001: Obtain bone density, content data and metabolic index data of each major part of an osteoporosis patient.

[0045] The content data and metabolic index data of each osteoporosis patient are obtained by retrieving the hospital case database, wherein the content data include serum calcium content data and serum vitamin D content data; the metabolic index data include calcium metabolic index data and vitamin D metabolic index data.

[0046] The bone density of each major part of the patient is obtained by dual-energy X-ray absorptiometry. The main parts of this embodiment are described by taking the lumbar spine, hip, and femur as examples.

[0047] Step S002: According to the difference in bone density distribution between each patient and other patients in each major part, the bone state expression of each major part of each patient is obtained.

[0048] It should be noted that whole-body bone density testing can evaluate the bone density of each major part of the human body, such as the lumbar spine, hip, and femur. Evaluating bone density helps to detect osteoporosis symptoms early. The human body's bone health is affected by many factors, such as age, exercise, and physical activity, which leads to differences in bone density in each major part of the human body. Generally, the greater the bone density, the greater the individual's activity, which makes the bones healthier. Therefore, the bone density of each major part is analyzed to determine its bone status expression. By sorting the bone density of each patient in the same part, and then comparing and analyzing the degree of bone status expression in the same part, it can reflect the bone health status of different patients. The degree of bone status expression reflects the health status of the bones, that is, the higher the bone status expression means the healthier the bones.

[0049] It should be further explained that when analyzing the bone density performance of each major part of each patient, it is necessary to compare it with the bone density performance of other patients in the same part. In order to determine this comparison, a bone density fluctuation threshold is pre-set for each major part. Due to the different conditions in different parts, low or high bone density is relatively rare in all patients. The bone density performance of most people tends to be in the middle state, that is, the corresponding numbers in the upper and lower ranges of their bone density are relatively consistent.

[0050] The preset first Bone density fluctuation thresholds at major sites , this is used as an example for description, and other values ​​may be set in other implementation modes, and this embodiment does not limit this.

[0051] For The patient's In all patients, the first Patients and except The first patient of the patient other than The bone density difference of the main parts is set to be less than or equal to the absolute value of the bone density difference The number of patients whose bone density fluctuation thresholds of the first major parts of the body are greater than 0 is recorded as the number of patients with upward fluctuations, and the absolute value of the bone density difference is less than or equal to the preset first The number of patients whose bone density fluctuation thresholds of the main parts and whose difference is less than or equal to 0 is recorded as the number of patients with downward fluctuations. The patient's The sum of the number of people who fluctuate upward and the number of people who fluctuate downward in the main parts is recorded as The patient's The density of bone density in the main parts of the body will be The patient's The difference between the ratio of the number of people with upward fluctuations to the number of people with downward fluctuations in the first major part and 1 is recorded as The patient's The number of patients with bone density within the threshold range at each major site was consistent. The patient's The specific calculation formula for the expression of the bone status of each major part is:

[0052] ;

[0053] in, Indicates The patient's The expression of bone status in each major part; Indicates The patient's Bone density in major areas; Indicates The patient's The density of bones in each major part; Indicates The patient's Consistency in the number of patients with bone density within the threshold range at each major site; Represents a linear normalization function that normalizes the data value to Within the range.

[0054] The larger the value, the The denser the bone density distribution in each major part, the more patients need to be analyzed. The greater the expression of the bone condition of each major part. Indicates The smaller the value, the stronger the consistency. The bone density of the main parts was within the normal range. It reflects the relationship between the density of bone density in specific major parts and the consistency of the number of patients within the upper and lower range of bone density fluctuations. When this ratio is close to 1, it means that the density of bone density and the consistency of the number of patients within the upper and lower range of bone density fluctuations are high, and the bone density fluctuations between patients are relatively consistent; when this ratio is far away from 1, it means that there is a large difference between the density of bone density and the consistency of the number of patients within the upper and lower range of bone density fluctuations.

[0055] At this point, the bone status expression of each major part of each patient is obtained.

[0056] Step S003: Obtain the physical fitness level of each patient based on the consistency of the bone status expression of all major parts of each patient.

[0057] It should be noted that based on the same part of the human body, the bone condition expression is analyzed among different patients. The higher the bone condition expression, the higher the bone health status. Based on the bone condition expression of each part, the physical fitness of each patient based on the bone condition can be determined. Because osteoporosis is usually a systemic bone disease, but it may show different degrees of lesions in different parts, the degree of physical fitness can be judged by the bone condition expression of all major parts of the patient.

[0058] Specifically, The specific calculation method for the degree of physical fitness of a patient is:

[0059] ;

[0060] in, Indicates The patient's physical condition; Indicates The average value of the bone status expression of all major parts of each patient; Indicates The consistency of the bone state expression of each patient is obtained by normalizing the standard deviation of the bone state expression of all body parts of each patient, The normalized result of the standard deviation of the bone status expression of all body parts of the patient is recorded as The consistency of bone status expression among patients.

[0061] Will As a benchmark, the consistency of bone status representation in all major parts was analyzed. Adjustments are made. When the average value of the bone status expression of all major parts of the patient is larger, it means that the patient participates in more exercise and the bones are relatively stronger. However, since osteoporosis is a systemic bone disease, different parts may show different degrees of lesions. Therefore, there are differences in the bone status expression of different parts. The more obvious the difference, the greater the impact of osteoporosis on the patient, and the lower the degree of physical fitness based on the bone status. To reflect the differences in bone status expression in different parts, the larger the standard deviation, the more significant the difference in bone status expression in each part. Assign a smaller weight, so Used to adjust the degree of physical fitness based on the consistency of bone condition expression.

[0062] Step S004: Obtain the health performance of each patient's living habits based on the similarity between each content data and the corresponding metabolic index data of each patient and the distribution deviation in all respective data.

[0063] It should be noted that the above process mainly evaluates the physical fitness of each patient based on the bone state according to bone density. However, calcium and vitamin D in the human body are important nutrients related to osteoporosis, and their content is crucial to the impact of bone state. The health of living habits will also directly affect the content of calcium and vitamin D in the body. Therefore, by analyzing the content of calcium and vitamin D in the human body, the health of the patient's living habits can be obtained.

[0064] It should be further explained that the serum calcium and serum vitamin D content data can only reflect the current blood status. Therefore, it is necessary to combine the metabolic index data of calcium and vitamin D to provide more comprehensive data to understand the metabolism and absorption of calcium and vitamin D by the human body.

[0065] Specifically, the distribution deviation of each metabolic index data is obtained according to the difference between the maximum and minimum values ​​of the metabolic index data and the collected metabolic index data, and the content data is weighted and corrected according to the distribution deviation as a weight to obtain the health performance of each patient's living habits. The calculation method of the health performance of a patient's lifestyle habits is:

[0066] ;

[0067] in, Indicates The health performance of each patient's lifestyle habits; Indicates the quantity of content data; Indicates The content data of each patient The content of the data; Indicates the maximum value of the content of all data in the content data; Indicates the number of metabolic index data; Indicates The metabolic index data of each patient The distribution deviation of the data is obtained by: The metabolic index data of each patient The difference between the metabolic index of the data and the minimum value of the metabolic index of all data in the metabolic index data, and The maximum value of all the data in the metabolic index data of the patient is The metabolic index data of each patient The ratio of the difference between the data is recorded as the The metabolic index data of each patient The distribution bias of the data; represents the absolute value function.

[0068] In the formula, the patient's serum calcium and serum vitamin D levels are analyzed and compared with the maximum values ​​of the normal range. Because the calcium content is floating, it can only reflect the human body's serum calcium and serum vitamin D levels in the current state. The closer the content is to the maximum value of the normal range, the more normal the human body's living habits and health performance are in the current state. However, it is impossible to determine the future state, so it is necessary to conduct a comprehensive analysis by analyzing the metabolic indicators of serum calcium and serum vitamin D. When conducting metabolic indicator analysis, its metabolic indicators usually need to be within the normal range. Unlike serum calcium and serum vitamin D, which are absorbed by the human body, any deviation of metabolic indicators from the normal range is an abnormal situation, so through and To conduct metabolic index data The normal or abnormal value to be judged of each data is analyzed. If the value is positive, it means that the metabolic index data is The data is normal; its value is negative, indicating that the metabolic index data is The data is abnormal.

[0069] At this point, the health performance of each patient's living habits is obtained.

[0070] Step S005: Acquire the comprehensive physical fitness of each patient by combining the physical fitness of each patient and the health performance of their living habits.

[0071] Through the above steps, we obtain the physical fitness condition and the health performance of living habits of each patient. Based on the physical fitness condition of each patient, we conduct an in-depth analysis and evaluate the patient's comprehensive physical fitness according to the health performance of living habits.

[0072] The threshold value of the healthy performance degree of living habits preset in this embodiment , the preset hyperparameters , this is used as an example for description, and other values ​​may be set in other implementation modes, and this embodiment does not limit this.

[0073] ;

[0074] in, Indicates The overall physical fitness of the patient; Indicates The patient's physical condition; Indicates The health performance of each patient's lifestyle habits; Indicates the preset threshold of health performance of living habits; Represents the preset hyperparameters; represents the absolute value function.

[0075] It indicates the ratio of the difference between the healthy expression of lifestyle habits and the threshold to its absolute value, which determines the direction of correction of the healthy expression of lifestyle habits; Indicates that the comprehensive physical fitness level is corrected according to the difference between the health performance of lifestyle habits and the threshold. If the health performance of lifestyle habits is greater than the threshold, the correction value is , indicating that the calcium and vitamin content related to osteoporosis is normal, so it can be adjusted to a larger value based on the degree of physical fitness; if the health performance of lifestyle habits is less than the threshold, the correction value is , indicating that it needs to be adjusted downward so that it can be appropriately adjusted according to the degree of physical fitness. Therefore, the patient's comprehensive physical fitness level can be adjusted according to the relationship between the patient's lifestyle health performance and the threshold, thereby creating a distinction between different patients.

[0076] At this point, the comprehensive physical fitness level of each patient is obtained.

[0077] Step S006: Cluster the comprehensive physical fitness levels of all patients to obtain several patient groups, and use the clinical data of the patients in each patient group to form a health assessment data set as a reference for similar cases.

[0078] Specifically, the number of clusters preset in this embodiment is , which is described as an example. Other implementations may be set to other values, which are not limited in this embodiment. The comprehensive physical fitness level of each patient is clustered by K-means clustering algorithm to obtain The invention provides a patient group cluster with a comprehensive physical fitness level, each cluster represents a group with similar or close osteoporosis-related data comprehensively considered from multiple angles, and the clinical data of the patients in each patient group cluster constitute a health assessment data set. When the doctor conducts a health assessment on the osteoporosis patient, the health assessment data set is matched with the patient's clinical data as a reference for analysis of similar cases, so as to improve the efficiency of the doctor's analysis and processing and provide auxiliary analysis for the doctor; that is, when evaluating the osteoporosis patient, the patient is matched with other patients in the patient group cluster to which he belongs, and the health assessment data set of the osteoporosis patient is analyzed based on the health assessment data sets of other patients; wherein, the K-means clustering algorithm is a well-known technology, and the specific method is not introduced here.

[0079] So far, the present invention is completed.

[0080] To summarize, in an embodiment of the present invention, the present invention also provides a health assessment system for osteoporosis clinical data, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program stored in the memory to implement the steps of the aforementioned health assessment method for osteoporosis clinical data.

[0081] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A health assessment method for osteoporosis clinical data, characterized in that: The method comprises the following steps: Collect bone density, content data and metabolic index data of each major part of each patient; According to the difference of bone density distribution of each patient and other patients in each major part, the bone state expression degree of each major part of each patient is obtained, and the major parts include lumbar spine, hip and femur; The specific steps for obtaining the bone status expression of each major part of each patient are as follows: No. The patient's The calculation formula for the expression of the bone status of each major part is: ; in, Indicates The patient's The degree of bone status expression of the main parts; Indicates The patient's Bone density in major areas; Indicates The patient's The density of bones in each major part; Indicates The patient's Consistency in the number of patients with bone density within the threshold range at each major site; Represents a linear normalization function that normalizes the data value to within the interval; The specific steps for obtaining the bone density are as follows: The first The patient's The sum of the number of people who fluctuate upward and the number of people who fluctuate downward in the main parts is recorded as The patient's The density of bones in each major part; The specific steps for obtaining the upward fluctuation number and the downward fluctuation number are as follows: Get the The bone density of each patient is The first patient of the patient other than The bone density difference of the main parts is set to be less than or equal to the absolute value of the bone density difference The number of patients whose bone density fluctuation thresholds of the first major parts of the body are greater than 0 is recorded as the number of patients with upward fluctuations, and the absolute value of the bone density difference is less than or equal to the preset first The number of patients whose bone density fluctuation thresholds of the main parts of the body and whose difference was less than or equal to 0 was recorded as the number of patients with downward fluctuations; The said The patient's The specific steps to obtain the consistency of the number of patients with bone density within the threshold range in each major part are as follows: The first The patient's The difference between the ratio of the number of people with upward fluctuations to the number of people with downward fluctuations in the first major part and 1 is recorded as The patient's Consistency in the number of patients with bone density within the threshold range at each major site; Obtain the degree of physical fitness of each patient based on the consistency of the bone status of all major parts of each patient; The specific steps for obtaining the physical condition of each patient are as follows: No. The specific calculation method for the degree of physical fitness of a patient is: ; in, Indicates The patient's physical condition; Indicates The average value of the bone status expression of all major parts of each patient; Indicates The consistency of bone status expression among patients; The specific steps for obtaining the consistency of the bone state expression are as follows: The standard deviation of the skeletal status expression of all body parts of each patient was normalized. The normalized result of the standard deviation of the bone status expression of all body parts of the patient is recorded as The consistency of bone status expression among patients; According to the similarity between each content data of each patient and the corresponding metabolic index data and the distribution deviation in all the respective data, the health performance of each patient's living habits is obtained; The specific steps for obtaining the health performance of each patient's living habits are as follows: No. The calculation method of the health performance of a patient's lifestyle habits is: ; in, Indicates The health performance of each patient's lifestyle habits; Indicates the quantity of content data; Indicates The content data of each patient The content of the data; Indicates the maximum value of the content of all data in the content data; Indicates the number of metabolic index data; Indicates The metabolic index data of each patient The distribution deviation of the data is obtained by: The metabolic index data of each patient The difference between the metabolic index of the data and the minimum value of the metabolic index of all data in the metabolic index data, and The maximum value of all the data in the metabolic index data of the patient is The metabolic index data of each patient The ratio of the difference between the data is recorded as the The metabolic index data of each patient The distribution deviation of individual data; represents an absolute value function; the similarity relationship of the metabolic index data is expressed by express; Combine the physical condition of each patient and the health performance of their living habits to obtain the comprehensive physical condition of each patient; The specific steps for obtaining the comprehensive physical fitness level of each patient are as follows: ; in, Indicates The overall physical fitness of the patient; Indicates The patient's physical condition; Indicates The health performance of each patient's lifestyle habits; Indicates the preset threshold of health performance of living habits; Represents the preset hyperparameters; represents the absolute value function; The comprehensive physical fitness levels of all patients are clustered to obtain several patient groups, and the clinical data of patients in each patient group are used to form a health assessment data set as a reference for similar cases.

2. A health assessment system for osteoporosis clinical data, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is executed by a processor, the steps of a health assessment method for osteoporosis clinical data as claimed in claim 1 are implemented.

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