WO2023184976A1

WO2023184976A1 - Medical data management method and system, device, medium, and computer program product

Info

Publication number: WO2023184976A1
Application number: PCT/CN2022/129182
Authority: WO
Inventors: 段琦; 张少霆
Original assignee: 上海商汤智能科技有限公司
Priority date: 2022-03-29
Filing date: 2022-11-02
Publication date: 2023-10-05
Also published as: CN114707030A

Abstract

A medical data management method and system, a device, a medium, and a computer program product. The medical data management method comprises: detecting a login to a data management platform, wherein the data management platform is used for managing medical data of a target object, and the medical data of the target object comprises at least one of clinical data of the target object and bioomics data of the target object; and in response to a preset operation on the data management platform, performing data processing matching the preset operation on the medical data. According to the medical data management method, a user can conveniently manage medical data in a data management platform.

Description

Medical data management methods and systems, equipment, media, computer program products

This application claims priority to the Chinese patent application filed with the China Patent Office on March 29, 2022, with application number 202210325624.5 and application name "Medical Data Management Methods and Systems, Equipment, and Media", the entire content of which is incorporated by reference in in this application.

Technical field

This application relates to the field of data management technology, and in particular to a medical data management method and system, equipment, media, and computer program products.

Background technique

In clinical scientific research work, medical data of case samples are often efficiently managed and analyzed. However, the target does not have a visualization system that can be used for medical data management. As a result, the clinical research team will spend a lot of manpower, material resources and time in data management. The cost of data management for the clinical research team is relatively high.

Contents of the invention

This application provides at least one medical data management method and system, equipment, media, and computer program products.

This application provides a medical data management method, including: detecting a login to a data management platform, wherein the data management platform is used to manage the medical data of the target object, and the medical data of the target object includes the clinical data of the target object and At least one of the biological omics data of the target object; in response to a preset operation on the data management platform, perform data processing matching the preset operation on the medical data.

Therefore, after detecting the login to the data management platform, according to the preset operations on the data management platform, the medical data can be managed in a manner that matches the preset operations, compared to the manual management of paper and other medical data. In other words, the former can reduce data management costs.

Wherein, in response to a preset operation on the data management platform, performing data processing on the medical data that matches the preset operation, including: in response to a data upload operation on the data management platform, uploading the medical data of at least one target object to the data management platform; and/or, in response to the data management operation on the data management platform, perform data management matching the data management operation on the medical data in the data management platform.

Therefore, medical data can be uploaded to the data management platform to facilitate subsequent management of medical data based on data management operations.

Among them, data management includes at least one of the following: displaying platform data on the data management platform, retrieving medical data on the data management platform, analyzing medical data on the data management platform, statistics on subject information in the data management platform, and searching for data. Manage the information of genetic testing files in the platform and display the information of the created target data set.

Therefore, by providing multiple data management methods, the flexibility of data management can be improved.

Wherein, in response to the data management operation on the data management platform, performing data management on the medical data in the data management platform that matches the data management operation, including: in response to the selection operation of the retrieval module on the data management platform, displaying the data The search interface of the management platform; obtains the search conditions entered in the search interface, and retrieves several pieces of medical data that match the search conditions in the data management platform as the first target medical data; displays the relevant first target medical data on the search interface target information.

Therefore, by matching the corresponding medical data according to the input search conditions, and displaying the target information of the medical data, it is convenient to view the corresponding medical data.

Wherein, obtaining the search conditions input in the search interface includes: obtaining the search conditions of at least one search dimension input in the search interface, wherein at least one search dimension includes at least one of the target object, gene and mutation; displaying it on the search interface The target information related to the first target medical data includes: displaying the target information related to the first target medical data according to at least one feedback dimension on the search interface, wherein the at least one feedback dimension includes the target object, gene and mutation. At least one.

Therefore, by providing at least one retrieval dimension and providing at least one feedback dimension, the retrieval process is made more flexible.

Wherein, in response to the data management operation on the data management platform, performing data management on the medical data in the data management platform that matches the data management operation, and also includes: in response to the data selection operation on the retrieval interface, the selected at least A first target medical data is saved as the target queue; in response to the selection operation of the analysis module on the data management platform, the medical data of the target queue is analyzed to obtain the medical data analysis results of the target queue; the medical data analysis of the target queue is displayed As a result, the medical data analysis result is at least one of the following: the cohort data statistics of the target cohort, the cohort comparison between the target cohort and the reference cohort, the genetic map of the target cohort, and the survival analysis results of the target cohort.

Therefore, obtaining at least one data analysis result by analyzing the target cohort can improve the diversity of data analysis.

Wherein, in response to the data management operation on the data management platform, performing data management on the medical data in the data management platform that matches the data management operation, including: in response to the data selection operation on the retrieval interface, the selected at least A first target medical data is saved as a target data set; in response to a selection operation of the user data module on the data management platform, information of the created at least one target data set is obtained and displayed, wherein the at least one target data set includes the target object cohort and/or biomarker cohort.

Therefore, data can be managed by displaying the target data set for data selection.

Among them, in response to the data management operation on the data management platform, performing data management on the medical data in the data management platform that matches the data management operation includes: in response to the selection operation of the platform viewing module on the data management platform, obtaining The platform data situation of the data management platform, and the platform data situation is displayed on the platform viewing interface of the data management platform; among them, the platform data situation includes at least one of the following data situations: the overall data situation of the data management platform, clinical data obtained based on clinical data statistics Data situation, biological data situation obtained based on biomics data statistics; or, in response to the selection operation of the data storage module on the data management platform, display the data storage interface of the data management platform; obtain the file input on the data storage interface information, and search for several genetic testing files that match the file information in the data management platform; display the information of several genetic testing files on the data storage interface.

Therefore, by displaying the platform data situation of the data management platform, the overall data situation can be easily understood. In addition, by displaying the data storage interface of the data management platform, the corresponding genetic testing file information can be easily understood.

Among them, detecting a login to the data management platform includes: receiving an access request, where the access request contains login information; in response to passing the verification of the login information, issuing a web interface of the data management platform; wherein the preset operation is performed by the user Implemented on the web interface displayed by the terminal.

Therefore, by performing preset operations on the web interface, the data in the data management platform can be managed.

This application provides a data management platform, including: an operation detection sub-module, used to detect login to the data management platform, wherein the data management platform is used to manage the medical data of the target object, and the medical data of the target object includes At least one of the target object's clinical data and the target object's biomics data; a data processing submodule for responding to a preset operation on the data management platform, performing data processing on the medical data that matches the preset operation .

This application provides an electronic device, including a memory and a processor. The processor is used to execute program instructions stored in the memory to implement the above medical data management method.

The present application provides a computer-readable storage medium on which program instructions are stored. When the program instructions are executed by a processor, the above medical data management method is implemented.

The present application provides a computer program product, which includes a computer readable code, or a computer readable storage medium carrying the computer readable code. When the computer readable code is run in a processor of an electronic device, the electronic device The processor in the device executes the above medical data management method.

The above scheme, after detecting the login to the data management platform, can perform data management on medical data that matches the preset operations according to the preset operations on the data management platform. Compared with the manual management of paper and other medical data, , the former can reduce data management costs.

It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only, and do not limit the present application.

Description of drawings

The accompanying drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present application, and together with the description, are used to explain the technical solutions of the present application.

Figure 1 is a schematic flow chart of an embodiment of the medical data management method of the present application;

Figure 2 is a schematic diagram showing the display of the data cockpit interface according to an embodiment of the medical data management method of the present application;

Figure 3 is a first schematic diagram showing the data retrieval interface of the data management platform according to an embodiment of the medical data management method of the present application;

Figure 4 is a schematic diagram showing the retrieval conditions of the target object dimension according to an embodiment of the medical data management method of the present application;

Figure 5 is a schematic diagram illustrating the search conditions of the gene dimension according to an embodiment of the medical data management method of the present application;

Figure 6 is a schematic diagram illustrating the retrieval conditions of the mutation dimension according to an embodiment of the medical data management method of the present application;

Figure 7 is a schematic diagram showing that the feedback dimension is the gene dimension according to an embodiment of the medical data management method of the present application;

Figure 8 is a schematic diagram showing the results of an embodiment of the medical data management method of the present application when the feedback dimension is the mutation dimension;

Figure 9 is a first display schematic diagram showing a user data interface according to an embodiment of the medical data management method of the present application;

Figure 10 is a second display schematic diagram of a user data interface according to an embodiment of the medical data management method of the present application;

Figure 11 is a third display schematic diagram of a user data interface according to an embodiment of the medical data management method of the present application;

Figure 12 is a schematic diagram showing a data storage interface according to an embodiment of the medical data management method of the present application;

Figure 13 is a first schematic diagram showing the data analysis interface according to an embodiment of the medical data management method of the present application;

Figure 14 is a schematic diagram showing a queue status display interface according to an embodiment of the medical data management method of the present application;

Figure 15 is a first schematic diagram showing a comparison display interface according to an embodiment of the medical data management method of the present application;

Figure 16 is a second schematic diagram showing a comparison display interface according to an embodiment of the medical data management method of the present application;

Figure 17 is a schematic diagram showing a gene map display interface according to an embodiment of the medical data management method of the present application;

Figure 18 is a schematic diagram showing a survival analysis display interface according to an embodiment of the medical data management method of the present application;

Figure 19 is a first schematic diagram showing the subject interface according to an embodiment of the medical data management method of the present application;

Figure 20 is a second schematic diagram showing the subject interface according to an embodiment of the medical data management method of the present application;

Figure 21 is a schematic structural diagram of an embodiment of the data management platform of the present application;

Figure 22 is a schematic structural diagram of an embodiment of the electronic device of the present application;

Figure 23 is a schematic structural diagram of an embodiment of a computer-readable storage medium of the present application.

Detailed ways

The solutions of the embodiments of the present application will be described in detail below with reference to the accompanying drawings.

In the following description, specific details such as specific system structures, interfaces, technologies, etc. are provided for the purpose of explanation and not limitation, so as to provide a thorough understanding of the present application.

The term "and/or" in this article is just an association relationship that describes related objects, indicating that three relationships can exist. For example, A and/or B can mean: A exists alone, A and B exist simultaneously, and they exist alone. B these three situations. In addition, the character "/" in this article generally indicates that the related objects are an "or" relationship. In addition, "many" in this article means two or more than two. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, and C, which can mean including from A, Any one or more elements selected from the set composed of B and C.

Please refer to Figure 1, which is a schematic flow chart of an embodiment of the medical data management method of the present application. Specifically, it can include the following steps:

Step S11: Login to the data management platform is detected, where the data management platform is used to manage the medical data of the target object. The medical data of the target object includes at least one of the clinical data of the target object and the biomics data of the target object. One.

The data management platform is a visual platform that can realize operations such as storage of medical data and visual management and analysis, and can assist medical workers to complete related research work more efficiently. Clinical data can be data with clinical manifestations, and biomics data can be genetic data. Detecting the login to the data management platform may specifically be detecting the user's login to the data management platform.

Step S12: In response to the preset operation on the data management platform, perform data management on the medical data that matches the preset operation.

Specifically, the data management platform may include multiple modules, and different modules may have different functions. The preset operation on the data management platform may be a selection operation on a certain module on the data management platform, etc.

The above solution, after detecting the login to the data management platform, can conduct data management of medical data that matches the preset operations according to the preset operations on the data management platform, compared with manual management of paper and other medical data. In terms of performance, the former can reduce data management costs.

In some disclosed embodiments, the above step S11 may include the following steps:

Receive access request. Among them, the access request contains login information. The access request may be sent by the user terminal. The preset login information can be an account number, a password, a user's fingerprint, a user's facial features, or a specific voice command. In other disclosed embodiments, there is no need to log in. After receiving the operation instruction to start the data management platform, it is determined that the user has accessed the data management platform.

In response to the verification of the login information passing, the web interface of the data management platform is delivered. The method may be to deliver a web interface of the data management platform to the user terminal. Among them, the preset operation is implemented by the user on the web interface displayed on the user terminal.

By users performing preset operations on the web interface, the data in the data management platform can be managed.

In some disclosed embodiments, the above step S12 may include any one or more of the following steps:

In response to the data upload operation on the data management platform, medical data of at least one target object is uploaded to the data management platform. Specifically, users upload genomic data and clinical medical data to the data management platform through online web pages for data storage and management of medical data.

In response to the data management operation on the data management platform, data management matching the data management operation is performed on the medical data in the data management platform. Data management operations may specifically be selection operations on various modules of the data management platform, etc.

Users can upload medical data to the data management platform to facilitate subsequent management of medical data based on data management operations.

In some disclosed embodiments, data management includes at least one of the following: displaying platform data status of the data management platform, retrieving medical data on the data management platform, analyzing medical data on the data management platform, and statistics on topics in the data management platform. Information, find information about genetic testing files in the data management platform, and display information about the created target data set. Among them, the target data set can be created by the user. By providing multiple data management methods, the flexibility of data management can be improved.

In some disclosed embodiments, in response to the data management operation on the data management platform, the way to perform data management on the medical data in the data management platform that matches the data management operation may be:

In response to the selection operation of the platform viewing module on the data management platform, the platform data situation of the data management platform is obtained, and the platform data situation is displayed on the platform viewing interface of the data management platform. Optionally, after detecting that the user clicks the data cockpit button on the main interface, it is determined that the selection operation of the platform viewing module on the data management platform is detected. Please also refer to FIG. 2 . FIG. 2 is a schematic diagram showing a data cockpit interface according to an embodiment of the medical data management method of the present application. As shown in Figure 2, the data management platform provided by the embodiment of the present disclosure can be a clinical omics data intelligence platform. The main interface includes a data cockpit button, a subject overview button, a data retrieval button, a data analysis button, a data storage button and a user interface. data button. The data cockpit button corresponds to the viewing module, the subject overview button corresponds to the subject overview module, the data retrieval button corresponds to the retrieval module, the data analysis button corresponds to the data analysis module, the data storage button corresponds to the data storage module and the my data button corresponds to the user data module. Click each The buttons corresponding to the modules enter the display interface corresponding to each module. For example, the user can enter the data cockpit interface by clicking the data cockpit button.

Among them, the overall data situation of the data management platform, the clinical data situation based on clinical data statistics, and the biological data situation based on biomics data statistics.

In some disclosed embodiments, the clinical data of the target object may include at least one of basic information and disease information of the target object. In the embodiment of this disclosure, the clinical data of the target object includes two basic information and disease information of the target object as an example. The basic information of the target object may specifically be at least one attribute information among the target object's identification information, current age, and gender. Among them, the identification information of the target object can be name, number, etc.

Wherein, when the target object has passed away, the current age of the target object may be the age at the time of death. The disease information may include at least one attribute information of disease type, lesion, and disease age. Among them, disease types include any disease such as lung cancer and liver cancer. The lesion can be the primary lesion, that is, the location where the tumor causing the disease originates. For example, when the disease type is lung cancer, and because the tumor of lung cancer originates from the lungs and the tumor has not metastasized, the lesion is the lungs. Age of onset can be the age at which a certain disease type is diagnosed.

The biological omics data of the target object may include at least one of the following: genetic data of the target object and data related to samples of the target object. Among them, biomics data is obtained by testing samples. Specifically, the sample can be a DNA fragment, and the detection method includes gene sequencing and other methods.

The genetic data includes at least one of genetic information of the target object and genetic detection files. Among them, the genetic testing file contains the genetic testing results obtained by performing genetic testing on the sample. Optionally, the genetic test results obtained by performing genetic testing on the sample include the genetic information of the target object. The genetic information may include at least one attribute information among genes detected in the sample, mutated genes, gene mutation types, and gene mutation results. Among them, the gene sequencing platform can perform gene sequencing on samples submitted for inspection and obtain gene sequencing results. Among them, the gene sequencing results include genetic information. Genes can include mutated genes as well as non-mutated genes. Among them, the mutant gene refers to the gene that has mutated. Gene mutation types generally include deletion mutations, frameshift mutations, and insertion mutations. Gene mutation results are further subdivisions of gene mutation types. For example, gene mutation results can include inframe-deletion (deletion mutation without frameshift mutation), missense-variants (missense mutation), intron-variant (inclusion submutation) and so on.

As shown in Figure 2, the overall data situation may include at least one of the following: the total number of target objects, the number of new target objects within the preset time period, the total number of genes, the number of mutated genes, the number of subjects, and the number of genetic testing files. Among them, the topics are set by the user, and each topic is associated with the medical data of at least one target object. For example, the user can establish a research topic on the risk of cancer caused by the living environment of the target object. In this topic, a total of M target objects are studied. The preset time period may be a period of time before the current platform data of the data management platform is obtained, such as one week, one month, three months, etc. The total number of genes is the sum of the number of genes corresponding to all target objects. In the process of calculating the total number of genes, if the same gene is in different target objects, the gene is recorded as one. The number of mutated genes is the sum of the number of mutated genes corresponding to all target objects. The number of genetic testing files is also the total number of genetic testing files corresponding to all target objects. Specifically, it can be the memory size occupied by the genetic testing files.

The clinical data may include at least one of the following: a first statistic about disease type, a second statistic about lesions, a third statistic about disease age, and a fourth statistic about gender.

The first statistical information about the disease type may be about high-frequency mutated genes in the disease type. Highly mutated genes refer to mutated genes with a high mutation frequency in target subjects suffering from disease types, such as the top N mutated genes with the highest mutation frequency. The method of obtaining high-frequency mutated genes may be to compare the gene detection results of each target subject under the disease type with respect to the location of the disease type with the gene detection results of other locations other than the disease type, and obtain information about the disease type. Highly mutated genes in disease types. The method of obtaining high-frequency mutated genes can also be to count the mutated genes of target subjects suffering from the disease type, and obtain the number of target subjects in which each mutated gene is located. Based on the number of target subjects in which each mutated gene is located, the number of target subjects is obtained. Highly mutated genes under disease types.

The first statistical result about the disease type may also be the statistics of the number of target objects corresponding to different disease types. For example, different disease types include liver cancer, lung cancer, and esophageal cancer. The first statistical result about the disease type is the number of target subjects suffering from liver cancer, the number of target subjects suffering from lung cancer, and the number of targets suffering from esophageal cancer in the data management platform. The number of objects.

The second statistical result about the lesion may be the statistical result about the number of target objects about the primary lesion. For example, the primary tumor can be breast, lung, or liver. The second statistical result about the tumor is the number of target subjects whose primary tumor is breast, the number of target subjects whose primary tumor is lung, and the number of target subjects whose primary tumor is liver. The number of target objects.

The third statistics about the age of disease may be to count the ages of disease of all target subjects to obtain an overall third statistical situation, or it may be to count the ages of disease of target subjects with different disease types to obtain different diseases. Type of tertiary statistics regarding age at onset of illness.

The fourth statistical situation about gender may be to count the genders of all target objects to obtain the overall fourth statistical situation, or it may be to count the genders of target objects of different disease types to obtain the fourth statistical situation about gender for different disease types. Statistics.

The biological data obtained from the statistics of genetic data includes at least one of the following: the genetic data obtained from the statistics of genetic data, and the sample data obtained from the statistics of related data of the sample. The relevant data of the sample includes at least one attribute information of sample type and sample detection location. The sample type includes at least one of normal solid tissue, normal blood, tumor tissue, recurrent tumor tissue, metastatic tumor tissue, and new metastatic tumor tissue. That is, sample types are classified based on where the sample is obtained from the target object. The location for sample testing is the institution that conducts genetic testing on samples or the department of the hospital that conducts genetic testing on samples.

Among them, the genetic data includes at least one of the following: a fifth statistical situation about gene mutation types, a sixth statistical situation about gene mutation results. As mentioned above, the data management platform contains the genetic information of the target object. By counting the genetic information of each target object, the fifth statistical information about gene mutation types and the sixth statistical information about gene mutation results can be obtained.

Wherein, the sample data situation may include at least one of the following: a seventh statistical situation regarding the sample type and an eighth statistical situation regarding the sample detection location. Among them, the data management platform stores the type of samples of each target object and the detection location of the samples. Through statistics, the sample data is obtained.

In some disclosed embodiments, at least some of the data situations are changeable statistical situations. Modifiable statistics can be statistics that can be adjusted. A configuration item that displays several data situations and displays corresponding attribute information for changeable statistics. That is, users can adjust the displayed changeable statistics through this configuration item. For example, the configuration item allows the user to change the disease type. If the user selects the disease type as liver cancer, then the changeable statistics are statistics corresponding to liver cancer.

Among them, after displaying the platform data to the user, the following steps may also be included:

In response to the user's third preset operation on the configuration item, the attribute information corresponding to the changeable statistics is adjusted, and the changeable statistics are re-calculated and displayed based on the adjusted attribute information. Among them, the attribute information here can be disease type. The configuration item may be a drop-down button for the user to adjust the attribute information. The user clicks the drop-down button to display the attribute information that the user can select. After receiving the user's instruction to select one of the attribute information, it is determined that the user's selection of the configuration item is detected. Third default operation.

By displaying the platform data of the data management platform, users can conveniently understand the overall data situation. In addition, by displaying the data storage interface of the data management platform, users can conveniently understand the corresponding genetic testing file information.

In some disclosed embodiments, in response to the user's data management operation on the data management platform, the way to perform data management on the medical data in the data management platform that matches the data management operation may be:

In response to the selection operation of the retrieval module on the data management platform, the retrieval interface of the data management platform is displayed. Then, the search conditions entered on the search interface are obtained, and several pieces of medical data matching the search conditions are retrieved in the data management platform as the first target medical data. Finally, the target information related to the first target medical data is displayed on the retrieval interface. By matching the corresponding medical data according to the input search conditions, and displaying the target information of the medical data, it is convenient to view the corresponding medical data. Among them, the selection operation of the search module can be made by the user, and the search conditions on the search interface can also be input by the user. Please also refer to FIG. 3 . FIG. 3 is a first schematic diagram showing the data retrieval interface of the data management platform according to an embodiment of the medical data management method of the present application.

Among them, the method of obtaining the search conditions entered in the search interface can be:

Get the search conditions of at least one search dimension entered in the search interface. As shown in Figure 3, at least one search dimension includes at least one of a target object, a gene, and a mutation. Specifically, a search interface is displayed. Wherein, the first sub-area of the retrieval area in the retrieval interface is provided with first dimension items corresponding to each retrieval dimension. Among them, the first dimension items can be selected by the user. In response to the first selection operation, the retrieval dimension corresponding to the selected first dimension item is used as the target retrieval dimension, and the retrieval conditions of the target retrieval dimension input in the second sub-area of the retrieval area are obtained. That is, the user can select the first dimension item corresponding to the search dimension on the displayed search interface, and use the search dimension corresponding to the first dimension item selected by the user as the target search dimension, and obtain the user's input in the second sub-area of the search area The search conditions of the target search dimension.

Among them, the method of obtaining the retrieval conditions of the target retrieval dimension input in the second sub-area of the retrieval area may be:

Several attribute items associated with the target retrieval dimension are displayed in the second sub-area. And obtain the attribute information entered or selected in at least one attribute item respectively as the retrieval conditions of the target retrieval dimension.

The retrieval conditions of the target object include at least one of the following attribute information: target object identification, target object name, cohort to which the target object belongs, lesion, gender, survival status, age of illness, survival time, cause of death, tumor pathological classification, and tumor pathological stage. , tumor pathological grade, whether it has received treatment, sample source, sample type, technology used for sample detection, and variation analysis. Please also refer to FIG. 4 , which shows a schematic diagram showing the search conditions of the target object dimension according to an embodiment of the medical data management method of the present application. As shown in Figure 4, after selecting the target object dimension, the second sub-area displays several attribute items of the target object dimension.

The queue to which the target object belongs can be a user-created queue for observation and research, or it can be a subject queue. The source of the sample is specifically the source of the biological sample, that is, which department the target subject's case comes from. The sample type can specifically be a biological sample tissue type, including solid and non-solid. For example, if a tumor has a clear boundary, it is a solid. If the tumor has no clear boundary, it is a non-solid. The technology used for sample detection is specifically experimental technology, which can be the sequencing technology used for gene sequencing of samples, such as WGS (whole-genome shotgun, whole genome sequencing) technology, WES (whole exome sequencing, whole exome sequencing) Technology, Panel (target sequence capture high-throughput sequencing) technology. Variation analysis may specifically be type analysis of genetic variation. Exemplarily, the type of genetic variation may be copy number variation, etc.

The gene retrieval conditions include at least one of the following attribute information: gene name, gene type and whether it belongs to cancer. The gene type may be the result of classifying genes, where the gene type may include coding genes, pseudogenes, etc. For example, the coding gene can be IGC gene, etc., and the pseudogene can be IGC pseudogene, etc. Whether it is a cancer can refer to whether the gene is an oncogene. Please also refer to FIG. 5 , which shows a schematic diagram showing gene-dimensional search conditions according to an embodiment of the medical data management method of the present application. As shown in Figure 5, after the user selects the gene dimension, the second sub-area displays several attribute items of the gene dimension.

The search conditions for mutations include at least one of the following attribute information: mutation gene identification, degree of impact of mutation on gene function, mutation type, and mutation result. The mutant gene identifier may be a genome change, where the genome change is specifically a DNA fragment subjected to gene sequencing. Please also refer to FIG. 6 , which shows a schematic diagram showing the search conditions of the mutation dimension according to an embodiment of the medical data management method of the present application. As shown in Figure 6, after selecting the mutation dimension, the second sub-area displays several attribute items of the mutation dimension.

In some disclosed embodiments, the method of displaying the target information related to the first target medical data on the search interface may be:

On the retrieval interface, target information related to the first target medical data is displayed according to at least one feedback dimension. Wherein, at least one feedback dimension includes at least one of a target object, a gene and a mutation. Among them, the target information corresponding to different feedback dimensions can be different. The retrieval process is made more flexible by providing at least one retrieval dimension and providing at least one feedback dimension.

Among them, the retrieval interface displays the second dimension items corresponding to each feedback dimension. The second dimension item may be a button for the user to select a feedback dimension. In response to the second selection operation on the retrieval interface, the feedback dimension corresponding to the selected second dimension item is used as the target feedback dimension, and the target information corresponding to the target feedback dimension is displayed in the result sub-area of the result display area of the retrieval interface.

Wherein, in response to at least one feedback dimension including the target object, the target medical data is displayed with the target object as the dimension, and/or several first attribute statistical results are displayed. As shown in Figure 2, the result sub-area of the result display area of the search interface in Figure 2 displays target information corresponding to the target object as the feedback dimension. As shown in Figure 2, several first attribute statistical results include statistical results obtained from at least one of the lesions, tumor types, subjects, and gender. The tumor type can be primary tumor type, metastatic tumor type and unknown type. Among them, the target medical data displayed with the target object as the dimension includes the specific information of each target object retrieved. The specific information of each target object can include the target object identification, cohort, lesion, gender, number of genetic testing files, number of original data, number of comparison data, SNV (Single Nucleotide Variant, single nucleotide variant) and Indel (Insertion - At least one of the number of deletions (insertion and deletion markers), the number of CNV (Copy Number Variation), the number of mutations, and the number of genes. The number of original data is the number of files of gene sequencing results corresponding to the target object's tumor tissue. The comparison data is the number of files of gene sequencing results corresponding to the normal tissue of the target object. The number of SNV and Indel refers to the SNV and Indel detection methods. The number of files obtained by detecting the sample of the target object. The number of CNV refers to the number of files of gene sequencing results obtained by detecting the sample of the target object through the CNV detection method. The number of mutations refers to the number of genes with genetic mutations detected, and the number of genes refers to the number of genes detected.

In response to at least one feedback dimension including genes, the target medical data is displayed with genes as dimensions, and/or several second attribute statistical results are displayed. Please also refer to FIG. 7 , which is a schematic diagram illustrating that the feedback dimension is the gene dimension according to an embodiment of the medical data management method of the present application. The result sub-area of the result display area of the search interface in Figure 7 displays the target information corresponding to genes as the feedback dimension. As shown in Figure 7, several second attribute statistical results include at least one of the following: statistical results on the number of target objects of several mutated genes whose mutation frequencies meet preset requirements, and survival curves for each target object in the target medical data. Several mutant genes whose mutation frequency meets the preset requirements may be the top N mutant genes with the highest mutation frequency. The target medical data displayed in the gene dimension includes specific information of the gene. The specific information of the gene may be the specific information of all genes included in the data management platform. In other disclosed embodiments, the specific information of the gene may also be the specific information of the gene that meets the search conditions. The specific information of each gene includes gene identification, gene name, related target objects in the search results, related target objects in the platform, the number of copy number amplifications, the number of copy number deletions, the number of mutations, and whether it is cancer.

In response to at least one feedback dimension including a mutation, display the target medical data with the mutation as a dimension, and/or display several third attribute statistical results. Please also refer to FIG. 8 . FIG. 8 is a schematic diagram showing the results of an embodiment of the medical data management method of the present application when the feedback dimension is the mutation dimension. The result sub-area of the result display area of the search interface in Figure 8 displays the target information corresponding to mutation as the feedback dimension. As shown in Figure 8, several third attribute statistical results include survival curves for each target object in the target medical data. The target medical data displayed in the mutation dimension can include specific information of each mutated gene in the data management platform. The specific information of each mutated gene may include at least one of genome changes, gene mutation types, amino acid changes, gene mutation results, related target objects in the search results, related target objects in the data management platform, and mutation effects. Among them, genomic changes refer to the DNA fragments used for genetic testing. For example, the amino acid change can be the site where the amino acid mutation occurs in the gene, such as BRAF V600E (BRAF gene is a proto-oncogene, V600E is the mutation node of the gene), etc. The mutation result shown in Figure 8 is the gene mutation result. The relevant target objects in the search results refer to the proportional relationship between the number of target objects containing the genome change in the search results and the number of all target objects in the search results. The relevant target objects in the data management platform may be the ratio between the number of target objects containing the genomic alteration in the platform and the number of all target objects in the platform. The impact of mutation refers to the degree of impact of mutation on gene function. Among them, the mutation impact can be determined using the above three determination methods, or the impact degree can be determined using one of the determination methods.

In some disclosed embodiments, target information corresponding to at least one feedback dimension can be downloaded by the user.

In some disclosed embodiments, in response to the data management operation on the data management platform, the method of performing data management on the medical data in the data management platform that matches the data management operation may also be:

In response to a data selection operation on the retrieval interface, the selected at least one first target medical data is saved as a target queue. Then, in response to the selection operation of the analysis module on the data management platform, the medical data of the target queue is analyzed to obtain the medical data analysis results of the target queue. Finally, the medical data analysis results of the target cohort are displayed. Among them, the medical data analysis results are at least one of the following: the cohort data statistics of the target cohort, the cohort comparison between the target cohort and the reference cohort, the genetic map of the target cohort, and the survival analysis results of the target cohort. Obtaining at least one data analysis result by analyzing the target cohort can improve the diversity of data analysis.

Wherein, in response to the data selection operation on the retrieval interface, the method of saving the selected at least one first target medical data as the target queue may be:

After the target medical data is displayed with the target object as the dimension, in response to the queue creation operation in the result display area of the retrieval interface, a queue is created using the medical data corresponding to the selected at least one target object. Specifically, there is a selection box in front of each target object, which can mark the target object as "selected", and then create a queue for the selected target object by clicking "Create/Edit Queue" on the result display interface of the retrieval interface. Among them, the created queue can be saved in the user data module for subsequent viewing by users.

After the target medical data is displayed with the gene dimension, in response to the first list creation operation in the result display area of the search interface, the first gene list is created using the medical data corresponding to the selected at least one gene. For example, there is a selection box in front of each gene identification, the gene can be marked as "selected", and then the first gene list is created through "Create/Edit Biomarker List" in the result display area. Among them, the created queue can also be saved in the user data module for subsequent viewing by users.

After the target medical image data is displayed with the mutation dimension, in response to the second list creation operation in the result display area of the search interface, a second gene list is created using the medical data corresponding to the selected at least one mutated gene. Among them, there is a selection box in front of each mutated gene, which can mark the mutated gene as "selected", and then create a second gene list through "Create/Edit Biomarker List" in the result display area. This second gene list can for subsequent bioinformatics analysis. Among them, the created queue can also be saved in the user data module for subsequent viewing by users.

In response to a data selection operation on the retrieval interface, the selected at least one first target medical data is saved as a target data set. Then, in response to a selection operation on the user data module on the data management platform, information of the created at least one target data set is obtained and displayed. Wherein, at least one target data set includes a target subject queue and/or a biomarker queue. By displaying the target data set for data selection, user data can be managed.

Among them, the target data set can be the target queue and gene list created in the search interface as mentioned above. The gene list may include a first gene list and a second gene list. Specifically, in response to the data selection operation on the retrieval interface, saving the selected at least one first target medical data as the target data set can be referred to the above description of obtaining the target queue and gene list, which will not be described again here. Please also refer to FIG. 9 , which is a first display schematic diagram of a user data interface according to an embodiment of the medical data management method of the present application.

As shown in Figure 8, the information of the target data set is displayed on the user data interface of the data management platform. The user data interface includes a first trigger item corresponding to the target object queue and a second trigger item corresponding to the biomarker queue. Among them, the biomarker cohort refers to the above-mentioned gene list.

In response to the selection operation of the user data module on the data management platform, the manner of obtaining and displaying the information of the at least one target data set created may be:

In response to the trigger operation on the first trigger item, the first target information of the target object queue is displayed on the user data interface. The first target information of the target data set includes the name and data amount of the target data set. As shown in Figure 9, the amount of data corresponding to the target object queue is the number of target objects.

Or, in response to the trigger operation on the second trigger item, display the first target information of the biomarker queue on the user data interface. Please also refer to FIG. 10 , which is a second display schematic diagram of a user data interface according to an embodiment of the medical data management method of the present application. As shown in Figure 10, the data volume corresponding to the biomarker queue is the number of biomarkers.

In some disclosed embodiments, after displaying the first target information of at least one target data set, the method further includes any one or more of the following steps:

In response to the name modification operation, adjust the name of the selected target data set to an editable state. And update the name of the selected target data set with the edited content. As shown in Figure 9 about the column of queue names, there is a modification operation key next to each queue name, which can be used to modify the name of the target object queue by clicking the modification operation key. As shown in Figure 10 regarding the column of biomarker list names, there is also a modification operation button next to each biomarker list name. By clicking the modification operation button, the name of the biomarker list can be modified.

In response to the first preset operation on the displayed data amount, the data information of the selected target data set is displayed. The data information is information corresponding to each target object or each biomarker in the target data set. The data information is information corresponding to each target object or each biomarker in the target data set. Specifically, the data information may be medical data information about each target object in the target data set or information corresponding to each biomarker. Among them, each biomarker can specifically be a gene or a mutated gene.

In response to the delete operation, the selected target data set is deleted. Of course, the target data set is only deleted from the user data module, and each medical data in the target data set does not need to be deleted from the data management platform.

Please also refer to FIG. 11 , which is a third display schematic diagram of a user data interface according to an embodiment of the medical data management method of the present application. As shown in Figure 11, the data information corresponding to the biomarker queue includes label information of each biomarker in the biomarker queue, and the label information indicates whether the biomarker has mutated.

As shown in Figure 9, the first target information of the target object queue also includes a viewing interface. The viewing interface is located in the third column, which is the viewing data column. After displaying the first target information of the target object queue, the method also includes:

In response to the second preset operation on the displayed viewing interface, jump to the data storage interface of the data management platform, and display the second target information of the selected target object queue on the data storage interface, where the second target information is the target The object queue contains information about genetic testing files. Please also refer to FIG. 12 , which is a schematic diagram showing a data storage interface according to an embodiment of the medical data management method of the present application. Among them, in addition to entering the data storage interface according to operations in the user data module, you can also click the data storage button on the main interface to enter the data storage interface. That is, in response to the data management operation on the data management platform, the way to perform data management on the medical data in the data management platform that matches the data management operation may be:

In response to the selection operation of the data storage module on the data management platform, the data storage interface of the data management platform is displayed. Then, obtain the file information entered on the data storage interface, and search for several genetic testing files matching the file information in the data management platform. Finally, the information of several genetic testing files is displayed on the data storage interface.

Among them, the information of several genetic testing files may include at least one of the following: basic information of the genetic testing files, and several target statistical results obtained by counting the genetic testing files. The basic information of the genetic testing file includes at least two types: file name, target object, subject, file type, file format, file size, and current acquisition status, where the current acquisition status is available or unavailable. Several target statistical results include at least one of the following: statistics of lesions corresponding to the target gene detection files, statistics of the subject to which they belong, statistics of file types, statistics of file formats, and statistics of gene detection methods.

In some disclosed embodiments, the method of displaying the information of several gene detection files or the second target information of the target object queue on the data storage interface may be:

In the result sub-area of the result display area of the data storage interface, the information of several gene detection files or the second target information is displayed.

The method also includes any one or more of the following steps: displaying the number of several gene detection files in the result sub-area. And, in the record sub-area of the result display area, the search conditions generated based on the file information are displayed.

As shown in Figure 12, the second target information includes at least one of the following: basic information of the gene detection file, and several target statistical results obtained by statistics of the gene detection file.

After the data storage interface displays the second target information of the selected target object queue or the information of several gene detection files, the method further includes any one or more of the following steps: when the basic information includes the file name of the gene detection file, detect To trigger the operation on the file name, perform the first preset processing on the selected gene detection file. The first preset process may be to display the file content of the target gene detection file. The file content may include genetic sequences. When the basic information includes the target object, the trigger operation on the target object is detected, the preset information of the target object of the selected gene detection file is obtained, and the preset information is displayed on the data storage interface. In response to the first operation in the data storage interface, first preset processing is performed on the selected target gene detection file. The preset information of the target object may be an identifier of the target object, such as the name of the target object. In response to the second operation in the data storage interface, a second preset process is performed on the selected target statistical result. The second preset processing may be download processing or update processing. Specifically, you can click the download or update button on the side of each statistical result to update or download the selected statistical result.

In response to a data selection operation on the retrieval interface, the selected at least one first target medical data is saved as a target queue. Then, in response to the selection operation of the analysis module on the data management platform, the medical data of the target queue is analyzed to obtain the medical data analysis results of the target queue. Finally, the medical data analysis results of the target cohort are displayed.

Please also refer to FIG. 13 , which is a first schematic diagram showing a data analysis interface according to an embodiment of the medical data management method of the present application. As shown in Figure 13, in response to the selection operation on the analysis result item, the data analysis result interface is displayed. The data analysis interface includes four sub-modules, namely the queue details sub-module, the queue comparison sub-module, the genetic map sub-module and the survival analysis sub-module. By triggering one of the sub-modules, corresponding data analysis and processing is performed on the medical data in the target queue, and the corresponding medical data analysis results are obtained. In some disclosed embodiments, the data analysis interface includes analysis application items and analysis result items. In response to the selection operation of the analysis application item, the data analysis interface displays the above-mentioned queue details sub-module, queue comparison sub-module, gene map sub-module and survival analysis sub-module.

Among them, the medical data analysis results are at least one of the following: the cohort data statistics of the target cohort, the cohort comparison between the target cohort and the reference cohort, the genetic map of the target cohort, and the survival analysis results of the target cohort. Obtaining at least one data analysis result by analyzing the target cohort can improve the diversity of data analysis.

In some disclosed embodiments, in response to the selection operation of the analysis module on the data management platform, the medical data of the target queue is analyzed, and obtaining the medical data analysis results of the target queue may include at least one or more of the following steps:

In response to the first trigger operation on the data analysis interface, statistics are performed on the medical data in the target queue to obtain queue data statistics of the target queue. As mentioned above, the data analysis interface includes four sub-modules. The first trigger operation in the data analysis interface can be the selection operation of the queue details sub-module. The cohort details submodule can be used to display statistical results of clinical information and genomic features of the target cohort.

In response to the second trigger operation on the data analysis interface, the medical data of the target queue and the reference queue are compared to obtain the queue comparison situation of the target queue. The second trigger operation on the data analysis interface may be a selection operation on the queue comparison sub-module. Cohort comparison can be used to analyze differences in clinical information and genomic characteristics between two cohorts.

In response to the third triggering operation on the data analysis interface, genetic statistics are performed using the medical data of the target cohort to obtain a genetic map of the target cohort. The genetic map is used to characterize the genetic mutations of the target objects in the target cohort. In other disclosed embodiments, in response to the third triggering operation, clinical statistical information and omics type statistical information of the target queue are statistically obtained, and the omics type statistical information includes the type of gene detection file of each target object in the target queue. The third trigger operation on the data analysis interface may be a selection operation on the gene map sub-module. The gene map sub-module can be used to display the heat distribution of the target cohort at the multi-omics feature level.

In response to the fourth trigger operation on the data analysis interface, survival analysis is performed using the medical data of the target queue to obtain the survival analysis result of the target queue. The fourth trigger operation may be a selection operation on the survival analysis sub-module. The survival analysis submodule is used for gene COX regression to perform survival analysis.

Please also refer to FIG. 14 , which is a schematic diagram of a queue status display interface according to an embodiment of the medical data management method of the present application. Figure 14 shows the medical data analysis results obtained by performing data analysis on the target queue after the first triggering operation. As shown in Figure 14, the cohort data statistics include the first cohort, clinical statistics obtained from clinical data statistics, and biomics statistics obtained from biomics data statistics. Different queue data statistics are displayed in different areas of the queue status display interface. By displaying the situation of the first queue, the overall situation of the first queue can be intuitively seen.

In some disclosed embodiments, the clinical statistics include at least one of the following: the proportions of different genders in the target cohort, the proportions of different disease age intervals in the target cohort, and the survival curve of the target cohort. Among them, the biological statistics include statistics on the number of objects of several first preset genes. The first preset gene may be several mutant genes whose mutation frequency meets preset requirements. The statistics of the number of target subjects of the first preset gene may display the number of patients with TOP20 high-frequency somatic mutation genes.

After the queue data statistics are displayed on the queue status display interface, the following steps can also be included:

In response to a title editing trigger operation on the queue status display interface, adjust the first title of the queue status display interface to an editable state, and update the first title based on the input title information;

In response to the update trigger operation on the queue status display interface, re-count and display the selected queue data statistics;

In response to the first download triggering operation on the queue status display interface, download the selected queue data statistics;

Obtain the gene name entered in the first search area of the queue status display interface, find the associated data with the entered gene name from the medical data of the target cohort, and display the associated data on the queue status display interface.

Please also refer to FIG. 15 , which is a first schematic diagram showing a comparison display interface according to an embodiment of the medical data management method of the present application. Figure 15 shows part of the medical data analysis results obtained by performing data analysis on the target queue after the second triggering operation. As shown in Figure 15, the cohort comparison includes the second cohort, the clinical comparison obtained by comparing clinical data, and the biomics comparison obtained by comparing biological data. Wherein, the second queue situation includes at least one of the names of the target queue and the reference queue, and the number of objects in the target queue and the reference queue. The clinical comparison situation includes at least one of the following: the difference in the number of subjects of different genders in the target cohort and the reference cohort, the difference in age of disease in the target cohort and the reference cohort, and the survival curves of the target cohort and the reference cohort. The difference in the number of objects of different genders in the target cohort and the reference cohort can be presented in the form of a histogram. In some disclosed embodiments, in response to the triggering of the first trigger key of the contrast display interface, the clinical contrast situation is displayed in the second area of the contrast display interface, and in response to the triggering of the second trigger key of the contrast display interface, the clinical contrast situation is displayed in the contrast display interface. The second area of the interface displays the biomics alignment.

Please also refer to Figure 16. Figure 16 is a second schematic diagram showing a comparison display interface according to an embodiment of the medical data management method of the present application. Figure 16 shows part of the medical data analysis results obtained by performing data analysis on the target queue after the second triggering operation. As shown in Figure 16, the biological comparison includes at least one of the following: the comparison of gene mutation frequencies between the target cohort and the reference cohort, the comparison of mutated genes with mutation frequencies greater than the preset threshold in the target cohort and the reference cohort, several third 2. Comparison of the mutation frequency of the preset genes in the target cohort and the reference cohort, and the status of each gene in the target cohort and the reference cohort.

In some disclosed embodiments, after the comparison display interface displays the corresponding queue comparison situation, the following steps may also be performed:

In response to the title editing triggering operation on the comparison display interface, adjust the second title of the comparison display interface to an editable state, and update the second title based on the input title information;

In response to the second download triggering operation on the comparison display interface, download the selected queue comparison situation;

When the biological comparison situation is displayed in the second area of the comparison display interface, in response to the export operation of the gene situation display area of the second area, the selected gene situation in the gene situation display area is exported, wherein the gene situation The display area is used to display the status of each gene in the target queue and reference queue;

When the biological comparison is displayed in the second area, the gene name entered in the second search area of the second area is obtained, and the correlation of the entered gene name is found from the medical data of the target cohort and/or the reference cohort. Gene status, and the relevant gene status is updated and displayed in the gene status display area;

When the biological comparison situation is displayed in the second area, in response to the selection operation on the significance display item in the second area, only the gene situations with significant effects are displayed in the gene situation display area.

Please also refer to FIG. 17 , which is a schematic diagram of a gene map display interface according to an embodiment of the medical data management method of the present application. As shown in Figure 17, the genetic map includes the number of mutated genes of each target object in the target queue and the number of mutated objects of each gene in the target queue. The gene map is represented by a combination of a heat map and a column chart. The heat map is used to represent the heat distribution of mutations in each gene in the target cohort. The column chart includes a first column chart and a second column chart. The first bar chart is used to represent the number of mutated genes of each target object in the target queue. The second bar chart is used to represent the number of objects with mutations in each gene in the target cohort. Among them, the horizontal axis of the heat map is the name of each target object in the target queue, and the vertical axis of the heat map is the name of each mutant gene. The first column chart is located above the heat map. The horizontal axis of the first column chart represents the name of each target object in the target queue, and the vertical axis represents the number of mutant genes contained in each target object. The second column chart is located on the right side of the heat map. The horizontal axis of the second column chart represents the name of the mutated gene present in the target queue, and the vertical axis represents the number of target objects where each mutated gene is located. Gene maps, clinical statistical information and omics type statistical information are all represented by charts and displayed on the same display interface.

In some disclosed embodiments, displaying the medical data analysis results of the target object includes: displaying the third queue situation and the survival analysis results of the target queue in different areas of the survival analysis display interface. The third queue situation includes the total number of objects in the target queue, The number of valid objects selected in the target queue and the ratio of the number of valid objects to the total number of objects. Please also refer to FIG. 18 , which is a schematic diagram showing a survival analysis display interface according to an embodiment of the medical data management method of the present application. As shown in Figure 18, the survival analysis results include any one or more of the following: multi-factor COX analysis results and distribution of observed variables.

The results of multivariate COX analysis include variables, hazard ratio (HR), confidence interval (CI) and p value. Among them, the variable is the name of the mutated gene, and the risk ratio includes the probability that the mutated gene causes malignant tumors. The confidence interval is set by the user and can be used to express the tolerance interval of the risk ratio. In other disclosed embodiments, the risk ratio can also be used to represent the concentration point of the survival time in the target cohort, and the confidence interval can also be used to represent the tolerance interval of the survival time.

The distribution of observed variables includes the name of the observed variable, variable classification, grouping, the number of target objects contained in different groups, and the proportion of target objects contained in different groups. The name of the observed variable is the name of the mutant gene, and the variable classification includes wild type and mutant type. The groups include observation group and reference group. The number of target objects contained in different groups is specifically the number of target objects belonging to each group in the target queue. The proportion includes the ratio between the number of target objects in each group and the total number of target objects in the target queue. The distribution of observed variables can be used to subsequently analyze the data.

In some disclosed embodiments, after the survival analysis display interface displays the medical data analysis results, the following steps may also be included:

In response to a result export operation on the survival analysis display interface, the survival analysis results are exported. And, based on the input key parameters, find the result data matching the key parameters from the survival analysis results, and display and/or export the result data.

In some disclosed embodiments, in response to a preset operation on the data management platform, the method of performing data processing on medical data that matches the preset operation may be:

In response to the selection operation of the subject overview module on the data management platform, the subject interface of the data management platform is displayed. Then, obtain basic information on several topics in the data management platform. Among them, the way to enter the subject overview module is to select the subject overview button on the main interface.

Please refer to FIG. 19 and FIG. 20 at the same time. FIG. 19 is a first schematic diagram showing a topic interface according to an embodiment of the medical data management method of the present application. FIG. 20 is a second schematic diagram showing a topic interface according to an embodiment of the medical data management method of the present application. As shown in Figure 19, the basic information of several topics is displayed on the topic interface of the data management platform. As shown in Figure 20, after selecting a topic from several topics shown in Figure 19, the statistical information of the topic selected on the topic interface can also be displayed. Among them, the statistical information of the topic is obtained based on the statistics of medical data related to the topic.

The statistical information of the subject includes at least one of the following: overview information of the target subject, type statistics based on gene detection file types, method statistics based on gene detection methods, and lesion statistics based on lesions. The genetic testing methods are as mentioned above and will not be described again here. Among them, the number of statistical files represents the number of genetic testing files obtained by counting the corresponding types, genetic testing methods, or lesions, and the number of statistical objects represents the number of target objects obtained by counting the corresponding types, genetic testing methods, or lesions.

The basic information of the subject includes at least one of the following: the name of the subject, whether the genetic testing documents included in the subject are obtained from public channels, the types of diseases included in the subject, the lesions included in the subject, the projects to which the subject belongs, the number of subject subjects, and the number of subject documents. Among them, the number of subject objects indicates the number of target objects included in the subject, and the number of subject files indicates the number of genetic testing files included in the subject.

Among them, there is at least one statistical file number and statistical object number in the displayed statistical information that can be triggered. And the number of subject objects and/or the number of subject documents can be triggered.

After displaying the statistical information of the topic selected on the topic interface, the method further includes: in response to a triggering operation on the number of triggerable statistical objects, using the target object as a dimension, displaying the first medical data corresponding to the number of triggered statistical objects. And/or, in response to a triggering operation on the number of triggerable statistical files, display the second medical data corresponding to the number of triggered statistical files with the gene detection file as a dimension.

Using the target object as a dimension, displaying the first medical data corresponding to the number of triggered statistical objects, or using the target object as a dimension, displaying the third medical data corresponding to the number of triggered subject objects, may be: using the first medical data or the third Three medical data are used as the first target medical data. Jump to the search interface of the data management platform, and display the first target medical data in the search interface with the target object as the dimension. For the content displayed on the search interface, please refer to the above and will not be described again here.

After displaying the basic information of several subjects on the subject interface of the data management platform, the method also includes: in response to a triggering operation on the number of triggerable subject objects, using the target object as a dimension, displaying the third medical information corresponding to the number of triggered subject objects. data. And/or, in response to a triggering operation on the number of triggerable subject files, display the fourth medical data corresponding to the number of triggered subject files using the genetic testing files as dimensions.

Among them, using the genetic testing files as a dimension to display the second medical data corresponding to the number of triggered statistical files, or using the genetic testing files as a dimension to display the fourth medical data corresponding to the number of triggered subject files may be: using the second Medical data or fourth medical data serve as the second target medical data. Jump to the data storage interface of the data management platform, and display the second target medical data in the data storage interface with the genetic testing file as the dimension. Among them, the content displayed on the data storage interface is as described above and will not be described again here.

The first target medical data can be displayed with the target object as the dimension in the retrieval interface, or the second target medical data can be displayed with the genetic testing file as the dimension in the data storage interface:

Take the retrieval interface as the target interface, the target object as the target dimension, the first target medical data as the target medical data, and the topic corresponding to the first target medical data as the search conditions, or, use the data storage interface as the target interface, and the genetic testing file as the target The dimensions, the second target medical data are the target medical data, and the topics and related file types corresponding to the second target medical data are used as search conditions. In the result sub-area of the result display area of the target interface, the target medical data is displayed according to the target dimension, and/or several attribute statistical results are displayed. The attribute statistical results are obtained by statistics of the target medical data.

In some disclosed embodiments, after jumping to the target interface, the method further includes at least one of the following steps: when the target dimension is the target object, setting the topic corresponding to the target medical data to the selected state in the retrieval area of the target interface. , when the target dimension is a genetic testing file, in the search area of the target interface, set the topic and related file type corresponding to the target medical data to the selected state. Search conditions are displayed in the record subarea of the result display area.

In some disclosed embodiments, the target dimension is the target object. After displaying the target medical data according to the target dimension, and/or displaying several attribute statistical results, the method further includes: in response to a preset selection operation on the target interface, using the selected gene or mutation as the current dimension, and in the result sub-area Displays the target information corresponding to the current dimension.

Among them, the method provided by the embodiment of the present disclosure is applied to the server of the target platform. The above step S12 may include the following steps:

Receive operation information sent by the terminal. The operation information is generated by the terminal in response to the predicted operation after logging into the data management platform.

Send the data processing results corresponding to the preset operation to the terminal, so that the terminal displays the data processing results.

In other disclosed embodiments, the methods provided by the disclosed embodiments can also be applied to devices installed with the target platform. After detecting the login to the data management platform, the device responds to the preset operation on the data management platform and performs data processing on the medical data that matches the preset operation.

Among them, the execution subject of the medical data management method can be a data management platform. For example, the medical data management method can be executed by terminal devices such as cameras, mobile phones, laptops with image acquisition functions, or servers or other processing devices, wherein the terminal devices can For user equipment (User Equipment, UE), mobile devices, user terminals, terminals, cellular phones, cordless phones, personal digital assistants (Personal Digital Assistant, PDA), handheld devices, computing devices, vehicle-mounted devices, wearable devices, etc. In some possible implementations, the medical data management method can be implemented by a processor calling computer-readable instructions stored in a memory.

Please refer to Figure 21, which is a schematic structural diagram of an embodiment of the data management platform of the present application. The data management platform 40 includes an operation detection sub-module 41 and a data processing sub-module 42. The operation detection sub-module is used to detect the login to the data management platform, where the data management platform is used to manage the medical data of the target object. The medical data of the target object includes the clinical data of the target object and the biomics of the target object. At least one of the data; a data processing submodule, configured to respond to a preset operation on the data management platform and perform data processing on the medical data that matches the preset operation.

In some disclosed embodiments, the data processing sub-module 42 responds to a preset operation on the data management platform and performs data processing on the medical data that matches the preset operation, including: in response to a data upload operation on the data management platform, Upload the medical data of at least one target object to the data management platform; and/or, in response to the data management operation on the data management platform, perform data management matching the data management operation on the medical data in the data management platform.

With the above solution, medical data can be uploaded to the data management platform to facilitate subsequent management of medical data based on data management operations.

In some disclosed embodiments, data management includes at least one of the following: displaying platform data status of the data management platform, retrieving medical data on the data management platform, analyzing medical data on the data management platform, and statistics on topics in the data management platform. Information, find information about genetic testing files in the data management platform, and display information about the created target data set.

The above solution can improve the flexibility of data management by providing multiple data management methods.

In some disclosed embodiments, the data processing sub-module 42 responds to the data management operation on the data management platform and performs data management on the medical data in the data management platform that matches the data management operation, including: in response to the data management operation on the data management platform. The selection operation of the retrieval module displays the retrieval interface of the data management platform; obtains the retrieval conditions entered in the retrieval interface, and retrieves several pieces of medical data matching the retrieval conditions in the data management platform as the first target medical data; in the retrieval The interface displays target information related to the first target medical data.

The above solution can match the corresponding medical data according to the input search conditions and display the target information of the medical data to facilitate viewing of the corresponding medical data.

In some disclosed embodiments, the data processing sub-module 42 obtains the search conditions entered in the search interface, including: obtaining the search conditions of at least one search dimension entered in the search interface, where at least one search dimension includes target objects, genes, and mutations. At least one of; displaying target information related to the first target medical data on the retrieval interface, including: displaying target information related to the first target medical data on the retrieval interface according to at least one feedback dimension, wherein at least one feedback dimension At least one of a target object, a gene, and a mutation is included.

The above solution makes the retrieval process more flexible by providing at least one retrieval dimension and at least one feedback dimension.

In some disclosed embodiments, the data processing sub-module 42 responds to the data management operation on the data management platform, performs data management on the medical data in the data management platform that matches the data management operation, and further includes: in response to the data management operation on the retrieval interface. perform a data selection operation to save the selected first target medical data as the target queue; in response to the selection operation of the analysis module on the data management platform, analyze the medical data of the target queue to obtain the medical data analysis of the target queue Result; display the medical data analysis results of the target cohort, in which the medical data analysis results are at least one of the following: the cohort data statistics of the target cohort, the cohort comparison between the target cohort and the reference cohort, the genetic map of the target cohort, and the target cohort. Survival analysis results of the cohort.

The above solution can obtain at least one data analysis result by analyzing the target queue, which can improve the diversity of data analysis.

In some disclosed embodiments, the data processing sub-module 42 responds to the data management operation on the data management platform, performs data management on the medical data in the data management platform that matches the data management operation, including: in response to the data management operation on the retrieval interface. a data selection operation to save the selected at least one first target medical data as a target data set; in response to a selection operation of the data module on the data management platform, obtain and display information of the created at least one target data set, wherein, At least one target data set includes a target subject cohort and/or a biomarker cohort.

The above solution can realize data management by displaying the target data set for data selection.

In some disclosed embodiments, the data processing sub-module 42 responds to the data management operation on the data management platform and performs data management on the medical data in the data management platform that matches the data management operation, including: in response to the data management operation on the data management platform. Select the platform viewing module to obtain the platform data situation of the data management platform, and display the platform data situation on the platform viewing interface of the data management platform; where the platform data situation includes at least one of the following data situations: overall data of the data management platform situation, the clinical data situation obtained based on clinical data statistics, the biological data situation obtained based on biomics data statistics; or, in response to the selection operation of the data storage module on the data management platform, display the data storage interface of the data management platform; Obtain the file information entered on the data storage interface, and search for several genetic testing files matching the file information in the data management platform; display the information of several genetic testing files on the data storage interface.

The above solution can easily understand the overall data situation by displaying the platform data situation of the data management platform. In addition, by displaying the data storage interface of the data management platform, the corresponding genetic testing file information can be easily understood.

In some disclosed embodiments, the operation detection sub-module 41 detects logging into the data management platform, including: receiving an access request, where the access request contains login information; in response to passing the verification of the login information, delivering the web interface of the data management platform; Among them, the preset operation is implemented on the web interface displayed on the user terminal.

The above solution realizes the management of data in the data management platform by performing preset operations on the web interface.

For the above solution, the execution subject can be hardware execution, or execution by a processor running computer executable code.

Please refer to FIG. 22 , which is a schematic structural diagram of an embodiment of the electronic device of the present application. The electronic device 50 includes a memory 51 and a processor 52. The processor 52 is used to execute program instructions stored in the memory 51 to implement the steps in any of the above medical data management method embodiments. In a specific implementation scenario, the electronic device 50 may include but is not limited to: medical equipment, microcomputers, desktop computers, servers. In addition, the electronic device 50 may also include mobile devices such as laptop computers and tablet computers, which are not limited here. .

Specifically, the processor 52 is used to control itself and the memory 51 to implement the steps in any of the above medical data management method embodiments. The processor 52 may also be called a CPU (Central Processing Unit). The processor 52 may be an integrated circuit chip with signal processing capabilities. The processor 52 can also be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field programmable gate array (Field-Programmable Gate Array, FPGA) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. In addition, the processor 52 may be implemented by an integrated circuit chip.

Please refer to Figure 23, which is a schematic structural diagram of an embodiment of a computer-readable storage medium of the present application. The computer-readable storage medium 60 stores program instructions 61. When the program instructions 61 are executed by the processor, the steps in any of the above medical data management method embodiments are implemented. The storage medium can be a volatile or non-volatile computer. Readable storage media.

In some embodiments, the functions or modules included in the system provided by the embodiments of the present disclosure can be used to execute the methods described in the above method embodiments. For specific implementation, refer to the description of the above method embodiments. For the sake of brevity, here No longer.

The above description of various embodiments tends to emphasize the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described again here.

In the several embodiments provided in this application, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system implementation described above is only illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other divisions, for example, units or components may be combined or integrated. to another system, or some features can be ignored, or not implemented. On the other hand, the coupling or direct coupling or communication connection between each other shown or discussed may be through some interfaces, and the indirect coupling or communication connection of the system or unit may be in electrical, mechanical or other forms.

In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or software functional units. Integrated units may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as independent products. Based on this understanding, the technical solution of the present application is essentially or contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , including a number of instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the various implementation methods of this application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program code. .

Embodiments of the present disclosure also provide a computer program product. The computer program product carries program code, including computer readable code, or a computer readable storage medium carrying computer readable code. When the computer readable code is stored in an electronic When running in the processor of the device, the instructions included in the program code can be used to execute the steps of the method described in the above method embodiments. For details, please refer to the above method embodiments, which will not be described again here.

Among them, the above-mentioned computer program product can be specifically implemented by hardware, software or a combination thereof. In an optional embodiment, the computer program product is embodied as a computer storage medium. In another optional embodiment, the computer program product is embodied as a software product, such as a Software Development Kit (SDK), etc. wait.

If the technical solution of this application involves personal information, the products applying the technical solution of this application will clearly inform the personal information processing rules and obtain the individual's independent consent before processing personal information. If the technical solution in this application involves sensitive personal information, the product applying the technical solution in this application must obtain the individual's separate consent before processing sensitive personal information, and meet the requirement of "express consent" at the same time. For example, setting up clear and conspicuous signs on personal information collection devices such as cameras to inform them that they have entered the scope of personal information collection, and that personal information will be collected. If an individual voluntarily enters the collection scope, it is deemed to have agreed to the collection of his or her personal information; or On personal information processing devices, when using obvious logos/information to inform personal information processing rules, obtain personal authorization through pop-up messages or asking individuals to upload their personal information; among them, personal information processing rules may include personal information processing rules. Information such as information processors, purposes of processing personal information, methods of processing, and types of personal information processed.

Claims

A medical data management method, characterized by including:

Login to the data management platform is detected, wherein the data management platform is used to manage the medical data of the target object, and the medical data of the target object includes the clinical data of the target object and the biological group of the target object. At least one of the academic data;

In response to a preset operation on the data management platform, data processing matching the preset operation is performed on the medical data.
The method according to claim 1, characterized in that, in response to a preset operation on the data management platform, performing data processing on the medical data that matches the preset operation, including:

In response to a data upload operation on the data management platform, uploading medical data of at least one target object to the data management platform; and/or,

In response to a data management operation on the data management platform, data management matching the data management operation is performed on the medical data in the data management platform.
The method according to claim 2, characterized in that the data management includes at least one of the following: displaying platform data status of the data management platform, retrieving medical data of the data management platform, and analyzing the data. Analyze the medical data of the management platform, collect statistics on subject information in the data management platform, search for information on genetic testing files in the data management platform, and display information on the created target data set.
The method of claim 3, wherein in response to a data management operation on the data management platform, the medical data in the data management platform is subjected to data management that matches the data management operation. ,include:

In response to the selection operation of the retrieval module on the data management platform, display the retrieval interface of the data management platform;

Obtain the retrieval conditions input in the retrieval interface, and retrieve several pieces of medical data matching the retrieval conditions in the data management platform as the first target medical data;

Target information related to the first target medical data is displayed on the retrieval interface.
The method according to claim 4, characterized in that said obtaining the retrieval conditions input on the retrieval interface includes:

Obtain the search conditions of at least one search dimension input in the search interface, wherein the at least one search dimension includes at least one of a target object, a gene and a mutation;

The display of target information related to the first target medical data on the retrieval interface includes:

On the retrieval interface, target information related to the first target medical data is displayed according to at least one feedback dimension, wherein the at least one feedback dimension includes at least one of a target object, a gene, and a mutation.
The method according to claim 4 or 5, characterized in that, in response to the data management operation on the data management platform, the medical data in the data management platform is processed to match the data management operation. Data management, also includes:

In response to a data selection operation on the retrieval interface, saving the selected at least one first target medical data as a target queue;

In response to the selection operation of the analysis module on the data management platform, analyze the medical data of the target queue to obtain the medical data analysis results of the target queue;

Display the medical data analysis results of the target queue, wherein the medical data analysis results are at least one of the following: the queue data statistics of the target queue, the queue comparison between the target queue and the reference queue, the Gene map of the target cohort and survival analysis results of the target cohort.
The method according to claim 4 or 5, characterized in that, in response to the data management operation on the data management platform, the medical data in the data management platform is processed to match the data management operation. Data management, including:

In response to a data selection operation on the retrieval interface, saving the selected at least one first target medical data as the target data set;

In response to a selection operation on the user data module on the data management platform, obtaining and displaying information of the at least one target data set created, wherein the at least one target data set includes a target object queue and/or a biomarker object queue.
The method of claim 3, wherein in response to a data management operation on the data management platform, the medical data in the data management platform is subjected to data management that matches the data management operation. ,include:

In response to the selection operation of the platform viewing module on the data management platform, obtain the platform data situation of the data management platform, and display the platform data situation on the platform viewing interface of the data management platform; wherein, the The platform data situation includes at least one of the following data situations: the overall data situation of the data management platform, the clinical data situation obtained based on the clinical data statistics, and the biological data situation obtained based on the biomics data statistics; or,

In response to the selection operation of the data storage module on the data management platform, display the data storage interface of the data management platform; obtain the file information input on the data storage interface, and search in the data management platform Several gene detection files matching the file information are output; and the information of the several gene detection files is displayed on the data storage interface.
The method according to any one of claims 1 to 8, characterized in that the detection of login to the data management platform includes:

Receive an access request, wherein the access request includes login information;

In response to the verification of the login information passing, the web interface of the data management platform is delivered; wherein the preset operation is implemented on the web interface displayed on the user terminal.
A data management platform is characterized by including:

The operation detection submodule is used to detect the login to the data management platform, wherein the data management platform is used to manage the medical data of the target object, and the medical data of the target object includes the clinical data of the target object and At least one of the biological omics data of the target subject;

A data processing submodule, configured to respond to a preset operation on the data management platform and perform data processing on the medical data that matches the preset operation.
An electronic device, characterized by comprising a memory and a processor, the processor being configured to execute program instructions stored in the memory to implement the method according to any one of claims 1 to 9.
A computer-readable storage medium on which program instructions are stored, characterized in that when the program instructions are executed by a processor, the method of any one of claims 1 to 9 is implemented.
A computer program product comprising computer readable code, or a computer readable storage medium carrying the computer readable code, when the computer readable code is executed in a processor of an electronic device, a process in the electronic device The processor executes the method described in any one of claims 1 to 9.