A method and system for tracking and managing postpartum follow-up information based on mobile internet.

Abstract

The present application relates to the technical field of medical informatics, in particular to a postpartum follow-up information tracking management method and system based on mobile internet. The present application first acquires growth abnormality metrics according to the change of each growth and development index of the follow-up object with time sequence in the follow-up stage; acquires recovery abnormality metrics according to the abnormality of each physiological recovery index of the follow-up object in the follow-up stage; acquires recovery affecting development indexes of the follow-up object according to the correlation between the growth abnormality metrics and the recovery abnormality metrics of the follow-up object in each follow-up stage in the follow-up cycle, and the recovery abnormality metrics of the follow-up object in each follow-up stage in the follow-up cycle; and finally classifies and manages the postpartum follow-up information set of all follow-up objects. The present application fully considers the influence of the recovery of the puerpera on the growth and development indexes of the newborn, and improves the classification result accuracy of the postpartum follow-up information.

Description

Technical Field

[0001] This invention relates to the field of medical informatics technology, specifically to a method and system for tracking and managing postpartum follow-up information based on the mobile Internet. Background Technology

[0002] Postpartum follow-up is a crucial step in ensuring the mother's postpartum recovery and the newborn's healthy growth. The primary focus of postpartum follow-up is on both the mother and newborn, involving continuous monitoring of their physical condition and living conditions for a period after delivery. Follow-up visits are conducted at key postpartum milestones. Information collected includes data on the mother's physiological recovery indicators and the newborn's growth and development indicators. Tracking and managing postpartum follow-up information helps safeguard the health of both mother and newborn, provides personalized guidance, and optimizes the allocation of medical resources. To more accurately assess the newborn's health, postpartum follow-up information needs to be categorized to identify data correlations and support data analysis and decision-making.

[0003] Because newborns with varying health conditions exhibit different growth and developmental stages, current technologies often classify all newborns based on the latest growth and developmental indicators. However, this classification method does not adequately consider the impact of maternal recovery on newborn growth and developmental indicators, leading to inaccurate classification results in postpartum follow-up information and hindering accurate analysis of newborn health. Summary of the Invention

[0004] To address the technical problem of accurately classifying postpartum follow-up information in existing technologies, the present invention aims to provide a method and system for tracking and managing postpartum follow-up information based on the mobile internet. The specific technical solution adopted is as follows:

[0005] A method for tracking and managing postpartum follow-up information based on mobile internet, the method comprising:

[0006] Obtain a set of postpartum follow-up information for each follow-up subject; the set of postpartum follow-up information includes all growth and development indicators and their corresponding physiological recovery indicators at each follow-up stage during the follow-up period;

[0007] Based on the changes in various growth and development indicators of the follow-up subjects over time during the follow-up period, the growth abnormality measure of the follow-up subjects during the follow-up period is obtained; based on the abnormalities of the corresponding physiological recovery indicators of the follow-up subjects during the follow-up period, the corresponding recovery abnormality measure of the follow-up subjects during the follow-up period is obtained; based on the correlation between the growth abnormality measure and the recovery abnormality measure of the follow-up subjects in each follow-up period, and the recovery abnormality measure of the follow-up subjects in each follow-up period, the recovery-impact-development indicator of the follow-up subjects is obtained.

[0008] Based on all growth and development indicators of the subjects during each follow-up stage of the follow-up period, as well as the recovery impact indicators of the subjects, the postpartum follow-up information sets of all subjects are classified and managed.

[0009] Furthermore, the method for obtaining the growth anomaly measurement includes:

[0010] Any follow-up phase will be used as the phase to be analyzed;

[0011] For any growth and development indicator, calculate the difference between the value of the growth and development indicator of the follow-up subject in the analysis stage and the value of the growth and development indicator in the previous follow-up stage in terms of time sequence, and obtain the growth rate of the growth and development indicator of the follow-up subject in the analysis stage; calculate the mean of the growth rate of the growth and development indicator of all follow-up subjects in the analysis stage, and obtain the reference growth rate of the growth and development indicator in the analysis stage; calculate the absolute value of the difference between the growth rate of the growth and development indicator of the follow-up subject in the analysis stage and the reference growth rate, and obtain the local anomaly measurement of the growth and development indicator of the follow-up subject in the analysis stage.

[0012] The mean of all growth and development indicators of the follow-up subjects corresponding to the local abnormality measure in the analysis stage is calculated to obtain the growth abnormality measure of the follow-up subjects in the analysis stage.

[0013] Furthermore, the method for obtaining the recovery anomaly metric includes:

[0014] Any physiological recovery indicator is used as the target recovery indicator; for any follow-up stage, the isolation forest method is used to obtain the abnormal score of the target recovery indicator of the follow-up subject in the follow-up stage based on the isolation status of the target recovery indicator of the follow-up subject among all follow-up subjects.

[0015] Calculate the abnormal scores of all growth and development indicators of the follow-up subjects during the follow-up period to obtain the recovery abnormality measure of the follow-up subjects during the follow-up period.

[0016] Furthermore, the method for obtaining the recovery indicators affecting development includes:

[0017] Based on the correlation between the growth abnormality measure and the recovery abnormality measure of the follow-up subject at each follow-up stage during the follow-up period, obtain the health association measure of the follow-up subject.

[0018] Based on the recovery anomaly measurement of the follow-up subject at each follow-up stage during the follow-up period, obtain the overall recovery anomaly measurement corresponding to the follow-up subject;

[0019] By positively fusing the health correlation metric and the overall recovery abnormality metric, the recovery impact on developmental indicators of the follow-up subjects are obtained.

[0020] Furthermore, the method for obtaining the health correlation metric includes:

[0021] The growth abnormality measures of the follow-up subjects are statistically analyzed sequentially at each follow-up stage during the follow-up period to obtain the growth abnormality measure sequence of the follow-up subjects; the recovery abnormality measures of the follow-up subjects are statistically analyzed sequentially at each follow-up stage during the follow-up period to obtain the recovery abnormality measure sequence of the follow-up subjects; the DTW distance between the growth abnormality measure sequence and the recovery abnormality measure sequence is calculated and negative correlation mapping is performed to obtain the health association measure of the follow-up subjects.

[0022] Furthermore, the method for obtaining the overall anomaly metric includes:

[0023] Calculate the mean of the recovery anomaly metric for the follow-up subject across all follow-up stages during the follow-up period to obtain the overall recovery anomaly metric for the follow-up subject.

[0024] Furthermore, the method for obtaining the classification management includes:

[0025] Based on all growth and development indicators of the subjects during each follow-up stage of the follow-up period, and the recovery impact indicators of the subjects, the distance metric value between each pair of subjects is obtained.

[0026] Based on the distance metric between each pair of the follow-up subjects, the postpartum follow-up information sets of all follow-up subjects are clustered to obtain the categories of each postpartum follow-up information set.

[0027] Furthermore, the method for obtaining the classification management includes:

[0028] Calculate the mean of the growth and development indicators of the follow-up subjects during all follow-up stages in the follow-up period to obtain the overall growth value corresponding to the growth and development indicators of the follow-up subjects; construct the feature vector of the follow-up subjects based on the recovery impact development indicators of the follow-up subjects and the overall growth value corresponding to each growth and development indicator of the follow-up subjects; obtain the distance metric value between each pair of follow-up subjects based on the Euclidean distance between the feature vectors corresponding to each pair of follow-up subjects.

[0029] Furthermore, the method for obtaining the classification management includes:

[0030] Using the K-Means clustering algorithm, the postpartum follow-up information sets of all follow-up subjects are clustered based on the distance metric between each pair of follow-up subjects to obtain the categories of each postpartum follow-up information set.

[0031] This invention proposes a postpartum follow-up information tracking and management system based on 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 the postpartum follow-up information tracking and management method based on mobile Internet.

[0032] The present invention has the following beneficial effects:

[0033] This invention analyzes the degree of abnormality in neonatal growth and development indicators during the follow-up period using growth abnormality measurement, and analyzes the degree of abnormality in maternal physiological recovery indicators during the follow-up period using recovery abnormality measurement. By comprehensively analyzing the correlation between neonatal growth abnormality measurement and maternal recovery abnormality measurement, as well as the maternal recovery abnormality measurement throughout the entire follow-up period, it obtains the recovery-impact-development index of the follow-up subjects to assess the specific impact of maternal recovery on neonatal growth and development. Based on all growth and development indicators and recovery-impact-development indexes of the follow-up subjects at each follow-up stage, a comprehensive assessment of the growth and development of the follow-up subjects is achieved. The postpartum follow-up information of all subjects is categorized and managed to improve the accuracy of the categorization results. Attached Figure Description

[0034] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 A flowchart illustrating a postpartum follow-up information tracking and management method based on mobile internet, as provided in one embodiment of the present invention;

[0036] Figure 2 This is a flowchart of a method for obtaining indicators that affect development, provided as an embodiment of the present invention. Detailed Implementation

[0037] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a postpartum follow-up information tracking and management method and system based on the mobile internet proposed by the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0038] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0039] The following description, in conjunction with the accompanying drawings, details the specific solution of the postpartum follow-up information tracking and management method and system based on the mobile Internet provided by this invention.

[0040] This invention provides a method and system for tracking and managing postpartum follow-up information based on the mobile internet. Please refer to [link / reference]. Figure 1 The diagram illustrates a flowchart of a postpartum follow-up information tracking and management method based on mobile internet, according to an embodiment of the present invention. The method includes the following steps:

[0041] Step S1: Obtain the postpartum follow-up information set for each follow-up subject; 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.

[0042] From the hospital database, following strict authorization principles, a legal and compliant set of postpartum follow-up information for each subject was obtained. This set of postpartum follow-up information comprehensively records the growth and development indicators and their corresponding physiological recovery indicators for each follow-up stage within the follow-up period. The specific acquisition process includes:

[0043] Considering that postpartum follow-up is a crucial step in ensuring the mother's postpartum recovery and the newborn's healthy growth, postpartum follow-up refers to monitoring the physical condition of both mother and newborn during key postpartum periods. In this invention, the postpartum follow-up cycle covers multiple follow-up stages after delivery: for example, a one-week follow-up stage, a two-week follow-up stage, a one-month follow-up stage, a six-week follow-up stage, a three-month follow-up stage, and a six-month follow-up stage. Detailed postpartum follow-up is conducted at each stage to promptly identify and address health issues for both mother and newborn, providing personalized medical advice and support.

[0044] For each follow-up stage, data on all growth and development indicators of the newborn are collected to assess their growth and development, including but not limited to weight, length, and head circumference. Data on the mother's physiological recovery indicators are also collected to assess her recovery, including but not limited to uterine recovery indicators and wound healing indicators. For example, medical staff score the wound healing based on the mother's wound's redness, swelling, bleeding, oozing, induration, tenderness, blood accumulation under the scab, and fluid accumulation. A higher score indicates better recovery, and this score is used as the corresponding numerical value for the wound healing indicator. It should be noted that the follow-up subject in this invention refers to the newborn. All physiological recovery indicators of the mother and all growth and development indicators of the newborn at each follow-up stage of the follow-up period are used as the newborn's postpartum follow-up information set.

[0045] The data collected in this invention is authorized by the user, does not violate relevant laws and regulations, and does not contravene public order and good morals. To facilitate calculations, all indicator data involved in the calculations in this embodiment of the invention have undergone data preprocessing to eliminate the influence of dimensions. The specific methods for removing the influence of dimensions are well-known to those skilled in the art and are not limited here.

[0046] Step S2: Based on the changes in various growth and development indicators of the follow-up subjects over time, obtain the growth abnormality measurement of the follow-up subjects during the follow-up period; based on the abnormalities of the corresponding physiological recovery indicators of the follow-up subjects during the follow-up period, obtain the corresponding recovery abnormality measurement of the follow-up subjects during the follow-up period; based on the correlation between the growth abnormality measurement and the recovery abnormality measurement of the follow-up subjects in each follow-up period, and the recovery abnormality measurement of the follow-up subjects in each follow-up period, obtain the recovery impact on development indicators of the follow-up subjects.

[0047] By constructing a growth abnormality metric to analyze the degree of abnormality in the growth and development indicators of newborns during the follow-up period, and by constructing a recovery abnormality metric to analyze the degree of abnormality in the physiological recovery indicators of mothers during the follow-up period, and by comprehensively analyzing the correlation between the growth abnormality metric of newborns and the recovery abnormality metric of mothers, as well as the recovery abnormality metric of mothers throughout the entire follow-up period, the recovery impact indicators of the follow-up subjects are obtained to assess the specific impact of maternal recovery on the growth and development of newborns.

[0048] Considering that a newborn's malnutrition or congenital abnormalities can cause significant differences in their height development indicators compared to the overall height growth and development indicators of newborns, and for example, a newborn with brain malformation can cause significant differences in their head circumference growth and development indicators compared to the overall newborn population, in order to analyze the degree of abnormality in the growth and development indicators of newborns during the follow-up period, preferably, in one embodiment of the present invention, the method for obtaining the measurement of growth abnormalities includes:

[0049] Any follow-up phase will be used as the phase to be analyzed;

[0050] For any growth and development indicator, calculate the difference between the growth and development indicator values ​​of the follow-up subject in the analysis stage and the previous follow-up stage in terms of time sequence to obtain the growth rate of the follow-up subject's growth and development indicator in the analysis stage; calculate the mean of the growth rate of all follow-up subjects' growth and development indicators in the analysis stage to obtain the reference growth rate of the growth and development indicator in the analysis stage; calculate the absolute value of the difference between the growth rate of the follow-up subject's growth and development indicator in the analysis stage and the reference growth rate to obtain the local anomaly measurement of the follow-up subject's growth and development indicator in the analysis stage.

[0051] The mean value of all growth and development indicators of the follow-up subjects at the stage to be analyzed is calculated to obtain the growth abnormality measure of the follow-up subjects at the stage to be analyzed.

[0052] In one embodiment of the present invention, the formula for measuring abnormal growth includes:

[0053] ;in, To measure abnormal growth in the subjects during the analysis phase; For the first follow-up subject The corresponding growth rate of each growth and development indicator in the stage to be analyzed; For the first follow-up subject The reference increase for each growth and development indicator during the analysis phase; The total number of all growth and development indicators; It is the absolute value symbol; For the first follow-up subject Each growth and development indicator corresponds to a local anomaly measurement in the stage to be analyzed.

[0054] Following the steps above, for each follow-up subject, the difference between their growth and development indicators in the analysis phase and the previous follow-up phase is calculated. This difference represents the growth rate of that subject in the analysis phase. The average growth rates of all follow-up subjects in the analysis phase are then calculated to obtain the reference growth rate for that growth and development indicator in the analysis phase. This reference growth rate represents the average growth level under normal conditions. For each follow-up subject, the absolute value of the difference between their growth rate in the analysis phase and the reference growth rate is calculated. This difference represents the local anomaly measure of that subject in the analysis phase. The local anomaly measure reflects the degree of deviation of the follow-up subject from the average growth level. For each follow-up subject, the average of the local anomaly measures of all growth and development indicators in the analysis phase is calculated to obtain the growth anomaly measure of that subject in the analysis phase. The growth anomaly measure comprehensively reflects the degree of abnormality of the follow-up subject across multiple growth and development indicators.

[0055] To quantify the degree of abnormality in the physiological recovery indicators of postpartum women during the follow-up phase, preferably, in one embodiment of the present invention, the method for obtaining the recovery abnormality measurement includes:

[0056] Any physiological recovery indicator is used as the target recovery indicator; for any follow-up stage, the isolation forest method is used to obtain the abnormal score of the target recovery indicator of the follow-up subject in the follow-up stage based on the isolation status of the target recovery indicator of the follow-up subject among all follow-up subjects.

[0057] The abnormal scores for all growth and development indicators of the follow-up subjects during the follow-up period are calculated to obtain the recovery abnormality measure of the subjects during the follow-up period. It should be noted that the isolated forest method is a well-known existing technique; here, only a brief description of the process of calculating the abnormal scores of the target recovery indicators of the follow-up subjects during the follow-up period is provided:

[0058] For any follow-up phase, an isolated forest tree is constructed based on the data values ​​of the target recovery indicators of all follow-up subjects. Based on the path of the target recovery indicator data value of the follow-up subject in the isolated forest tree, the abnormal score of the target recovery indicator of the follow-up subject in the follow-up phase is obtained.

[0059] Regarding the above steps, considering that the more isolated the postpartum woman's physiological recovery indicator is relative to other follow-up subjects—that is, the more it deviates from the normal recovery range—it may indicate that the postpartum woman has an abnormal recovery in that indicator. Conversely, the lower the abnormality score, the more similar the postpartum woman's physiological recovery indicator is to other follow-up subjects, and it is within the normal recovery range. Any physiological recovery indicator is used as the target recovery indicator for analysis. During the follow-up phase, the target recovery indicator data values ​​of all follow-up subjects are collected. These data values ​​are then used to construct an isolated forest tree. The isolated forest method is a tree-based anomaly detection algorithm that randomly selects a feature and a feature value to segment data points until all data points are isolated. For each follow-up subject, the abnormality score of that subject's target recovery indicator during the follow-up phase is calculated based on the path length of its data value in the isolated forest tree. The abnormality score reflects the degree of isolation of the follow-up subject's target recovery indicator relative to all follow-up subjects. The higher the score, the more the target recovery indicator deviates from the normal distribution, indicating a possible recovery abnormality. For each follow-up subject, the mean of the abnormal scores for all target recovery indicators during the follow-up phase is calculated to obtain the recovery abnormality measure for that subject during the follow-up phase. The recovery abnormality measure comprehensively reflects the recovery abnormality of the follow-up subject across multiple physiological recovery indicators.

[0060] Considering that abnormal neonatal growth may be influenced by maternal recovery abnormalities or genetic factors, in order to analyze the causes of abnormal neonatal growth, it is necessary to analyze the impact of abnormal maternal recovery on abnormal neonatal development. Please refer to [link to relevant documentation]. Figure 2 The diagram illustrates a flowchart of a method for obtaining indicators affecting developmental recovery according to an embodiment of the present invention. Preferably, in one embodiment of the present invention, the method for obtaining indicators affecting developmental recovery includes:

[0061] Step S201: Based on the correlation between the growth abnormality measure and the recovery abnormality measure of the follow-up subject at each follow-up stage during the follow-up period, obtain the health association measure of the follow-up subject.

[0062] We used health association metrics to quantify the correlation between maternal recovery and neonatal growth abnormalities.

[0063] Preferably, in one embodiment of the present invention, the method for obtaining health correlation metrics includes:

[0064] The growth abnormality measures of the follow-up subjects were statistically analyzed sequentially at each follow-up stage during the follow-up period to obtain a growth abnormality measure sequence. Similarly, the recovery abnormality measures of the follow-up subjects were statistically analyzed sequentially at each follow-up stage during the follow-up period to obtain a recovery abnormality measure sequence. The DTW distance between the growth abnormality measure sequence and the recovery abnormality measure sequence was calculated and negatively correlated to obtain the health association measure of the follow-up subjects. It should be noted that obtaining the DTW distance is a prior art well-known to those skilled in the art and can be achieved through a dynamic time warping algorithm.

[0065] Regarding the steps outlined above, considering that in this example, the DTW distance reflects the degree of temporal dynamic matching between growth abnormalities and recovery abnormalities, a negative correlation mapping is then performed. Since poor maternal recovery is generally expected to lead to neonatal growth abnormalities, the resulting health association metric is a quantitative indicator representing the strength of the correlation between maternal recovery abnormalities and neonatal growth abnormalities.

[0066] Step S202: Based on the recovery anomaly measurement of the follow-up subject at each follow-up stage during the follow-up period, obtain the overall recovery anomaly measurement corresponding to the follow-up subject.

[0067] To assess the overall degree of abnormality in the recovery of postpartum women throughout the entire follow-up period.

[0068] Preferably, in one embodiment of the present invention, the method for obtaining the overall anomaly measurement includes:

[0069] Calculate the mean of the recovery anomaly measure of the follow-up subject across all follow-up stages during the follow-up period to obtain the overall recovery anomaly measure for the follow-up subject.

[0070] To address the above steps, restoring overall abnormality measurement avoids the randomness of single-stage data and reflects the overall health abnormality status of postpartum women.

[0071] Step S203: Positively integrate health-related metrics and overall recovery abnormality metrics to obtain the recovery impact on development indicators of the follow-up subjects.

[0072] By combining health-related metrics and overall recovery abnormality metrics, the overall impact of maternal recovery on neonatal development is quantified.

[0073] It should be noted that forward fusion is a well-known prior art technique, and forward fusion can employ simple product, arithmetic mean, or other suitable fusion methods. In one embodiment of the present invention, the product of the health association metric and the overall recovery abnormality metric is calculated to obtain the recovery impact development index of the follow-up subjects.

[0074] Regarding the above steps, considering the strong correlation between abnormal maternal recovery and abnormal neonatal growth, and given that the overall maternal recovery is poor, the recovery-impact-development index will also be higher, indicating a significant impact of maternal recovery on neonatal development. The recovery-impact-development index is a comprehensive quantitative indicator that reflects the overall impact of maternal recovery on neonatal development. This index is crucial for classification. For example, a higher recovery-impact-development index for a follow-up subject indicates a greater impact of the mother on neonatal health, requiring further analysis during classification to facilitate the analysis of the causes of neonatal health abnormalities.

[0075] Step S3: Based on all growth and development indicators of the follow-up subjects at each follow-up stage during the follow-up period, as well as the recovery impact indicators on the follow-up subjects' development, classify and manage the postpartum follow-up information set of all follow-up subjects.

[0076] Considering that growth and development indicators reflect the specific situation of growth and development, and recovery impact indicators reflect the specific impact of maternal recovery on neonatal growth and development, based on all growth and development indicators of the follow-up subjects at each follow-up stage during the follow-up period, as well as the recovery impact indicators of the follow-up subjects, a comprehensive assessment of the growth and development of the follow-up subjects can be achieved. The postpartum follow-up information of all follow-up subjects can be classified and managed to improve the accuracy of the classification results of postpartum follow-up information.

[0077] Preferably, in one embodiment of the present invention, the method for obtaining classification management includes:

[0078] Based on all growth and development indicators of the subjects at each follow-up stage during the follow-up period, as well as the recovery impact indicators of the subjects, the distance metric between each pair of subjects was obtained.

[0079] Based on the distance metric between each pair of follow-up subjects, the postpartum follow-up information sets of all follow-up subjects are clustered to obtain the categories of each postpartum follow-up information set.

[0080] Specifically, the mean values ​​of growth and development indicators of the follow-up subjects across all follow-up stages are calculated to obtain the overall growth value corresponding to each growth and development indicator. Based on the recovery impact development indicators and the overall growth values ​​corresponding to each growth and development indicator, feature vectors for the follow-up subjects are constructed. The distance metric between each pair of follow-up subjects is obtained based on the Euclidean distance between their corresponding feature vectors. Using the K-Means clustering algorithm, the postpartum follow-up information sets of all follow-up subjects are clustered based on the distance metric between each pair of follow-up subjects to obtain the categories of each postpartum follow-up information set. For example, the construction of the feature vectors is illustrated in this invention. All growth and development indicators of newborns include weight, length, and head circumference growth and development indicators; the weight growth and development indicator is 3.57, the length growth and development indicator is 54.3, the head circumference growth and development indicator is 36.1, and the recovery impact development indicator is 0.33. The specific values ​​of the feature vectors are (3.57, 54.3, 36.1, 0.33).

[0081] Regarding the above steps, the overall growth value represents the average level of various growth and development indicators of the newborn during the follow-up period, used to comprehensively assess their overall growth status. The feature vector is a multi-dimensional data point that comprehensively reflects the newborn's overall growth status and the impact of maternal recovery on their development. The distance metric (Euclidean distance) is used to measure the similarity between the feature vectors of two follow-up subjects; the smaller the value, the more similar they are. Based on the distance metric, the follow-up subjects are divided into several categories, each representing a similar health status or risk level. Obtaining a more accurate set of postpartum follow-up information categories helps medical staff quickly identify high-risk groups and optimize resource allocation. It provides data support for personalized health interventions and medical research. It significantly improves the automation level and accuracy of postpartum follow-up management, and has important clinical application value.

[0082] This invention proposes a postpartum follow-up information tracking and management system based on 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 mobile Internet.

[0083] In summary, this invention provides a method and system for tracking and managing postpartum follow-up information based on the mobile internet. First, it obtains a growth abnormality metric based on the changes in various growth and development indicators of the follow-up subject over time. Then, it obtains a recovery abnormality metric based on the abnormalities in corresponding physiological recovery indicators during the follow-up phase. Finally, it obtains a recovery-impact-development indicator based on the correlation between the growth abnormality metric and the recovery abnormality metric at each follow-up phase, as well as the recovery abnormality metric at each follow-up phase. Finally, it classifies and manages the postpartum follow-up information set of all subjects. This invention improves the accuracy of postpartum follow-up information classification by fully considering the impact of the mother's recovery on the newborn's growth and development indicators.

[0084] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0085] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1.A method for tracking and managing postpartum follow-up information based on a mobile Internet, characterized in that, The method comprises: acquiring a postpartum follow-up information set of each follow-up newborn; the postpartum follow-up information set comprises all growth and development indexes of the follow-up newborn in each follow-up stage in a follow-up period and all physiological recovery indexes of the corresponding puerpera; acquiring a growth abnormality measure of the follow-up newborn in the follow-up stage according to the change of each growth and development index of the follow-up newborn over time; acquiring a recovery abnormality measure corresponding to the follow-up stage of the corresponding puerpera according to the abnormality of each physiological recovery index of the corresponding puerpera in the follow-up stage; acquiring a recovery influence development index of the follow-up newborn according to the correlation between the growth abnormality measure of the follow-up newborn in each follow-up stage in the follow-up period and the recovery abnormality measure of the corresponding puerpera and the recovery abnormality measure of the corresponding puerpera in each follow-up stage in the follow-up period; classifying and managing the postpartum follow-up information set of all follow-up newborns according to all growth and development indexes of the follow-up newborn in each follow-up stage in the follow-up period and the recovery influence development index of the follow-up newborn; wherein the method for acquiring the recovery influence development index comprises: acquiring a health correlation measure of the follow-up newborn according to the correlation between the growth abnormality measure of the follow-up newborn in each follow-up stage in the follow-up period and the recovery abnormality measure of the corresponding puerpera; the method for acquiring the health correlation measure comprises: sequentially calculating the growth abnormality measure of the follow-up newborn in each follow-up stage in the follow-up period in time sequence to obtain a growth abnormality measure sequence of the follow-up newborn; sequentially calculating the recovery abnormality measure of the corresponding puerpera in each follow-up stage in the follow-up period in time sequence to obtain a recovery abnormality measure sequence of the corresponding puerpera; calculating the DTW distance of the growth abnormality measure sequence and the recovery abnormality measure sequence and performing negative correlation mapping to obtain the health correlation measure of the follow-up newborn; acquiring a recovery overall abnormality measure of the corresponding puerpera according to the recovery abnormality measure of the corresponding puerpera in each follow-up stage in the follow-up period; the method for acquiring the recovery overall abnormality measure comprises: calculating the average of the recovery abnormality measure of the corresponding puerpera in all follow-up stages in the follow-up period to obtain the recovery overall abnormality measure of the corresponding puerpera; positively fusing the health correlation measure and the recovery overall abnormality measure to obtain the recovery influence development index of the follow-up newborn. 2.The postpartum follow-up information tracking management method based on mobile Internet according to claim 1, characterized in that, The method for acquiring the growth abnormality measure comprises: taking any one follow-up stage as an analysis stage; For any one growth and development index, the numerical difference between the growth and development index of the new-born baby to be analyzed in the to-be-analyzed stage and the growth and development index of the new-born baby in the previous follow-up stage in time sequence is calculated to obtain the corresponding growth amplitude of the growth and development index of the new-born baby to be analyzed in the to-be-analyzed stage; the mean value of the growth and development index of all new-born babies to be analyzed in the to-be-analyzed stage corresponding to the growth amplitude is calculated to obtain the reference amplitude corresponding to the growth and development index in the to-be-analyzed stage; and the absolute value of the difference between the growth and development index of the new-born baby to be analyzed in the to-be-analyzed stage corresponding to the growth amplitude and the reference amplitude is calculated to obtain the local abnormality measure corresponding to the growth and development index of the new-born baby to be analyzed in the to-be-analyzed stage. The mean value of all growth and development indexes of the new-born baby to be analyzed in the to-be-analyzed stage corresponding to the local abnormality measure is calculated to obtain the growth abnormality measure of the new-born baby to be analyzed in the to-be-analyzed stage. 3.The postpartum follow-up information tracking management method based on mobile Internet according to claim 1, characterized in that, The method for obtaining the recovery abnormality measure comprises the following steps: Any one physiological recovery index is taken as a target recovery index; for any one follow-up stage, the target recovery index of the new-born baby corresponding to the mother is obtained by using the isolation forest method according to the isolation of the target recovery index of the new-born baby corresponding to the mother in all new-born babies corresponding to the mother, and the abnormal score of the target recovery index of the new-born baby corresponding to the mother in the follow-up stage is obtained. The mean value of all target recovery indexes of the new-born baby corresponding to the mother in the follow-up stage corresponding to the abnormal score is calculated to obtain the recovery abnormality measure corresponding to the new-born baby corresponding to the mother in the follow-up stage. 4.The postpartum follow-up information tracking management method based on mobile Internet according to claim 1, characterized in that, The method for obtaining the classification management comprises the following steps: According to all growth and development indexes of the new-born baby to be analyzed in each follow-up stage in the follow-up cycle and the recovery influence development index of the new-born baby to be analyzed, the distance measure value of each two new-born babies to be analyzed is obtained. According to the distance measure value of each two new-born babies to be analyzed, the postpartum follow-up information set of all new-born babies to be analyzed is clustered to obtain each postpartum follow-up information set category. 5.The postpartum follow-up information tracking management method based on a mobile Internet according to claim 4, characterized in that, The method for obtaining the classification management comprises the following steps: The mean value of all growth and development indexes of the new-born baby to be analyzed in each follow-up stage in the follow-up cycle is calculated to obtain the overall growth value corresponding to the growth and development index of the new-born baby to be analyzed; the feature vector of the new-born baby to be analyzed is constructed according to the recovery influence development index of the new-born baby to be analyzed and the overall growth value corresponding to each growth and development index of the new-born baby to be analyzed; and the distance measure value of each two new-born babies to be analyzed is obtained according to the Euclidean distance of the feature vectors corresponding to each two new-born babies to be analyzed. 6.The postpartum follow-up information tracking management method based on mobile Internet according to claim 4, characterized in that, The method for obtaining the classification management comprises the following steps: According to the distance measure value of each two new-born babies to be analyzed, the postpartum follow-up information set of all new-born babies to be analyzed is clustered by using the K-Means clustering algorithm to obtain each postpartum follow-up information set category. 7.A mobile Internet-based postpartum follow-up information tracking management system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to realize the steps of the postpartum follow-up information tracking management method based on the mobile Internet according to any one of claims 1-6.

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