# US 2018/0322308 A1 · Computer system of computer servers and dedicated computer clients specially programmed to generate synthetic non-reversible electronic data records based on real-time electronic querying and methods of use thereof > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2018/0322308 A1 - Document ID: US20180322308A1 - Status: Published application - Kind: A1 - Application number: 15/968,194 - Filed: 2018-05-01 - Published: 2018-11-08 - Earliest claimed: 2016-05-11 - Assignees: MDClone Ltd. - Applicants: MDClone Ltd. - Inventors: Luz Erez - Web page: https://patentgrep.com/patent/US20180322308A1 ## CPC - G06F 21/6254: {by anonymising data, e.g. decorrelating personal data from the owner's identification} - G06F 3/0482: Interaction with lists of selectable items, e.g. menus - G06F 3/04847: Interaction techniques to control parameter settings, e.g. interaction with sliders or dials - G06F 16/24564: {Applying rules; Deductive queries} - G06F 16/248: Presentation of query results - G06F 16/335: Filtering based on additional data, e.g. user or group profiles (filtering in web context G06F16/9535, G06F16/9536) - G06F 16/9038: Presentation of query results - G06F 21/6245: {Protecting personal data, e.g. for financial or medical purposes} - G16H 10/60: for patient-specific data, e.g. for electronic patient records - G06F 21/602: {Providing cryptographic facilities or services} - H04L 9/0618: {Block ciphers, i.e. encrypting groups of characters of a plain text message using fixed encryption transformation} - H04L 2209/42: Anonymization, e.g. involving pseudonyms - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) ## Abstract In some embodiments, the present invention provides for an exemplary computer system which includes at least: a graphical user interface client; a dedicated application server; the dedicated application server is configured to connect to the graphical user interface client and an electronic source with electronic data records; where the electronic data records include real identification identifiers of real individuals; where the graphical user interface client is configured to generate at a graphical user interface that is configured to receive user authenticating credential information and to conduct a real-time electronic negotiation querying session between the user and the dedicated application server to generate a plurality of non-reversible synthetic electronic data records of a plurality of synthetic individuals, by utilizing at least one statistical technique so that the plurality of non-reversible synthetic electronic data records cannot be used to identify any real individual in the plurality of electronic data records. ## Claims ### Claim 1 A computer system, comprising: a non-transitory memory storing instructions and at least one processor; wherein, when executing the instructions, the at least one processor is configured to: receive at least one electronic query from a user, wherein the at least one electronic query comprises: a) at least one of: a plurality of personal event data parameters of at least one personal event or at least one demographic identifier, and b) a plurality of reference event data parameters of at least one reference event, wherein the plurality of reference event data parameters of the at least one reference event comprises a plurality of time-related property data parameters for at least one time-related property of the at least one reference event; assign an anonymity level to the user; identify, in response to the at least one electronic query, a matched subset of matched data records for a number of real individuals from a plurality of electronic data records stored in at least one electronic source, based at least in part on: a) the anonymity level of the user, b) the at least one personal event, and c) the at least one reference event; wherein the plurality of electronic data records comprises real identification identifiers of real individuals; generate, based at least in part on the matched subset, a plurality of non-reversible synthetic electronic data records of a plurality of synthetic individuals by at least one of: self-recalculation of discrete values of the matched subset or self-transformation of categorical values of the matched subset; generate at least one comparison report that analyzes all pairs of variables between the matched subset and the plurality of non-reversible synthetic electronic data records of the plurality of synthetic individuals to confirm that the plurality of non-reversible synthetic electronic data records of the plurality of synthetic individuals is statistically representative of the matched subset; wherein the plurality of non-reversible synthetic electronic data records of the plurality of synthetic individuals is unsuitable to be utilized to identify any real individual from the matched subset so as to protect privacy of the real individuals associated with the matched subset; and wherein each respective synthetic identification identifier of the plurality of non-reversible synthetic electronic data records of the plurality of synthetic individuals corresponds to at least one real identification identifier of a real individual in the matched subset to avoid a generalization of the matched subset. ### Claim 2 (depends on 1) The computer system of claim 1, wherein the anonymity level is assigned based at least in part on an entity affiliation of the user. ### Claim 3 (depends on 1) The computer system of claim 1, wherein the self-recalculation, the self-transformation, or both are based on a conditional probability methodology. ### Claim 4 (depends on 1) The computer system of claim 1, wherein the at least one comparison report is generated based at least in part on Pearson's correlation for each pairs of variables. ### Claim 5 (depends on 1) The computer system of claim 1, wherein the plurality of electronic data records are a plurality of electronic medical records. ### Claim 6 (depends on 1) The computer system of claim 1, wherein the at least one processor is further configured to: conduct, based at least in part on the at least one electronic query, at least one real-time electronic negotiation querying session with the user; wherein the at least one real-time electronic negotiation querying session allows the user to iteratively adjust the plurality of personal event data parameters of the at least one personal event and at least one of the at least one demographic identifier and the plurality of reference event data parameters of the at least one reference event so that, based on the anonymity level of the user, the matched subset contains a minimal desired number of real individuals associated with the plurality of electronic data records of the at least one electronic source matching the at least one personal event and the at least one reference event. ### Claim 7 (depends on 1) The computer system of claim 1, wherein the plurality of non-reversible synthetic electronic data records of the plurality of synthetic individuals are self-compliant to at least one privacy policy. ### Claim 8 (depends on 7) The computer system of claim 7, wherein each respective synthetic identification identifier is a de-identification identifier that is required, based on the at least one privacy policy, to be removed from the matched subset when the matched subset would be outputted to the user. ### Claim 9 A computer-implemented method, comprising: receiving, by a computer processor, at least one electronic query from a user, wherein the at least one electronic query comprises: a) at least one of: a plurality of personal event data parameters of at least one personal event or at least one demographic identifier, and b) a plurality of reference event data parameters of at least one reference event, wherein the plurality of reference event data parameters of the at least one reference event comprises a plurality of time-related property data parameters for at least one time-related property of the at least one reference event; assign, by the computer processor, an anonymity level to the user; identifying, in response to the at least one electronic query, a matched subset of matched data records for a number of real individuals from a plurality of electronic data records stored in at least one electronic source, based at least in part on: a) the anonymity level of the user, b) the at least one personal event, and c) the at least one reference event; wherein the plurality of electronic data records comprises real identification identifiers of real individuals; generating, by the computer processor, based at least in part on the matched subset, a plurality of non-reversible synthetic electronic data records of a plurality of synthetic individuals by at least one of: self-recalculation of discrete values of the matched subset or self-transformation of categorical values of the matched subset; generating, by the computer processor, at least one comparison report that analyzes all pairs of variables between the matched subset and the plurality of non-reversible synthetic electronic data records of the plurality of synthetic individuals to confirm that the plurality of non-reversible synthetic electronic data records of the plurality of synthetic individuals is statistically representative of the matched subset; wherein the plurality of non-reversible synthetic electronic data records of the plurality of synthetic individuals is unsuitable to be utilized to identify any real individual from the matched subset so as to protect privacy of the real individuals associated with the matched subset; and wherein each respective synthetic identification identifier of the plurality of non-reversible synthetic electronic data records of the plurality of synthetic individuals corresponds to at least one real identification identifier of a real individual in the matched subset so as to avoid a generalization of the matched subset. ### Claim 10 (depends on 9) The method of claim 9, wherein the anonymity level is assigned based at least in part on an entity affiliation of the user. ### Claim 11 (depends on 9) The method of claim 9, wherein the self-recalculation, the self-transformation, or both are based on a conditional probability methodology. ### Claim 12 (depends on 9) The method of claim 9, wherein the at least one comparison report is generated based at least in part on Pearson's correlation for each pairs of variables. ### Claim 13 (depends on 9) The method of claim 9, wherein the plurality of electronic data records are a plurality of electronic medical records. ### Claim 14 (depends on 9) The method of claim 9, wherein the method further comprises: conduct, based at least in part on the at least one electronic query, by the computer processor, at least one at least one real-time electronic negotiation querying session with the user; wherein the at least one real-time electronic negotiation querying session allows the user to iteratively adjust the plurality of personal event data parameters of the at least one personal event and at least one of the at least one demographic identifier and the plurality of reference event data parameters of the at least one reference event so that, based on the anonymity level of the user, the matched subset contains a minimal desired number of real individuals associated with the plurality of electronic data records of the at least one electronic source matching the at least one personal event and the at least one reference event. ### Claim 15 (depends on 9) The method of claim 9, wherein the plurality of non-reversible synthetic electronic data records of the plurality of synthetic individuals are self-compliant to at least one privacy policy. ### Claim 16 (depends on 15) The method of claim 15, wherein each respective synthetic identification identifier is a de-identification identifier that is required, based on the at least one privacy policy, to be removed from the matched subset when the matched subset would be outputted to the user.