Hepatitis B surface antigen track mode prompting method, device, equipment and storage medium

Abstract

The invention relates to the technical field of medical information processing, and discloses a hepatitis B surface antigen track mode prompting method, device and equipment and a storage medium, the method comprises the following steps: obtaining hepatitis B surface antigen information obtained by multiple first objects through multiple times of detection, the first objects being chronic hepatitis B objects; obtaining a first grouping result output by a target group-based trajectory model, wherein the target group-based trajectory model is used for grouping the first objects based on the trajectory of the hepatitis B surface antigen information; based on the first grouping result, determining a hepatitis B surface antigen trajectory pattern corresponding to the first object in each group, one group corresponding to one hepatitis B surface antigen trajectory pattern; for the first object in the group, corresponding first prompt information is output, the first prompt information is used for indicating the hepatitis B surface antigen track mode of the first object, different hepatitis B surface antigen track modes correspond to different target states, and the target states are converted states. The invention can guide the development and improvement of medicines.

Description

Technical Field

[0001] The present invention relates to the field of medical information processing technology, and in particular to a hepatitis B surface antigen trajectory pattern prompting method, device, equipment and storage medium. Background Art

[0002] Chronic hepatitis B (CHB) is a major potential factor for the development of cirrhosis and hepatocellular carcinoma (HCC), posing a major threat to global public health. Exploring the risk factors associated with HCC in CHB patients will help develop drugs for CHB. Viral markers play a vital role in the occurrence and development of HCC. Quantitative hepatitis B surface antigen levels are one of the valuable viral markers. Related studies have shown that high levels of HBsAg increase the risk of HCC in treatment-naive individuals with serum HBV DNA <2000IU / mL. However, another study found that in CHB patients with undetectable HBV DNA after nucleoside (acid) analog therapy, HBsAg levels were not associated with the occurrence of HCC. In addition, in untreated CHB patients with hepatitis B E antigen seropositive, persistently high levels of HBsAg were associated with a lower risk of HCC. Therefore, the role of HBsAg in the occurrence and development of HCC remains controversial. More importantly, the relationship between HBsAg trajectory patterns and HCC in CHB patients receiving nucleoside (acid) analog therapy is still unclear.

[0003] Therefore, it is necessary to clarify the correspondence between the HBsAg trajectory pattern and the development of chronic hepatitis B (including development towards cure and development towards liver cancer) to guide the research and development and improvement of chronic hepatitis B. Summary of the invention

[0004] In view of this, the present invention provides a hepatitis B surface antigen trajectory pattern prompt method, device, equipment and storage medium to solve the problem of unclear drug development direction caused by the unclear correspondence between the hepatitis B surface antigen trajectory pattern and the development of chronic hepatitis B.

[0005] In a first aspect, the present invention provides a method for prompting a hepatitis B surface antigen trajectory pattern, the method comprising:

[0006] Acquire hepatitis B surface antigen information obtained by multiple tests of multiple first objects, where the first objects are objects with chronic hepatitis B. If the first objects are converted from a chronic hepatitis B state to another state, only the hepatitis B surface antigen information of the first objects when they are in the chronic hepatitis B state is acquired;

[0007] Acquire a first grouping result output by a target group basis trajectory model, wherein the target group basis trajectory model groups the first objects based on the trajectory of the hepatitis B surface antigen information;

[0008] Based on the first grouping result, determining the hepatitis B surface antigen trajectory pattern corresponding to the first object in each group, where one group corresponds to one hepatitis B surface antigen trajectory pattern;

[0009] For the first object in the group, the corresponding first prompt information is output, and the first prompt information is used to indicate the hepatitis B surface antigen trajectory pattern of the first object. Different hepatitis B surface antigen trajectory patterns correspond to different target states, and the target state is the state after the chronic hepatitis B is converted.

[0010] In an optional embodiment, the hepatitis B surface antigen trajectory pattern includes at least: a fast decline mode and a slow decline mode.

[0011] In an optional implementation, before obtaining the first grouping result output by the target group base trajectory model, the method further includes:

[0012] Establishing a plurality of initial group basis trajectory models, each of the initial group basis trajectory models having a different number of groups;

[0013] Using the initial group basis trajectory model to perform group fitting on the trajectory of the hepatitis B surface antigen information, to obtain a fitting result and an initial grouping result;

[0014] Calculating an evaluation index of the initial group basis trajectory model based on the fitting result and / or the initial grouping result;

[0015] The target group basis trajectory model is selected from the initial group basis trajectory models based on the evaluation index.

[0016] In an optional embodiment, the method for prompting the hepatitis B surface antigen trajectory pattern further includes:

[0017] Acquire hepatitis B surface antigen information obtained by multiple tests of multiple second objects, where the second objects are objects with chronic hepatitis B. If the second objects are converted from a chronic hepatitis B state to another state, only the hepatitis B surface antigen information of the second objects when they are in the chronic hepatitis B state is acquired;

[0018] Acquire a second grouping result output by the target group basis trajectory model, wherein the target group basis trajectory model groups the second objects based on the trajectory of the hepatitis B surface antigen information;

[0019] Based on the second grouping result, determining the hepatitis B surface antigen trajectory pattern corresponding to the second object in each group;

[0020] Obtain state transition information of the first object in each of the groups of the second grouping result;

[0021] If within the first group, the proportion of the second object's state converted to the target state is greater than a first preset threshold, determining a correspondence between a first hepatitis B surface antigen trajectory pattern and the target state, the first hepatitis B surface antigen trajectory pattern being the hepatitis B surface antigen trajectory pattern corresponding to the first group;

[0022] Output second prompt information, where the second prompt information is used to indicate a corresponding relationship between the first hepatitis B surface antigen trajectory pattern and the target state.

[0023] In an optional embodiment, after determining the correspondence between the first hepatitis B surface antigen trajectory pattern and the target state, the method further includes:

[0024] Acquiring hepatitis B surface antigen information obtained from multiple tests of a third subject, wherein the third subject is a subject in a chronic hepatitis B state;

[0025] Acquire the target group base trajectory model, and output a third grouping result after grouping the first object and the third object based on the trajectory of the hepatitis B surface antigen information;

[0026] Based on the third grouping result, determining the group to which the third object belongs;

[0027] Based on the hepatitis B surface antigen trajectory pattern of the first object in the group to which the third object belongs, the hepatitis B surface antigen trajectory pattern corresponding to the third object is determined.

[0028] In an optional implementation, after determining the hepatitis B surface antigen trajectory pattern corresponding to the first object in each group based on the first grouping result, the method further includes:

[0029] Acquiring medication information of the first subject in each of the groups;

[0030] If, in the first group, the proportion of the first object's medication information that is the target medication information is greater than a first preset threshold, determining a correspondence between a first hepatitis B surface antigen trajectory pattern and the target medication information, the first hepatitis B surface antigen trajectory pattern being the hepatitis B surface antigen trajectory pattern corresponding to the first group;

[0031] Output third prompt information, where the third prompt information is used to indicate a corresponding relationship between the first hepatitis B surface antigen trajectory pattern and the target medication information.

[0032] In an optional implementation, after determining the hepatitis B surface antigen trajectory pattern corresponding to the first object in each group based on the first grouping result, the method further includes:

[0033] Acquire the state transition of the first object in each of the groups and the baseline information of the first object, wherein the baseline information includes one or more of age, gender, liver cirrhosis information, hepatitis B E antigen information, and hepatitis B surface antigen information;

[0034] If within the first group, the proportion of the first objects' states converted to the target state is greater than a first preset threshold, obtaining a corresponding relationship between the baseline information and the target state;

[0035] Output fourth prompt information, where the fourth prompt information is used to indicate a corresponding relationship between the baseline information and the target state.

[0036] In a second aspect, the present invention provides a device for prompting a hepatitis B surface antigen trajectory pattern, the device comprising:

[0037] A hepatitis B surface antigen information acquisition module, used to acquire hepatitis B surface antigen information obtained by multiple tests of multiple first objects, wherein the first objects are objects with chronic hepatitis B. If the first objects are converted from a chronic hepatitis B state to another state, only the hepatitis B surface antigen information of the first objects when they are in the chronic hepatitis B state is acquired;

[0038] A first grouping result acquisition module, configured to acquire a first grouping result output by a target group base trajectory model, wherein the target group base trajectory model groups the first objects based on a trajectory of the hepatitis B surface antigen information;

[0039] a trajectory pattern determination module, configured to determine, based on the first grouping result, a hepatitis B surface antigen trajectory pattern corresponding to the first object in each group, wherein one group corresponds to one hepatitis B surface antigen trajectory pattern;

[0040] The first prompt module is used to output the corresponding first prompt information for the first object in the group, and the first prompt information is used to indicate the hepatitis B surface antigen trajectory pattern of the first object. Different hepatitis B surface antigen trajectory patterns correspond to different target states, and the target state is the state after the chronic hepatitis B is converted.

[0041] In a third aspect, the present invention provides a medical device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method for prompting a hepatitis B surface antigen trajectory pattern of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0042] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for prompting a hepatitis B surface antigen trajectory pattern of the first aspect or any corresponding embodiment thereof.

[0043] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions, wherein the computer instructions are used to enable a computer to execute the method for prompting a hepatitis B surface antigen trajectory pattern according to the first aspect or any corresponding embodiment thereof.

[0044] The hepatitis B surface antigen trajectory pattern prompt method, device, equipment and storage medium provided in this embodiment can output prompt information of the hepatitis B surface antigen trajectory pattern of the first object, and different hepatitis B surface antigen trajectory patterns correspond to different target states. At this time, based on the target state corresponding to the hepatitis B surface antigen trajectory pattern of the first object, the medication of the first object can be adjusted, or the medication of the first object can be determined to be a suitable drug, thereby guiding the development and improvement of the drug.

[0045] In addition, in the embodiment of the present invention, the group-based trajectory model is used to determine the hepatitis B surface antigen trajectory pattern, which does not require the hepatitis B surface antigen information detection time point of the first object to be consistent, nor does it require the hepatitis B surface antigen information detection time interval to be consistent, which greatly increases the convenience of hepatitis B surface antigen data collection. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the related technologies, the drawings required for use in the specific embodiments or the related technical descriptions will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0047] Figure 1 is a flow chart of a method for prompting a hepatitis B surface antigen trajectory pattern according to an embodiment of the present invention;

[0048] Figure 2 is a schematic diagram of fitting curves of two hepatitis B surface antigen trajectories according to an embodiment of the present invention;

[0049] Figure 3 is a schematic diagram of the change of the number of patients in the target group base trajectory model grouping over time according to an embodiment of the present invention;

[0050] Figure 4 is a schematic diagram of KM survival curves of patients with different trajectory patterns according to an embodiment of the present invention;

[0051] Figure 5is a structural block diagram of a hepatitis B surface antigen trajectory pattern prompting device according to an embodiment of the present invention;

[0052] Figure 6 It is a schematic diagram of the hardware structure of the medical device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0054] According to an embodiment of the present invention, a method embodiment of a prompting method for a hepatitis B surface antigen trajectory pattern is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of executable computer instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0055] In this embodiment, a method for prompting a pattern of a hepatitis B surface antigen trajectory is provided, which can be used for medical equipment. Figure 1 is a flow chart of a method for prompting a pattern of a hepatitis B surface antigen trajectory according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0056] Step S101, obtaining hepatitis B surface antigen (HBsAg) information obtained by multiple tests of multiple first objects, where the first objects are chronic hepatitis B objects. If the first objects are converted from a chronic hepatitis B state to other states, only the hepatitis B surface antigen information of the first objects when they are in the chronic hepatitis B state is obtained.

[0057] The first object may be an experimental animal. Other states are states after the development of chronic hepatitis B (including development toward cure and toward liver cancer), including liver cancer state, cure state, liver cirrhosis state, etc. Different states may be further subdivided, for example, the liver cirrhosis state may be subdivided into the early liver cirrhosis state, the late liver cirrhosis state, etc.

[0058] Step S102: obtaining a first grouping result output by a target group base trajectory model, wherein the target group base trajectory model groups the first objects based on the trajectory of the hepatitis B surface antigen information.

[0059] The trajectory of HBsAg information is the dynamic change process of HBsAg. Group-based trajectory modeling (GBTM) can be used to identify objects with similar development trajectories in a group of objects and classify them into specific groups / classes. GBTM can construct multiple groups of trajectory patterns based on the corresponding longitudinal distribution of HBsAg and output grouping probability values.

[0060] Step S103: based on the first grouping result, determine the hepatitis B surface antigen trajectory pattern corresponding to the first object in each group, wherein one group corresponds to one hepatitis B surface antigen trajectory pattern.

[0061] Specifically, the HBsAg trajectory pattern includes at least: a fast decline pattern and a slow decline pattern. Different HBsAg trajectory patterns correspond to different HBsAg decline speeds.

[0062] Step S104: output corresponding first prompt information for the first object in the group, wherein the first prompt information is used to indicate the hepatitis B surface antigen trajectory pattern of the first object, and different hepatitis B surface antigen trajectory patterns correspond to different target states, and the target state is the state after the chronic hepatitis B is converted.

[0063] The pattern prompt method of the hepatitis B surface antigen trajectory provided in this embodiment can output prompt information of the hepatitis B surface antigen trajectory pattern of the first object, and different hepatitis B surface antigen trajectory patterns correspond to different target states. At this time, based on the target state corresponding to the hepatitis B surface antigen trajectory pattern of the first object, the medication of the first object can be adjusted, or the medication of the first object can be determined to be a suitable drug, thereby guiding the development and improvement of the drug.

[0064] In addition, in the embodiment of the present invention, the group-based trajectory model is used to determine the hepatitis B surface antigen trajectory pattern, which does not require the hepatitis B surface antigen information detection time point of the first object to be consistent, nor does it require the hepatitis B surface antigen information detection time interval to be consistent, which greatly increases the convenience of hepatitis B surface antigen data collection.

[0065] In some optional specific implementations, before obtaining the first grouping result output by the target group base trajectory model, the method further includes:

[0066] Establishing a plurality of initial group basis trajectory models, each of the initial group basis trajectory models having a different number of groups;

[0067] Using the initial group basis trajectory model to perform group fitting on the trajectory of the hepatitis B surface antigen information, to obtain a fitting result and an initial grouping result;

[0068] Calculating an evaluation index of the initial group basis trajectory model based on the fitting result and / or the initial grouping result;

[0069] The target group basis trajectory model is selected from the initial group basis trajectory models based on the evaluation index.

[0070] In the embodiment of the present invention, in order to obtain the development trajectory of the object, it is necessary to determine the number of trajectory groups (i.e., groups) and the trajectory morphology. Adhering to the goal of model simplicity and interpretability, multiple initial group-based trajectory models are generally constructed. These group-based trajectory models are grouped into 2-6 groups, and each model fits linear, square and cubic respectively. By comparing the fitting indicators of different models and the professional interpretability of the trajectory group morphology, the most suitable model is selected. The evaluation indicators of the model include but are not limited to the following indicators:

[0071] (1) BIC: Bayesian information criterion. The closer the BIC is to 0, the better the model fit.

[0072] (2) Average posterior probability: The posterior probability indicates the probability that each object belongs to a certain trajectory group. The average posterior probability is the average of the posterior probabilities of all objects in their assigned trajectory groups and is used to evaluate the grouping quality of the model. It reflects the degree of conformity between the members of the class grouped according to the trajectory and the trajectory, and usually >0.7 is an acceptable standard.

[0073] (3) Proportions per class %: generally not less than 5%.

[0074] (4) Odds of Correct Classification measures the ratio of the probability of correctly classifying into each group. It is generally believed that OCC>5 indicates that the model has a high classification accuracy.

[0075] In this embodiment, 2-6 trajectory models were fitted respectively. Among them, the 6-trajectory model had the lowest BIC (BIC = -49216.64), but the proportion of 2 trajectory groups was less than 5%. The 4-trajectory model and the 5-trajectory model also had a proportion of 1 trajectory group less than 5%. The 2-trajectory model and the 3-trajectory model both met the indicators. Combined with the clinical application practicality, model simplicity and interpretability, the 2-trajectory model was finally selected.

[0076] In some specific implementations, the method provided in the above embodiment further includes a process for determining the correspondence between the hepatitis B surface antigen trajectory pattern and the target state, which is specifically as follows:

[0077] Acquire hepatitis B surface antigen information obtained from multiple tests on multiple second objects, where the second objects are chronic hepatitis B objects. If the second object is converted from a chronic hepatitis B state to another state, only acquire the hepatitis B surface antigen information of the second object when it is in the chronic hepatitis B state.

[0078] A second grouping result output by the target group base trajectory model is obtained, where the target group base trajectory model groups the second objects based on the trajectory of the hepatitis B surface antigen information.

[0079] Based on the second grouping results, the hepatitis B surface antigen trajectory pattern corresponding to the second object in each group is determined.

[0080] Obtain state transition information of the first object in each of the groups of the second grouping result;

[0081] If the proportion of the second object's state converted to the target state in the first group is greater than a first preset threshold, the corresponding relationship between the first hepatitis B surface antigen trajectory pattern and the target state is determined, and the first hepatitis B surface antigen trajectory pattern is the hepatitis B surface antigen trajectory pattern corresponding to the first group. The proportion of the second object's state converted to the target state is the ratio of the number of second objects converted to the target state to the number of all second objects in the first group.

[0082] Output second prompt information, where the second prompt information is used to indicate a corresponding relationship between the first hepatitis B surface antigen trajectory pattern and the target state.

[0083] The second object in the embodiment of the present invention may be different from the first object in the above embodiment, or may be partially the same as, or even completely the same as, the first object in the above embodiment. If they are completely the same, the repeated steps may be omitted.

[0084] In the embodiment of the present invention, by constructing a correspondence between the trajectory pattern of hepatitis B surface antigen, a simple and easily available viral marker, and the target state of the object, it is convenient to predict the target state, thereby guiding the direction of drug development.

[0085] In addition, compared with predicting the target state using only the test results of the object at a single time point, the present application uses the hepatitis B surface antigen trajectory to predict the target state with higher accuracy.

[0086] In some specific embodiments, after determining the correspondence between the first hepatitis B surface antigen trajectory pattern and the target state, the method further includes:

[0087] Acquiring hepatitis B surface antigen information obtained from multiple tests of a third subject, wherein the third subject is a subject in a chronic hepatitis B state;

[0088] Acquire the target group base trajectory model, and output a third grouping result after grouping the first object and the third object based on the trajectory of the hepatitis B surface antigen information;

[0089] Based on the third grouping result, determining the group to which the third object belongs;

[0090] Based on the hepatitis B surface antigen trajectory pattern of the first object in the group to which the third object belongs, the hepatitis B surface antigen trajectory pattern corresponding to the third object is determined.

[0091] In an embodiment of the present invention, the third object may be a newly added object, and the hepatitis B surface antigen trajectory patterns of all or most (proportion greater than a threshold) first objects in the group to which the third object belongs are the hepatitis B surface antigen trajectory patterns corresponding to the third object.

[0092] In some specific implementations, after determining the hepatitis B surface antigen trajectory pattern corresponding to the first object in each group based on the first grouping result, the method further includes:

[0093] Acquiring medication information of the first subject in each of the groups;

[0094] If, in the first group, the proportion of the first object's medication information that is the target medication information is greater than a first preset threshold, determining a correspondence between a first hepatitis B surface antigen trajectory pattern and the target medication information, the first hepatitis B surface antigen trajectory pattern being the hepatitis B surface antigen trajectory pattern corresponding to the first group;

[0095] Output third prompt information, where the third prompt information is used to indicate a corresponding relationship between the first hepatitis B surface antigen trajectory pattern and the target medication information.

[0096] In the embodiment of the present invention, appropriate drugs can be screened through the correspondence between the first hepatitis B surface antigen trajectory pattern and the target medication information, thereby facilitating drug development and improvement.

[0097] In some specific implementations, after determining the hepatitis B surface antigen trajectory pattern corresponding to the first object in each group based on the first grouping result, the method further includes:

[0098] Acquire the state transition of the first subject in each of the groups and the baseline information of the first subject, wherein the baseline information includes one or more of age, gender, liver cirrhosis information, hepatitis B E antigen information, and hepatitis B surface antigen information; the baseline information mainly includes information of the first subject before treatment, or information collected for the first time;

[0099] If within the first group, the proportion of the first objects' states converted to the target state is greater than a first preset threshold, obtaining a corresponding relationship between the baseline information and the target state;

[0100] Output fourth prompt information, where the fourth prompt information is used to indicate a corresponding relationship between the baseline information and the target state.

[0101] In the embodiment of the present invention, the first subject is a chronic hepatitis B patient.

[0102] In a specific embodiment, clinical data of 10,175 patients with chronic hepatitis B who received long-term antiviral treatment from the Search-B cohort (NCT02167503) and were followed up from May 2014 to July 2023 can be collected. The 10,175 patients with chronic hepatitis B who received long-term antiviral treatment were excluded according to the following criteria: patients who developed liver cancer before enrollment and within six months of enrollment; patients whose hepatitis B surface antigen had turned negative at enrollment; patients who had received interferon treatment; patients with less than six months of follow-up. After exclusion, 7,929 patients with chronic hepatitis B who received long-term nucleoside (acid) analogue treatment were obtained. In this embodiment, taking liver cancer as the target state as an example, the diagnosis of liver cancer was regarded as the endpoint of the study. The visit time when the patient was first diagnosed with liver cancer was counted as the time of occurrence of the endpoint event. The 7,929 patients with chronic hepatitis B who received long-term nucleoside (acid) analogue treatment were analyzed using the method provided in the embodiment of the present invention, and the results were obtained. Figure 2 Schematic diagram of the fitting curves of the two HBsAg trajectories shown in FIG. Figure 3 The change of the number of patients in the target group base trajectory model group over time is shown in Figure 1. In addition, the following can be obtained: Figure 4 KM survival curves of patients with different trajectory patterns are shown. The fitting statistics of the group-based trajectory model are shown in Table 1. The evaluation indicators of the target group-based trajectory model are shown in Table 2.

[0103] Table 1. Statistics of fitting of the group basis trajectory model

[0104]

[0105] In addition, this embodiment also analyzes the baseline information of the above 7929 chronic hepatitis B patients who received long-term nucleoside (acid) analog therapy, and obtains the group comparison information shown in Table 3 below.

[0106] Table 3 Comparison of baseline information of chronic hepatitis B patients by group

[0107]

[0108] As can be seen from Table 3, compared with the non-liver cancer group, the patients in the liver cancer group were older at baseline, had a higher proportion of males, a higher proportion of liver cirrhosis, a higher proportion of hepatitis B E antigen negatives, a lower hepatitis B surface antigen level, and a shorter duration of antiviral treatment before enrollment.

[0109] In the present embodiment, a prompting device for the hepatitis B surface antigen trajectory pattern is also provided, and the device is used to implement the above-mentioned embodiments and preferred embodiments, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware is also possible and conceived.

[0110] This embodiment provides a device for prompting a HBsAg trajectory pattern, such as Figure 5 As shown, including:

[0111] The hepatitis B surface antigen information acquisition module 501 is used to acquire the hepatitis B surface antigen information obtained by multiple tests of multiple first objects, wherein the first objects are objects with chronic hepatitis B. If the first objects are converted from the chronic hepatitis B state to other states, only the hepatitis B surface antigen information of the first objects when they are in the chronic hepatitis B state is acquired;

[0112] A first grouping result acquisition module 502 is used to acquire a first grouping result output by a target group base trajectory model, wherein the target group base trajectory model groups the first objects based on the trajectory of the hepatitis B surface antigen information;

[0113] A trajectory pattern determination module 503 is used to determine the hepatitis B surface antigen trajectory pattern corresponding to the first object in each group based on the first grouping result, where one group corresponds to one hepatitis B surface antigen trajectory pattern;

[0114] The first prompt module 504 is used to output the corresponding first prompt information for the first object in the group, and the first prompt information is used to indicate the hepatitis B surface antigen trajectory pattern of the first object. Different hepatitis B surface antigen trajectory patterns correspond to different target states, and the target state is the state after the chronic hepatitis B is converted.

[0115] In some optional embodiments, the prompting device of the hepatitis B surface antigen trajectory pattern further includes:

[0116] A model building module, used to build a plurality of initial group basis trajectory models, each of which has a different number of groups;

[0117] A fitting module, used for grouping and fitting the trajectory of the hepatitis B surface antigen information using the initial group basis trajectory model to obtain a fitting result and an initial grouping result;

[0118] A calculation module, used for calculating the evaluation index of the initial group basis trajectory model based on the fitting result and / or the initial grouping result;

[0119] A selection module is used to select the target group basis trajectory model from the initial group basis trajectory models based on the evaluation index.

[0120] In some optional embodiments, the prompting device of the hepatitis B surface antigen trajectory pattern further includes:

[0121] A first information acquisition module is used to acquire hepatitis B surface antigen information obtained by multiple tests of multiple second objects, where the second objects are objects with chronic hepatitis B. If the second objects are converted from a chronic hepatitis B state to another state, only the hepatitis B surface antigen information of the second objects when they are in the chronic hepatitis B state is acquired;

[0122] A second grouping result acquisition module, configured to acquire a second grouping result output by the target group base trajectory model, wherein the target group base trajectory model groups the second objects based on the trajectory of the hepatitis B surface antigen information;

[0123] A determination module, configured to determine, based on the second grouping result, a hepatitis B surface antigen trajectory pattern corresponding to the second object in each group;

[0124] A second information acquisition module, configured to acquire state transition information of the first object in each of the groups of the second grouping result;

[0125] a first correspondence determination module, configured to determine a correspondence between a first hepatitis B surface antigen trajectory pattern and the target state if a proportion of the state of the second object in the first group being converted to a target state is greater than a first preset threshold, wherein the first hepatitis B surface antigen trajectory pattern is the hepatitis B surface antigen trajectory pattern corresponding to the first group;

[0126] The second prompt module is used to output second prompt information, where the second prompt information is used to indicate the corresponding relationship between the first hepatitis B surface antigen trajectory pattern and the target state.

[0127] In some optional embodiments, the prompting device of the hepatitis B surface antigen trajectory pattern further includes:

[0128] A third information acquisition module is used to acquire hepatitis B surface antigen information obtained by multiple tests on a third subject, wherein the third subject is a subject in a chronic hepatitis B state;

[0129] A third grouping result acquisition module, configured to acquire the target group base trajectory model, and output a third grouping result after grouping the first object and the third object based on the trajectory of the hepatitis B surface antigen information;

[0130] A group determination module, configured to determine the group to which the third object belongs based on the third grouping result;

[0131] A pattern determination module is used to determine the hepatitis B surface antigen trajectory pattern corresponding to the third object based on the hepatitis B surface antigen trajectory pattern of the first object in the group to which the third object belongs.

[0132] In some optional embodiments, the prompting device of the hepatitis B surface antigen trajectory pattern further includes:

[0133] A medication information acquisition module, used to acquire medication information of the first subject in each of the groups;

[0134] A second correspondence determination module is used to determine the correspondence between a first hepatitis B surface antigen trajectory pattern and the target medication information if the proportion of the medication information of the first object in the first group that is the target medication information is greater than a first preset threshold, and the first hepatitis B surface antigen trajectory pattern is the hepatitis B surface antigen trajectory pattern corresponding to the first group;

[0135] The third prompt module is used to output third prompt information, and the third prompt information is used to indicate the corresponding relationship between the first hepatitis B surface antigen trajectory pattern and the target medication information.

[0136] In some optional embodiments, the prompting device of the hepatitis B surface antigen trajectory pattern further includes:

[0137] A baseline information acquisition module, used to acquire the state transition of the first object in each of the groups and the baseline information of the first object, wherein the baseline information includes one or more of age, gender, liver cirrhosis information, hepatitis B E antigen information and hepatitis B surface antigen information;

[0138] a third corresponding relationship determining module, configured to obtain a corresponding relationship between the baseline information and the target state if a proportion of the first objects in the first group being converted to the target state is greater than a first preset threshold;

[0139] The fourth prompt module is used to output fourth prompt information, where the fourth prompt information is used to indicate the corresponding relationship between the baseline information and the target state.

[0140] The further functional description of each of the above modules is the same as that of the above corresponding embodiments and will not be repeated here.

[0141] The hepatitis B surface antigen trajectory pattern prompting device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0142] The embodiment of the present invention also provides a medical device having the above Figure 5 The HBsAg trajectory pattern shown is a prompt device.

[0143] See also Figure 6 , Figure 6 is a schematic diagram of the structure of a medical device provided by an optional embodiment of the present invention, such as Figure 6 As shown, the medical device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the medical device, including instructions stored in or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Figure 6 A processor 10 is taken as an example.

[0144] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0145] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0146] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the medical device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the medical device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0147] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0148] The medical device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 6 The example of connecting through bus is taken in the following.

[0149] The input device 30 can receive input digital or character information, and generate key signal input related to the user settings and function control of the medical device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator bar, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0150] The medical device also includes a communication interface for the medical device to communicate with other devices or a communication network.

[0151] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0152] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0153] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for prompting a hepatitis B surface antigen trajectory pattern, characterized in that: The method comprises: Acquire hepatitis B surface antigen information obtained by multiple tests of multiple first objects, where the first objects are objects with chronic hepatitis B. If the first objects are converted from a chronic hepatitis B state to another state, only the hepatitis B surface antigen information of the first objects when they are in the chronic hepatitis B state is acquired; Acquire a first grouping result output by a target group basis trajectory model, wherein the target group basis trajectory model groups the first objects based on the trajectory of the hepatitis B surface antigen information; Based on the first grouping result, determining the hepatitis B surface antigen trajectory pattern corresponding to the first object in each group, where one group corresponds to one hepatitis B surface antigen trajectory pattern; For the first object in the group, the corresponding first prompt information is output, and the first prompt information is used to indicate the hepatitis B surface antigen trajectory pattern of the first object. Different hepatitis B surface antigen trajectory patterns correspond to different target states, and the target state is the state after the chronic hepatitis B is converted.

2. The method according to claim 1, characterized in that The hepatitis B surface antigen trajectory mode at least includes: a fast decline mode and a slow decline mode.

3. The method according to claim 1, characterized in that Before obtaining the first grouping result output by the target group base trajectory model, the method further includes: Establishing a plurality of initial group basis trajectory models, each of the initial group basis trajectory models having a different number of groups; Using the initial group basis trajectory model to perform group fitting on the trajectory of the hepatitis B surface antigen information, to obtain a fitting result and an initial grouping result; Calculating an evaluation index of the initial group basis trajectory model based on the fitting result and / or the initial grouping result; The target group basis trajectory model is selected from the initial group basis trajectory models based on the evaluation index.

4. The method according to claim 1, characterized in that Also includes: Acquire hepatitis B surface antigen information obtained by multiple tests of multiple second objects, where the second objects are objects with chronic hepatitis B. If the second objects are converted from a chronic hepatitis B state to another state, only the hepatitis B surface antigen information of the second objects when they are in the chronic hepatitis B state is acquired; Acquire a second grouping result output by the target group basis trajectory model, wherein the target group basis trajectory model groups the second objects based on the trajectory of the hepatitis B surface antigen information; Based on the second grouping result, determining the hepatitis B surface antigen trajectory pattern corresponding to the second object in each group; Obtaining state transition information of the first object in each of the groups of the second grouping result; If within the first group, the proportion of the second object's state converted to the target state is greater than a first preset threshold, determining a correspondence between a first hepatitis B surface antigen trajectory pattern and the target state, the first hepatitis B surface antigen trajectory pattern being the hepatitis B surface antigen trajectory pattern corresponding to the first group; Output second prompt information, where the second prompt information is used to indicate a corresponding relationship between the first hepatitis B surface antigen trajectory pattern and the target state.

5. The method according to claim 1, characterized in that After determining the correspondence between the first hepatitis B surface antigen trajectory pattern and the target state, the method further includes: Acquiring hepatitis B surface antigen information obtained from multiple tests of a third subject, wherein the third subject is a subject in a chronic hepatitis B state; Acquire the target group base trajectory model, and output a third grouping result after grouping the first object and the third object based on the trajectory of the hepatitis B surface antigen information; Based on the third grouping result, determining the group to which the third object belongs; Based on the hepatitis B surface antigen trajectory pattern of the first object in the group to which the third object belongs, the hepatitis B surface antigen trajectory pattern corresponding to the third object is determined.

6. The method according to claim 1, characterized in that After determining the hepatitis B surface antigen trajectory pattern corresponding to the first object in each group based on the first grouping result, the method further includes: Acquiring medication information of the first subject in each of the groups; If, in the first group, the proportion of the first object's medication information that is the target medication information is greater than a first preset threshold, determining a correspondence between a first hepatitis B surface antigen trajectory pattern and the target medication information, the first hepatitis B surface antigen trajectory pattern being the hepatitis B surface antigen trajectory pattern corresponding to the first group; Output third prompt information, where the third prompt information is used to indicate a corresponding relationship between the first hepatitis B surface antigen trajectory pattern and the target medication information.

7. The method according to claim 1, characterized in that After determining the hepatitis B surface antigen trajectory pattern corresponding to the first object in each group based on the first grouping result, the method further includes: Acquire the state transition of the first object in each of the groups and the baseline information of the first object, wherein the baseline information includes one or more of age, gender, liver cirrhosis information, hepatitis B E antigen information, and hepatitis B surface antigen information; If within the first group, the proportion of the first objects' states converted to the target state is greater than a first preset threshold, obtaining a corresponding relationship between the baseline information and the target state; Output fourth prompt information, where the fourth prompt information is used to indicate a corresponding relationship between the baseline information and the target state.

8. A device for prompting a hepatitis B surface antigen trajectory pattern, characterized in that: The device comprises: A hepatitis B surface antigen information acquisition module, used to acquire hepatitis B surface antigen information obtained by multiple tests of multiple first objects, wherein the first objects are objects with chronic hepatitis B. If the first objects are converted from a chronic hepatitis B state to another state, only the hepatitis B surface antigen information of the first objects when they are in the chronic hepatitis B state is acquired; A first grouping result acquisition module, configured to acquire a first grouping result output by a target group base trajectory model, wherein the target group base trajectory model groups the first objects based on a trajectory of the hepatitis B surface antigen information; a trajectory pattern determination module, configured to determine, based on the first grouping result, a hepatitis B surface antigen trajectory pattern corresponding to the first object in each group, wherein one group corresponds to one hepatitis B surface antigen trajectory pattern; The first prompt module is used to output the corresponding first prompt information for the first object in the group, and the first prompt information is used to indicate the hepatitis B surface antigen trajectory pattern of the first object. Different hepatitis B surface antigen trajectory patterns correspond to different target states, and the target state is the state after the chronic hepatitis B is converted.

9. A medical device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 7.

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