Postpartum follow-up information tracking management method and system based on mobile internet

Abstract

The invention relates to the technical field of medical informatics, in particular to a postpartum follow-up visit information tracking management method and system based on the mobile internet. The method comprises the following steps: firstly, according to the change condition of each growth and development index of a follow-up visit object at a follow-up visit stage at any time order, obtaining growth abnormality measurement; according to the abnormal condition of the follow-up visit object corresponding to each physiological recovery index in the follow-up visit stage, obtaining a recovery abnormity measure; obtaining a recovery influence development index of the follow-up visit object according to a correlation condition between the growth anomaly measurement and the recovery anomaly measurement of the follow-up visit object in each follow-up visit stage in the follow-up visit period and the recovery anomaly measurement of the follow-up visit object in each follow-up visit stage in the follow-up visit period; and finally, carrying out classified management on the postpartum follow-up visit information sets of all follow-up visit objects. By fully considering the influence of the recovery condition of the puerpera on the growth and development indexes of the newborn, the accuracy of the classification result of the postpartum follow-up visit information is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical informatics, and particularly relates to a method and system for tracking and managing postpartum follow-up information based on the mobile Internet. Background Art

[0002] Postpartum follow-up is an important link to ensure the physical recovery of parturients and the healthy growth of newborns. The objects of postpartum follow-up are mainly parturients and newborns after childbirth. Mainly, their physical conditions, living conditions, etc. are continuously monitored for a period of time after childbirth, and postpartum follow-up is carried out at important time nodes after childbirth. Postpartum follow-up information includes physiological recovery index data of parturients and growth and development index data of newborns, etc. Tracking and managing postpartum follow-up information helps to ensure the health of parturients and newborns, provide personalized guidance, and optimize the allocation of medical resources. In order to more accurately detect the health status of newborns, it is necessary to classify postpartum follow-up information to discover data correlations and provide support for data analysis and decision-making.

[0003] Since newborns with different health conditions have different growth and development situations, the prior art often classifies all newborns based on all the latest growth and development index data of newborns. When classifying newborns in the prior art, the influence of the recovery situation of parturients on the growth and development indexes of newborns is not fully considered, resulting in inaccurate classification results of postpartum follow-up information and making it difficult to accurately analyze the health status of newborns. Summary of the Invention

[0004] In order to solve the technical problem that it is difficult to accurately classify postpartum follow-up information in the prior art, the purpose of the present invention is to provide a method and system for tracking and managing postpartum follow-up information based on the mobile Internet. The specific technical solutions adopted are as follows: A method for tracking and managing postpartum follow-up information based on the mobile Internet, the method comprising: Obtaining a postpartum follow-up information set of each follow-up object; the postpartum follow-up information set includes all growth and development indexes and their corresponding all physiological recovery indexes in each follow-up stage during the follow-up period; According to the change situation of each growth and development index of the follow-up object in the follow-up stage over time, obtaining the growth abnormality measure of the follow-up object in the follow-up stage; according to the abnormality situation of each of the physiological recovery indexes corresponding to the follow-up object in the follow-up stage, obtaining the corresponding recovery abnormality measure of the follow-up object in the follow-up stage; according to the correlation between the growth abnormality measure and the recovery abnormality measure of the follow-up object in each follow-up stage during the follow-up period, and the recovery abnormality measure of the follow-up object in each follow-up stage during the follow-up period, obtaining the recovery-influencing development index of the follow-up object; Classify and manage the postnatal follow-up information set of all follow-up objects based on all growth and development indicators of each follow-up stage in the follow-up cycle of the follow-up objects, as well as the recovery impact development indicators of the follow-up objects.

[0005] Further, the method for obtaining the growth abnormality measure includes: Take any one follow-up stage as the stage to be analyzed; For any one growth and development indicator, calculate the numerical difference between the growth and development indicator of the follow-up object in the stage to be analyzed and its growth and development indicator in the previous follow-up stage in time sequence, and obtain the growth rate corresponding to the growth and development indicator of the follow-up object in the stage to be analyzed; calculate the average value of the growth rates corresponding to the growth and development indicators of all follow-up objects in the stage to be analyzed to obtain the reference growth rate corresponding to the growth and development indicator in the stage to be analyzed; calculate the absolute value of the difference between the growth rate corresponding to the growth and development indicator of the follow-up object in the stage to be analyzed and the reference growth rate to obtain the local abnormality measure corresponding to the growth and development indicator of the follow-up object in the stage to be analyzed; Calculate the average value of the local abnormality measures corresponding to all growth and development indicators of the follow-up object in the stage to be analyzed to obtain the growth abnormality measure of the follow-up object in the stage to be analyzed.

[0006] Further, the method for obtaining the recovery abnormality measure includes: Take any one physiological recovery indicator as the target recovery indicator; for any one follow-up stage, use the isolation forest method to obtain the abnormal score corresponding to the target recovery indicator of the follow-up object in the follow-up stage according to the isolation situation of the follow-up object corresponding to the target recovery indicator among all follow-up objects; Calculate the abnormal scores corresponding to all growth and development indicators of the follow-up object in the follow-up stage to obtain the recovery abnormality measure corresponding to the follow-up object in the follow-up stage.

[0007] Further, the method for obtaining the recovery impact development indicator includes: Obtain the health correlation measure of the follow-up object according to the correlation between the growth abnormality measure and the recovery abnormality measure of the follow-up object in each follow-up stage in the follow-up cycle; Obtain the overall recovery abnormality measure corresponding to the follow-up object according to the recovery abnormality measure of the follow-up object in each follow-up stage in the follow-up cycle; Fusion the health correlation measure and the overall recovery abnormality measure in a positive direction to obtain the recovery impact development indicator of the follow-up object.

[0008] Further, the method for obtaining the health correlation measure includes: Sequentially count the growth abnormality metrics of the follow-up object at each follow-up stage during the follow-up period in chronological order to obtain the growth abnormality metric sequence of the follow-up object; sequentially count the recovery abnormality metrics of the follow-up object at each follow-up stage during the follow-up period in chronological order to obtain the recovery abnormality metric sequence of the follow-up object; calculate the DTW distance between the growth abnormality metric sequence and the recovery abnormality metric sequence and perform a negative correlation mapping to obtain the health correlation metric of the follow-up object.

[0009] Further, the method for obtaining the overall recovery abnormality metric includes: Calculate the mean value of the recovery abnormality metrics of the follow-up object at all follow-up stages during the follow-up period to obtain the overall recovery abnormality metric corresponding to the follow-up object.

[0010] Further, the method for obtaining the classification management includes: According to all the growth and development indicators of the follow-up object at each follow-up stage during the follow-up period, and the recovery impact development indicators of the follow-up object, obtain the distance metric values of every two follow-up objects. Cluster the postpartum follow-up information set of all follow-up objects according to the distance metric values of every two follow-up objects to obtain each category of the postpartum follow-up information set.

[0011] Further, the method for obtaining the classification management includes: Calculate the mean value of the growth and development indicators of the follow-up object at all follow-up stages during the follow-up period to obtain the overall growth value corresponding to the growth and development indicators of the follow-up object; construct the feature vector of the follow-up object according to the recovery impact development indicators of the follow-up object and the overall growth value corresponding to each growth and development indicator of the follow-up object; obtain the distance metric values of every two follow-up objects according to the Euclidean distance between the feature vectors corresponding to every two follow-up objects.

[0012] Further, the method for obtaining the classification management includes: Use the K-Means clustering algorithm to cluster the postpartum follow-up information set of all follow-up objects according to the distance metric values of every two follow-up objects to obtain each category of the postpartum follow-up information set.

[0013] The present invention proposes a postpartum follow-up information tracking and management system based on the mobile Internet, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for tracking and managing postpartum follow-up information based on the mobile Internet are implemented.

[0014] The present invention has the following beneficial effects: The present invention analyzes the degree of abnormality of the growth and development indicators of newborns during the follow-up stage through growth abnormality measurement, analyzes the degree of abnormality of the physiological recovery indicators of parturients during the follow-up stage through recovery abnormality measurement, and obtains the development indicators affected by recovery of the follow-up objects by comprehensively analyzing the correlation between the growth abnormality measurement of newborns and the recovery abnormality measurement of parturients, as well as the recovery abnormality measurement of parturients during the entire follow-up period, so as to evaluate the specific impact of parturient recovery on the growth and development of newborns. According to all the growth and development indicators of the follow-up objects in each follow-up stage during the follow-up period and the development indicators affected by the recovery of the follow-up objects, a comprehensive evaluation of the growth and development of the follow-up objects is realized, and the postpartum follow-up information sets of all follow-up objects are classified and managed to improve the accuracy of the classification results of postpartum follow-up information. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 It is a flowchart of a method for tracking and managing postpartum follow-up information based on mobile Internet provided by an embodiment of the present invention; Figure 2 It is a flowchart of a method for obtaining development indicators affected by recovery provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following will, in conjunction with the accompanying drawings and preferred embodiments, describe in detail the specific implementation manners, structures, features and effects of a method and system for tracking and managing postpartum follow-up information based on mobile Internet proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0019] The following will specifically describe the specific solutions of a method and system for tracking and managing postpartum follow-up information based on mobile Internet provided by the present invention with reference to the accompanying drawings.

[0020] An embodiment of the present invention provides a method and system for tracking and managing postpartum follow-up information based on mobile Internet. Please refer toFigure 1 , which shows a flow chart of a postpartum follow-up information tracking and management method based on mobile Internet provided by an embodiment of the present invention, the method comprising the following steps: Step S1: obtaining a postpartum follow-up information set of each follow-up object; the postpartum follow-up information set includes all growth and development indicators at each follow-up stage in the follow-up cycle and all corresponding physiological recovery indicators.

[0021] From the hospital database, we obtain the postpartum follow-up information set of each follow-up object legally and compliantly based on strict authorization principles. This postpartum follow-up information set records the growth and development indicators and their corresponding physiological recovery indicators at each follow-up stage during the follow-up period in detail. The specific acquisition process includes: Considering that postpartum follow-up is an important link to ensure the physical recovery of the mother after childbirth and the healthy growth of the newborn, postpartum follow-up refers to postpartum follow-up of the physical condition of the mother and the newborn during an important time period after childbirth. The postpartum follow-up cycle in the present invention covers multiple follow-up stages after childbirth: for example, a one-week postpartum follow-up stage, a two-week postpartum follow-up stage, a full-month postpartum follow-up stage, a six-week postpartum follow-up stage, a three-month postpartum follow-up stage, and a six-month postpartum follow-up stage. Detailed postpartum follow-up is carried out at each follow-up stage to timely discover and deal with health problems of the mother and the newborn, and provide personalized medical advice and support.

[0022] For each follow-up stage, in order to evaluate the growth and development of the newborn, data collection is performed on all growth and development indicators of the newborn, including but not limited to weight, height, head circumference, etc. In order to evaluate the recovery of the parturient, data collection is performed on the physiological recovery indicators of the parturient, including but not limited to uterine recovery indicators and wound healing indicators. For example, medical staff score the wound healing situation based on the redness, swelling, bleeding, exudation, nodules and tenderness, subcrustal blood and effusion of the parturient's wound, wherein the larger the score value, the better the recovery situation, and the score value is used as the corresponding numerical value of the wound healing indicator. It should be noted that the follow-up object in the present invention refers to the newborn, and all the physiological recovery indicators of the newborn corresponding to the parturient at each follow-up stage in the follow-up period, as well as all the growth and development indicators of the newborn at each follow-up stage in the follow-up period, are used as the postpartum follow-up information set of the newborn.

[0023] The data collection in the present invention is authorized by the user, does not violate relevant laws and regulations, and does not violate public order and good morals. In order to facilitate calculations, all indicator data involved in the calculations in the embodiments of the present invention are pre-processed to eliminate the dimension effect. The specific means of removing the dimension effect are technical means well known to those skilled in the art and are not limited here.

[0024] Step S2: Obtain the growth anomaly metric of the follow-up object during the follow-up stage according to the chronological changes of each growth and development index of the follow-up object during the follow-up stage; obtain the recovery anomaly metric of the follow-up object during the follow-up stage according to the anomaly of each physiological recovery index of the follow-up object during the follow-up stage; obtain the development index affected by recovery of the follow-up object according to the correlation between the growth anomaly metric and the recovery anomaly metric of each follow-up stage in the follow-up cycle of the follow-up object, and the recovery anomaly metric of each follow-up stage in the follow-up cycle of the follow-up object.

[0025] By constructing a growth anomaly metric to analyze the anomaly degree of the growth and development indexes of a newborn during the follow-up stage, by constructing a recovery anomaly metric to analyze the anomaly degree of the physiological recovery indexes of a parturient during the follow-up stage, and by comprehensively analyzing the correlation between the growth anomaly metric of the newborn and the recovery anomaly metric of the parturient, as well as the recovery anomaly metric of the parturient during the entire follow-up cycle, obtain the development index affected by recovery of the follow-up object to evaluate the specific impact of the parturient's recovery on the growth and development of the newborn.

[0026] Considering that in the abnormal situation where a certain newborn has malnutrition or congenital diseases, it will make the body length development index of the newborn significantly different from the body length growth and development indexes of the overall newborns. For example, in the abnormal situation where a certain newborn has abnormal brain development, it will make the head circumference growth and development index of the newborn significantly different from that of the overall newborns. In order to analyze the anomaly degree of the growth and development indexes of a newborn during the follow-up stage, preferably, in an embodiment of the present invention, the method for obtaining the growth anomaly metric includes: Take any follow-up stage as the stage to be analyzed; For any growth and development index, calculate the numerical difference between the growth and development index of the follow-up object in the stage to be analyzed and its growth and development index in the previous follow-up stage in chronological order, and obtain the growth rate corresponding to the growth and development index of the follow-up object in the stage to be analyzed; calculate the average value of the growth rates corresponding to the growth and development indexes of all follow-up objects in the stage to be analyzed to obtain the reference growth rate corresponding to the growth and development index in the stage to be analyzed; calculate the absolute value of the difference between the growth rate corresponding to the growth and development index of the follow-up object in the stage to be analyzed and the reference growth rate to obtain the local anomaly metric corresponding to the growth and development index of the follow-up object in the stage to be analyzed; Calculate the average value of the local anomaly metrics corresponding to all growth and development indexes of the follow-up object in the stage to be analyzed to obtain the growth anomaly metric of the follow-up object in the stage to be analyzed.

[0027] In an embodiment of the present invention, the formula of the growth anomaly metric includes: ; where is the growth anomaly metric of the follow-up object in the stage to be analyzed; is the The growth rate corresponding to each growth and development indicator in the stage to be analyzed; For the reference growth rate corresponding to each growth and development indicator of the follow-up object in the stage to be analyzed; is the total number of all growth and development indicators; is the absolute value symbol; For the local anomaly measure corresponding to each growth and development indicator of the follow-up object in the stage to be analyzed.

[0028] For the above steps, for each follow-up object, calculate the difference between its growth and development indicators in the stage to be analyzed and the previous follow-up stage. This difference is the growth rate of the follow-up object in the stage to be analyzed. Calculate the average value of the growth rates of all follow-up objects in the stage to be analyzed to obtain the reference growth rate of this growth and development indicator in the stage to be analyzed. This reference growth rate represents the average growth level under normal circumstances. For each follow-up object, calculate the absolute value of the difference between its growth rate in the stage to be analyzed and the reference growth rate. This difference is the local anomaly measure of the follow-up object in the stage to be analyzed. The local anomaly measure reflects the degree of deviation of the follow-up object from the average growth level. For each follow-up object, calculate the average value of the local anomaly measures of all its growth and development indicators in the stage to be analyzed to obtain the growth anomaly measure of the follow-up object in the stage to be analyzed. The growth anomaly measure comprehensively reflects the degree of abnormality of the follow-up object in multiple growth and development indicators.

[0029] In order to quantify the degree of abnormality of the physiological recovery indicators of the parturient during the follow-up stage, preferably, in an embodiment of the present invention, the method for obtaining the recovery anomaly measure includes: Take any one of the physiological recovery indicators as the target recovery indicator; for any one follow-up stage, use the isolation forest method to obtain the anomaly score corresponding to the target recovery indicator of the follow-up object in the follow-up stage according to the isolation situation of the target recovery indicator of the follow-up object among all follow-up objects; Calculate the anomaly scores corresponding to all growth and development indicators of the follow-up object in the follow-up stage to obtain the recovery anomaly measure corresponding to the follow-up object in the follow-up stage. It should be noted that the isolation forest method is a well-known prior art to those skilled in the art. Here, only the brief process of the anomaly score corresponding to the target recovery indicator of the follow-up object in the follow-up stage is briefly described: For any one follow-up stage, construct an isolation forest tree according to the data values of the target recovery indicators of all follow-up objects, and obtain the anomaly score corresponding to the target recovery indicator of the follow-up object in the follow-up stage according to the path of the data value of the target recovery indicator of the follow-up object in the isolation forest tree.

[0030] For the above steps, considering that the physiological recovery index of the parturient is more isolated relative to other follow-up objects, that is, the more it deviates from the normal recovery range, it may indicate that the parturient has abnormal recovery in this index. On the contrary, the lower the abnormal score, the more similar the physiological recovery index of the parturient is to other follow-up objects and within the normal recovery range. Taking any one of the physiological recovery indexes as the target recovery index for analysis, during the follow-up stage, the data values of the target recovery indexes of all follow-up objects are collected. Using these data values, an isolation forest tree is constructed. The isolation forest method is a tree-based anomaly detection algorithm that divides data points by randomly selecting a feature and a feature value until all data points are isolated. For each follow-up object, according to the path length of the data value of its target recovery index in the isolation forest tree, the abnormal score of the target recovery index of this follow-up object during the follow-up stage is calculated. The abnormal score reflects the degree of isolation of the target recovery index of the follow-up object relative to all follow-up objects. The higher the score, the more the target recovery index of this follow-up object deviates from the normal distribution, that is, there may be abnormal recovery. For each follow-up object, the mean value of the abnormal scores of all its target recovery indexes during the follow-up stage is calculated to obtain the recovery anomaly measure of this follow-up object during the follow-up stage. The recovery anomaly measure comprehensively reflects the abnormal recovery situation of the follow-up object in multiple physiological recovery indexes.

[0031] Considering that the abnormal growth of the newborn may be affected by the abnormal recovery of the parturient or may also be affected by genetic factors, in order to analyze the causes of the abnormal growth of the newborn, it is necessary to analyze the impact of the abnormal recovery of the parturient on the abnormal development of the newborn. Please refer to Figure 2 , which shows a flowchart of a method for obtaining a recovery impact development index provided by an embodiment of the present invention. Preferably, in an embodiment of the present invention, the method for obtaining a recovery impact development index includes: Step S201: Obtain the health correlation measure of the follow-up object according to the correlation between the growth anomaly measure and the recovery anomaly measure of the follow-up object in each follow-up stage during the follow-up period.

[0032] Use the health correlation measure to quantify the correlation between the parturient's recovery situation and the abnormal growth of the newborn.

[0033] Preferably, in an embodiment of the present invention, the method for obtaining the health correlation measure includes: Sequentially count the growth anomaly metrics of the follow-up object at each follow-up stage during the follow-up period according to the time sequence to obtain the growth anomaly metric sequence of the follow-up object; sequentially count the recovery anomaly metrics of the follow-up object at each follow-up stage during the follow-up period according to the time sequence to obtain the recovery anomaly metric sequence of the follow-up object; calculate the DTW distance between the growth anomaly metric sequence and the recovery anomaly metric sequence and perform a negative correlation mapping to obtain the health correlation metric of the follow-up object. It should be noted that the acquisition of the DTW distance is a well-known existing technology in the art and can be obtained through the dynamic time warping algorithm.

[0034] Regarding the above steps, considering that in this example, the DTW distance reflects the time dynamic matching degree between growth anomaly and recovery anomaly. Subsequently, a negative correlation mapping is performed. Since it is generally expected that poor maternal recovery will lead to neonatal growth anomalies, there is an adverse association between the two. Thus, the obtained health correlation metric is a quantitative index indicating the correlation strength between maternal recovery anomalies and neonatal growth anomalies.

[0035] Step S202: Obtain the overall recovery anomaly metric corresponding to the follow-up object according to the recovery anomaly metrics of the follow-up object at each follow-up stage during the follow-up period.

[0036] To evaluate the overall recovery anomaly degree of the parturient during the entire follow-up period.

[0037] Preferably, in an embodiment of the present invention, the method for obtaining the overall recovery anomaly metric includes: Calculate the mean value of the recovery anomaly metrics of the follow-up object at all follow-up stages during the follow-up period to obtain the overall recovery anomaly metric corresponding to the follow-up object.

[0038] Regarding the above steps, the overall recovery anomaly metric avoids the contingency of single-stage data and reflects the overall health anomaly status of the parturient.

[0039] Step S203: Positively fuse the health correlation metric and the overall recovery anomaly metric to obtain the recovery impact on development index of the follow-up object.

[0040] Integrate the health correlation metric and the overall recovery anomaly metric to quantify the overall impact of maternal recovery on neonatal development.

[0041] It should be noted that positive fusion is a well-known existing technology in the art. Positive fusion can adopt simple multiplication, arithmetic mean or other suitable fusion methods. In an embodiment of the present invention, calculate the product of the health correlation metric and the overall recovery anomaly metric to obtain the recovery impact on development index of the follow-up object.

[0042] Regarding the above steps, considering the strong correlation between abnormal maternal recovery and abnormal neonatal growth, and the relatively poor overall maternal recovery, the recovery impact on developmental indicators will be correspondingly higher, indicating that maternal recovery has a greater impact on neonatal development. The recovery impact on developmental indicators is a comprehensive quantitative indicator that reflects the overall impact of maternal recovery on neonatal development. The recovery impact on developmental indicators is of great significance for classification. For example, a higher recovery impact on developmental indicators for a certain follow-up object represents a greater impact of the mother on the health of the newborn. Analysis is required during classification to more conveniently analyze the causes of neonatal health abnormalities.

[0043] Step S3: Classify and manage the postpartum follow-up information set of all follow-up objects according to all the growth and development indicators of each follow-up stage of the follow-up object during the follow-up period, as well as the recovery impact on developmental indicators of the follow-up object.

[0044] Considering that the growth and development indicators reflect the specific situation of growth and development, and the recovery impact on developmental indicators reflects the specific impact of maternal recovery on neonatal growth and development, classify and manage the postpartum follow-up information set of all follow-up objects according to all the growth and development indicators of each follow-up stage of the follow-up object during the follow-up period, as well as the recovery impact on developmental indicators of the follow-up object, so as to achieve a comprehensive assessment of the growth and development of the follow-up object, and improve the accuracy of the classification results of the postpartum follow-up information.

[0045] Preferably, in an embodiment of the present invention, preferably, in an embodiment of the present invention, the acquisition method for classification management includes: Obtain the distance metric value of every two follow-up objects according to all the growth and development indicators of each follow-up stage of the follow-up object during the follow-up period, as well as the recovery impact on developmental indicators of the follow-up object; Cluster the postpartum follow-up information set of all follow-up objects according to the distance metric value of every two follow-up objects to obtain each category of the postpartum follow-up information set.

[0046] Specifically, calculate the mean value of the growth and development indicators of all follow-up stages of the follow-up object during the follow-up period to obtain the overall growth value corresponding to the growth and development indicators of the follow-up object; construct the feature vector of the follow-up object according to the recovery influence development indicators of the follow-up object and the overall growth value corresponding to each growth and development indicator of the follow-up object; obtain the distance metric value between every two follow-up objects according to the Euclidean distance between the feature vectors corresponding to every two follow-up objects. Use the K-Means clustering algorithm to cluster the postpartum follow-up information set of all follow-up objects according to the distance metric value between every two follow-up objects to obtain each postpartum follow-up information set category. Among them, an example is given for the construction of the feature vector. All growth and development indicators of newborns in the present invention include weight, body length, and head circumference growth and development indicators; among them, the weight growth and development indicator is 3.57, the body length growth and development indicator is 54.3, the head circumference growth and development indicator is 36.1, and the recovery influence development indicator is 0.33; the specific value of the feature vector is (3.57, 54.3, 36.1, 0.33).

[0047] For the above steps, the overall growth value represents the average level of each growth and development indicator of the newborn during the follow-up period, and is used to comprehensively evaluate its overall growth status. The feature vector is a multi-dimensional data point, which comprehensively reflects the overall growth status of the newborn and the impact of the mother's recovery on its development. The distance metric value (Euclidean distance) is used to measure the similarity between the feature vectors of two follow-up objects, and the smaller the value, the more similar. The follow-up objects are divided into several categories according to the distance metric value, and each category represents a similar health status or risk level. Obtaining more accurate postpartum follow-up information set categories helps medical staff quickly locate high-risk groups and optimize resource allocation. It provides data support for personalized health intervention and medical research. It significantly improves the automation level and accuracy of postpartum follow-up management and has important clinical application value.

[0048] The present invention proposes a postpartum follow-up information tracking and management system based on the mobile Internet, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of a postpartum follow-up information tracking and management method based on the mobile Internet.

[0049] In summary, the embodiments of the present invention provide a method and system for tracking and managing postpartum follow-up information based on the mobile Internet. First, according to the changes in each growth and development index of the follow-up object over time during the follow-up stage, a growth abnormality metric is obtained; according to the abnormal conditions of each physiological recovery index of the follow-up object during the follow-up stage, a recovery abnormality metric is obtained; according to the correlation between the growth abnormality metric and the recovery abnormality metric of each follow-up stage of the follow-up object during the follow-up cycle, and the recovery abnormality metric of each follow-up stage of the follow-up object during the follow-up cycle, a recovery impact development index of the follow-up object is obtained; finally, the postpartum follow-up information set of all follow-up objects is classified and managed. By fully considering the impact of the mother's recovery on the growth and development indexes of the newborn, the present invention improves the accuracy of the classification results of postpartum follow-up information.

[0050] It should be noted that the above sequence of the embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0051] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A method for tracking and managing postpartum follow-up information based on the mobile Internet, characterized in that, The method includes: Obtaining the postpartum follow-up information set of each follow-up object; the postpartum follow-up information set includes all growth and development indicators and their corresponding physiological recovery indicators at each follow-up stage during the follow-up period; According to the change of each growth and development indicator of the follow-up object over time at the follow-up stage, obtaining the growth anomaly measure of the follow-up object at the follow-up stage; according to the anomaly of each of the physiological recovery indicators corresponding to the follow-up object at the follow-up stage, obtaining the corresponding recovery anomaly measure of the follow-up object at the follow-up stage; according to the correlation between the growth anomaly measure and the recovery anomaly measure of the follow-up object at each follow-up stage during the follow-up period, and the recovery anomaly measure of the follow-up object at each follow-up stage during the follow-up period, obtaining the recovery impact on development indicator of the follow-up object; Classifying and managing the postpartum follow-up information sets of all follow-up objects according to all the growth and development indicators of the follow-up object at each follow-up stage during the follow-up period, and the recovery impact on development indicator of the follow-up object.

2. The postpartum follow-up information tracking and management method based on the mobile Internet according to claim 1, characterized in that The method for obtaining the growth anomaly measure includes: Taking any one follow-up stage as the stage to be analyzed; For any one growth and development indicator, calculating the numerical difference between the stage to be analyzed of the follow-up object and the growth and development indicator of its previous follow-up stage in time sequence, obtaining the growth rate corresponding to the growth and development indicator of the follow-up object at the stage to be analyzed; calculating the mean value of the growth rates corresponding to the growth and development indicators of all follow-up objects at the stage to be analyzed, obtaining the reference growth rate corresponding to the growth and development indicator at the stage to be analyzed; calculating the absolute value of the difference between the growth rate corresponding to the growth and development indicator of the follow-up object at the stage to be analyzed and the reference growth rate, obtaining the local anomaly measure corresponding to the growth and development indicator of the follow-up object at the stage to be analyzed; Calculating the mean value of the local anomaly measures corresponding to all the growth and development indicators of the follow-up object at the stage to be analyzed, obtaining the growth anomaly measure of the follow-up object at the stage to be analyzed.

3. The method for postpartum follow-up information tracking and management based on the mobile Internet according to claim 1, wherein, The method for obtaining the recovery anomaly measure includes: Taking any one physiological recovery indicator as the target recovery indicator; for any one follow-up stage, using the isolation forest method, obtaining the anomaly score corresponding to the target recovery indicator of the follow-up object at the follow-up stage according to the isolation situation of the target recovery indicator of the follow-up object among all follow-up objects; Calculating the anomaly scores corresponding to all the growth and development indicators of the follow-up object at the follow-up stage, obtaining the corresponding recovery anomaly measure of the follow-up object at the follow-up stage.

4. The postpartum follow-up information tracking and management method based on the mobile Internet according to claim 1, characterized in that, The method for obtaining the recovery impact on development indicator includes: Obtaining the health correlation measure of the follow-up object according to the correlation between the growth anomaly measure and the recovery anomaly measure of the follow-up object at each follow-up stage during the follow-up period; Obtaining the overall recovery anomaly measure corresponding to the follow-up object according to the recovery anomaly measure of the follow-up object at each follow-up stage during the follow-up period; Fusing the health correlation measure and the overall recovery anomaly measure positively to obtain the recovery impact on development indicator of the follow-up object.

5. The method for tracking and managing postpartum follow-up information based on the mobile Internet according to claim 4, wherein, The method for obtaining the health correlation measure includes: Sequentially count the growth anomaly metrics of the follow-up object at each follow-up stage during the follow-up period according to the time sequence to obtain the growth anomaly metric sequence of the follow-up object; sequentially count the recovery anomaly metrics of the follow-up object at each follow-up stage during the follow-up period according to the time sequence to obtain the recovery anomaly metric sequence of the follow-up object; calculate the DTW distance between the growth anomaly metric sequence and the recovery anomaly metric sequence and perform negative correlation mapping to obtain the health correlation metric of the follow-up object.

6. The method for tracking and managing postpartum follow-up information based on the mobile Internet according to claim 4, wherein, The method for obtaining the overall recovery anomaly metric includes: Calculate the mean value of the recovery anomaly metrics of the follow-up object at all follow-up stages during the follow-up period to obtain the corresponding overall recovery anomaly metric of the follow-up object.

7. The postpartum follow-up information tracking and management method based on the mobile Internet according to claim 1, characterized in that The method for obtaining the classification management includes: According to all the growth and development indicators of the follow-up object at each follow-up stage during the follow-up period and the recovery impact development indicators of the follow-up object, obtain the distance metric values between every two follow-up objects. According to the distance metric values between every two follow-up objects, cluster the set of postpartum follow-up information of all follow-up objects to obtain each category of the set of postpartum follow-up information.

8. The postpartum follow-up information tracking and management method based on the mobile Internet according to claim 7, characterized in that, The method for obtaining the classification management includes: Calculate the mean value of the growth and development indicators of the follow-up object at all follow-up stages during the follow-up period to obtain the corresponding overall growth value of the growth and development indicators of the follow-up object; construct the feature vector of the follow-up object according to the recovery impact development indicator of the follow-up object and the corresponding overall growth value of each growth and development indicator of the follow-up object; obtain the distance metric values between every two follow-up objects according to the Euclidean distance between the corresponding feature vectors of every two follow-up objects.

9. The method for postnatal follow-up information tracking and management based on the mobile Internet according to claim 7, characterized in that, The method for obtaining the classification management includes: Use the K-Means clustering algorithm to cluster the set of postpartum follow-up information of all follow-up objects according to the distance metric values between every two follow-up objects to obtain each category of the set of postpartum follow-up information.

10. A postpartum follow-up information tracking and management system based on the mobile Internet, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for tracking and managing postpartum follow-up information based on mobile Internet according to any one of claims 1 to 9.

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