Medical data sharing system and method based on block chain

Abstract

The invention discloses a medical data sharing system and method based on a block chain, and relates to the technical field of medical data retrieval. When the retrieval information is typed in each time, numbering is performed on all matched medical data, in combination with selected medical data, whether the medical data and the corresponding numbering exist or not is searched in the retrieval information of each time, and a retrieval analysis module is arranged to periodically analyze a plurality of pieces of retrieval service information of each piece of stored medical data; according to the method, a plurality of pieces of retrieval service information meeting the analysis condition are stored, so that all retrieval personnel are screened based on the retrieval information of a plurality of pieces of medical data, the waste of analysis and storage resources in the process of updating the retrieval white list of a plurality of pieces of medical data is avoided, the updating efficiency of the retrieval white list of medical data is improved, and the user experience is improved. And the retrieval efficiency and accuracy in the medical data sharing process are further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical data retrieval, and in particular to a blockchain-based medical data sharing system and method. Background Art

[0002] In the medical field, the storage and sharing of medical data are crucial. With the continuous development of medical informatization, massive amounts of medical data are generated. Traditional storage methods face many challenges in terms of data security, integrity, and sharing. Blockchain technology, due to its decentralized, tamper-proof, and traceable characteristics, is gradually being applied to medical data storage, aiming to achieve secure and reliable storage and efficient sharing of medical data.

[0003] When using blockchain to store and share medical data, retrieval efficiency becomes a key issue. To improve retrieval efficiency, one current strategy is to periodically expand product information matching keywords. This strategy aims to make search results more comprehensive and accurate by continuously enriching the keyword library, allowing searchers to find the required environmental design resources more quickly.

[0004] Currently, one way to expand matching keywords is to select based on the search information entered by the searcher. However, the amount of search information is huge, and not all search information has reliable analysis standards. Expanding matching keywords based on the analysis of all search information will lead to inefficient keyword expansion and waste analysis resources.

[0005] In order to solve the above problems, the present invention proposes a solution. Summary of the Invention

[0006] The purpose of the present invention is to provide a blockchain-based medical data sharing system and method to solve the problems raised in the above background technology.

[0007] The present invention provides a blockchain-based medical data sharing system, comprising:

[0008] A search service unit, configured to obtain a plurality of medical data matching the search information according to the search information entered by the search personnel, wherein the search information includes a plurality of search keywords;

[0009] The search service unit is further configured to calculate the similarity between each matched medical data and the search information, number each medical data in descending order of similarity, and display all matched medical data to the search personnel in sequence after numbering is completed;

[0010] a monitoring and retrieval unit, configured to, upon detecting that a searcher has selected a medical data item after multiple entries of retrieval information, obtain a digital number of the selected medical data item from a plurality of medical data items that match the retrieval information according to the multiple entries of retrieval information, and generate retrieval service information of the selected medical data item according to the obtained digital numbers;

[0011] The selected updating unit is used to periodically optimize and screen the retrieval service information of all stored medical data to periodically determine whether the stored medical data meet the analysis conditions, and store the retrieval service information of the medical data that meets the analysis standards.

[0012] Furthermore, the steps of generating the retrieval service information of the selected medical data are as follows:

[0013] S11: marking all search information entered by the searcher for the selected medical data as H1, H2, ..., Hh, in the order of entry, where h≥1;

[0014] S12: Searching all medical data matching the search information H1 to see whether there is any medical data selected by the searcher after multiple entries of the search information. If so, obtaining the numerical number A1 of the medical data selected by the searcher after multiple entries of the search information from all medical data matching the search information H1;

[0015] Using the formula Calculate the deviation percentage of the search information H1, where B1 is the total number of all medical data that match the search information H1. If no medical data exists, no processing is performed.

[0016] S13: searching, in sequence according to S12, all medical data matching the search information H2, H3, ..., Hh to see whether there is medical data selected by the searcher after multiple entries of the search information, and obtaining deviation percentages of the search information based on the search results;

[0017] S14: Generate retrieval service information of medical data selected by the retrieval personnel after multiple retrieval information input according to the obtained deviation percentages of the retrieval information, wherein the deviation percentages of all retrieval information are arranged from left to right in the order in which the retrieval information is input.

[0018] Furthermore, the selected update unit pre-stores an update limit value.

[0019] A blockchain-based medical data sharing method includes the following steps:

[0020] Step 1: The search service unit obtains the search information entered by the search personnel and obtains a number of medical data matching the search information, wherein the search information includes a number of search keywords;

[0021] Step 2: The search service unit calculates the similarity between each matching medical data and the search information, numbers each medical data in descending order of similarity, and displays all matching medical data to the search personnel in sequence after the numbering is completed;

[0022] Step 3: When the monitoring and retrieval unit detects that the search person has selected a medical data item after inputting the search information multiple times, the monitoring and retrieval unit obtains the digital number of the selected medical data item from the medical data items that match the search information based on the multiple input search information items, generates retrieval service information of the selected medical data item based on the obtained digital numbers, and transmits the information to the selection and update unit;

[0023] Step 4: Select an update unit to periodically optimize and screen the retrieval service information of all stored medical data to determine whether it meets the analysis conditions, and store the retrieval service information of the medical data that meets the analysis conditions.

[0024] Compared with the existing technology, it has the following beneficial effects:

[0025] The present invention provides a monitoring and retrieval unit to analyze multiple retrieval information entered by a retrieval personnel to select a medical data. Each time a retrieval information is entered, all matching medical data are digitally numbered. In combination with the selected medical data, the retrieval information is searched for the presence of the medical data and the corresponding digital number when the medical data is displayed. The size of the digital number is associated with the similarity with the retrieval information. In this way, the deviation percentage corresponding to each retrieval information of the medical data is calculated to obtain the retrieval service information of the medical data. A retrieval analysis module is provided to periodically analyze the plurality of retrieval service information stored for each medical data. During the analysis, the plurality of retrieval service information stored for the medical data is determined to determine whether the analysis conditions are met by using the deviation percentage and the update over-limit value. The plurality of retrieval service information of the plurality of medical data that meet the conditions is stored. In this way, the retrieval information of all retrieval personnel based on the plurality of medical data is periodically screened to eliminate unnecessary retrieval information, thereby avoiding the waste of analysis and storage resources during the update of the retrieval whitelist of the plurality of medical data, improving the updating efficiency of the retrieval whitelist of the medical data, and further improving the efficiency and accuracy of retrieval during the medical data sharing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a system block diagram of the present invention;

[0027] Figure 2 Flow chart of the method of the present invention. DETAILED DESCRIPTION

[0028] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0029] See also Figure 1 、 Figure 2 , this application provides a blockchain-based medical data sharing system and method, including an information collection module and a medical data sharing service platform;

[0030] The information collection module is used to obtain the search information entered by the search personnel and transmit it to the medical data sharing service platform. The search information includes several search keywords;

[0031] A medical data sharing service platform is used to provide shared medical data retrieval services for search personnel. The medical data sharing service platform includes a retrieval service unit, a monitoring retrieval unit, and a selected update unit. The medical data sharing service platform receives the retrieval information input by the search personnel and transmits it to the retrieval service unit.

[0032] The search service unit stores a number of medical data that are authorized to be shared, including medical literature data, medical research data, and drug data. Each medical data corresponds to a search whitelist, which contains a number of search keywords.

[0033] After receiving the transmitted search information keyed in by the search personnel, the search service unit obtains a number of medical data that matches the search information from all medical data stored in the search service unit. In this application, if a search whitelist corresponding to a medical data contains a number of search keywords that are consistent with a number of search keywords in the search information, then the medical data matches the search information.

[0034] Calculate the similarity between each matched medical data and the search information respectively, and number each matched medical data in descending order of similarity, with the numbering starting from 1 and continuing thereafter. In this application, the algorithm for calculating the similarity can be any one of a string similarity algorithm, a simhash similarity algorithm, and a word2vec similarity algorithm;

[0035] The matching medical data are displayed to the search personnel in ascending numerical order for selection and review;

[0036] If the searcher does not select any medical data from all currently displayed medical data and calls the search box to re-enter the search information, the medical data numbered 1 is first extracted from all currently displayed medical data as the search response information of the searcher, and then the search box called by the searcher is monitored;

[0037] When the searcher is detected typing new search information in the search box, the search service unit acquires the search information in the search box and matches multiple medical data again according to the search information until the searcher selects a medical data;

[0038] In this application, the method for determining that a medical data is not selected is that the browsing time of each medical data currently displayed by the searcher does not exceed P1, where P1 is the preset standard browsing time for selection;

[0039] When it is detected that the search person has selected a medical data after inputting the search information multiple times, the monitoring and retrieval unit generates the search optimization information of the search person according to the preset generation rules. The generation rules are as follows:

[0040] S11: marking all search information entered by the searcher for the selected medical data as H1, H2, ..., Hh, in the order of entry, where h≥1;

[0041] S12: Searching all medical data matching the search information H1 to see whether there is any medical data selected by the searcher after multiple entries of the search information. If so, obtaining the numerical number A1 of the medical data selected by the searcher after multiple entries of the search information from all medical data matching the search information H1;

[0042] Using the formula Calculate the deviation percentage of the search information H1, where B1 is the total number of all medical data that match the search information H1. If no medical data exists, no processing is performed.

[0043] S13: searching, in sequence according to S12, all medical data matching the search information H2, H3, ..., Hh to see whether there is medical data selected by the searcher after multiple entries of the search information, and obtaining deviation percentages of the search information based on the search results;

[0044] S14: Generating search service information of medical data selected by the searcher after multiple search information input based on the obtained deviation percentages of the search information, wherein the deviation percentages of all the search information are arranged from left to right in the order in which the search information was input;

[0045] Transmit the retrieval service information of the medical data to a selected update unit for storage;

[0046] An update limit value is also pre-stored in the selected update unit. For the current optimization screening period, the selected update unit optimizes the retrieval service information of all medical data stored within the current optimization screening period. The optimization steps are as follows:

[0047] SS11: Obtain all the medical data corresponding to all the retrieval service information stored within the current optimization screening period and deduplicate it. Mark all the remaining medical data after deduplication as Z1, Z2,..., Zz, where z≥1;

[0048] SS12: Select medical data Z1 as the data to be optimized and screened. Mark all the retrieval service information of the data to be optimized and screened stored within the current optimization screening period as D1, D2,..., Dd, where d≥1;

[0049] SS13: Sequentially extract all the deviation percentages from the retrieval service information D1 from left to right and mark them as E1, E2,..., Ee;

[0050] SS14: Use the formula 1≤f≤e to calculate and obtain the retrieval deviation average ratio F1 of the retrieval service information D1. In the formula, Ef refers to each of the deviation percentages E1, E2,..., Ee;

[0051] SS15: Sequentially calculate and obtain the retrieval deviation average ratios F2, F3,..., Fd of the retrieval service information D2, D3,..., Dd according to SS11 to SS14;

[0052] SS16: Use the formula Calculate and obtain the deviation average ratio deviation G1 of the retrieval deviation average ratios F1, F2,..., Fd. In the formula, Ff refers to each of the retrieval deviation average ratios F1, F2,..., Fd. Compare the magnitudes of G1 and G. The G is a preset standard deviation average ratio value, and F is the average value of the retrieval deviation average ratios F1, F2,..., Fd at this time;

[0053] If G1≥G, then sequentially delete the corresponding Fg in descending order of |Fg - F| and calculate the deviation average ratio deviation G1 of the remaining Fg. Compare the magnitudes of G1 and G again until G1<G. Obtain the average value of the Fg participating in the calculation of G1 at this time and calibrate the average value as the retrieval deviation sub-ratio of the data to be optimized and screened in the current optimization screening period;

[0054] S17: Compare the retrieval deviation score ratio of the data to be optimized and screened in the current optimization screening cycle with the update over-limit value. If the retrieval deviation score ratio is smaller than the update over-limit value, it is determined that all the retrieval service information of the data to be optimized and screened stored in the current optimization screening cycle meets the analysis conditions, and analysis can be performed to update the retrieval whitelist of the data to be optimized and screened. Optimized screening data of the data to be optimized and screened in the current optimization screening cycle are generated based on all the retrieval service information of the data to be optimized and screened stored in the current optimization screening cycle, and the optimized screening data are stored for subsequent analysis. Otherwise, no processing is performed. The subsequent analysis process in this application includes the process of selecting a number of retrieval keywords from all the stored retrieval service information of the data to be optimized and screened and filling them into the retrieval whitelist of the medical data, and removing a number of search keywords from the retrieval whitelist of the medical data;

[0055] SS18: Select medical data Z2, Z3, ..., Zz in turn as the data to be optimized and screened, and determine whether all the retrieval service information of the medical data Z2, Z3, ..., Zz stored in the current optimization and screening cycle meets the analysis conditions according to SS12 to SS17.

[0056] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0057] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A blockchain-based medical data sharing system, characterized by: include: A search service unit, configured to obtain a plurality of medical data matching the search information according to the search information entered by the search personnel, wherein the search information includes a plurality of search keywords; The search service unit is further configured to calculate the similarity between each matched medical data and the search information, number each medical data in descending order of similarity, and display all matched medical data to the search personnel in sequence after numbering is completed; a monitoring and retrieval unit, configured to, upon detecting that a searcher has selected a medical data item after multiple entries of retrieval information, obtain a digital number of the selected medical data item from a plurality of medical data items that match the retrieval information according to the multiple entries of retrieval information, and generate retrieval service information of the selected medical data item according to the obtained digital numbers; The selected updating unit is used to periodically optimize and screen the retrieval service information of all stored medical data to periodically determine whether the stored medical data meet the analysis conditions, and store the retrieval service information of the medical data that meets the analysis standards.

2. A blockchain-based medical data sharing system according to claim 1, characterized in that: The numbers start from 1 and go on.

3. A blockchain-based medical data sharing system and method according to claim 1, characterized in that: All matching medical data will be displayed to the search personnel in ascending numerical order for selection and viewing.

4. A blockchain-based medical data sharing system and method according to claim 2, characterized in that: The steps for generating retrieval service information for selected medical data are as follows: S11: marking all search information entered by the searcher for the selected medical data as H1, H2, ..., Hh, in the order of entry, where h≥1; S12: Searching all medical data matching the search information H1 to see whether there is any medical data selected by the searcher after multiple entries of the search information. If so, obtaining the numerical number A1 of the medical data selected by the searcher after multiple entries of the search information from all medical data matching the search information H1; Using the formula Calculate the deviation percentage of the search information H1, where B1 is the total number of all medical data that match the search information H1. If no medical data exists, no processing is performed. S13: searching, in sequence according to S12, all medical data matching the search information H2, H3, ..., Hh to see whether there is medical data selected by the searcher after multiple entries of the search information, and obtaining deviation percentages of the search information based on the search results; S14: Generate retrieval service information of medical data selected by the retrieval personnel after multiple retrieval information input according to the obtained deviation percentages of the retrieval information, wherein the deviation percentages of all retrieval information are arranged from left to right in the order in which the retrieval information is input.

5. A blockchain-based medical data sharing system and method according to claim 1, characterized in that: The selected update unit has an update over-limit value pre-stored therein.

6. A blockchain-based medical data sharing system and method according to claim 5, characterized in that: The steps for selecting the update unit to determine whether all medical data stored in the current optimization screening cycle meet the analysis conditions are as follows: SS11: Obtain all medical data corresponding to all retrieval service information stored in the current optimization screening cycle and deduplicate them. All remaining medical data after deduplication are marked as Z1, Z2, ..., Zz, where z ≥ 1. SS12: Select medical data Z1 as the data to be optimized and screened, and mark all retrieval service information of the data to be optimized and screened stored in the current optimization and screening cycle as D1, D2, ..., Dd, where d≥1; SS13: Extract all the deviation percentages from the retrieval service information D1 in sequence from left to right and mark them as E1, E2, ..., Ee respectively; SS14: Utilizing Formulas Calculate the average retrieval deviation ratio F1 of the retrieval service information D1, where Ef refers to each of the deviation percentages E1, E2, ..., Ee; SS15: Calculate and obtain the retrieval deviation average ratios F2, F3, ..., Fd of the retrieval service information D2, D3, ..., Dd in sequence according to SS11 to SS14; SS16: Leveraging Formula Calculate and obtain the average deviation G1 of the average retrieval deviation ratios F1, F2, ..., Fd, where Ff refers to each of the average retrieval deviation ratios F1, F2, ..., Fd, and compare G1 with G, where G is a preset standard average deviation ratio and F is the average of the average retrieval deviation ratios F1, F2, ..., Fd at this time; If G1 ≥ G, then delete the corresponding Fg in sequence according to the order from large to small of |Fg - F| and calculate the deviation average ratio difference G1 of the remaining Fg. Compare the size of G1 and G again until G1 < G. Obtain the average value of Fg participating in the calculation of G1 at this time, and calibrate the average value as the retrieval deviation sub-ratio of the data to be optimized and screened in the current optimization screening cycle; SS17: Compare the size of the retrieval deviation sub-ratio of the data to be optimized and screened in the current optimization screening cycle with the updated over-limit value. If the retrieval deviation sub-ratio is less than the updated over-limit value, it is determined that all the retrieval service information of the data to be optimized and screened stored in the current optimization screening cycle meets the analysis conditions, otherwise no processing is performed; SS18: Select the medical data Z2, Z3, ..., Zz in sequence as the data to be optimized and screened, and determine whether all the retrieval service information of the medical data Z2, Z3, ..., Zz stored in the current optimization screening cycle meets the analysis conditions in sequence according to SS12 to SS17.

7. A blockchain-based medical data sharing system and method according to claim 6, characterized in that: SS17: Generate the optimized screening data of the data to be optimized and screened in the current optimization screening cycle according to all the retrieval service information of the data to be optimized and screened stored in the current optimization screening cycle, and store the optimized screening data.

8. A medical data sharing method based on blockchain, characterized in that: It includes the following steps: Step 1: The retrieval service unit obtains the retrieval information typed by the retrieval personnel and obtains several medical data that match the retrieval information. The retrieval information includes several retrieval keywords; Step 2: The retrieval service unit calculates the similarity between each matched medical data and the retrieval information, numbers each medical data in sequence according to the order from large to small of the similarity, and displays all the matched medical data to the retrieval personnel in sequence after the numbering is completed; Step 3: When the monitoring retrieval unit monitors that the retrieval personnel select a medical data after typing the retrieval information multiple times, it obtains the digital number of the selected medical data from several medical data that match the retrieval information according to the retrieval information typed multiple times, generates the retrieval service information of the selected medical data according to the obtained several digital numbers and transmits it to the selected update unit; Step 4: The selected update unit periodically optimizes and screens the retrieval service information of all the stored medical data, determines whether it meets the analysis conditions, and stores the retrieval service information of the medical data that meets the analysis conditions.

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