Abstract: A method for implementing a targeted medical outputs is disclosed. The method may comprise: receiving first user data associated with a user from an external server; receiving second user data associated with the user from an internal server; processing the first user data and the second user data at a data fabric structure to generate domains; receiving the domains as an input at a machine learning model trained to generate a machine learning output; receiving at a database cube the machine learning output; performing one or more database cube processing operations on the machine learning output to generate a database cube output; transmitting the database cube output to one or more outputs, identified based on the one or more markers.

Abstract: A computer-implemented method for deploying database management tools is disclosed. The method may comprise: receiving user data sets including biological data, previous medical history data, or previous schema data for users; determining one or more groups; receiving a first user data set of a first user; identifying a first group for the first user; generating a plurality of schema plans for the first group; identifying a first schema including a first treatment; determining a schedule; transmitting first electronic content; receiving a signal comprising updated information for the first user; parsing the updated information; and modifying the schema based on the parsed updated information.

Abstract: A method for outputting new target populations for system initiation using a first machine learning model and a second machine learning model, the method comprising: receiving, user data; storing the user data; identifying a target population based on the user data to select groups of individuals not currently serviced by a specific provider; identifying a population criteria for the target population; applying a population criteria to target population user data of the target population; determining that the population criteria for the target population is above a first threshold population criteria; receiving initiated population data for an initiated population; and determining that the system initiation meets an improvement threshold probability to improve the population criteria by a second threshold amount.

Abstract: A computer-implemented method for implementing a data fabric structure is disclosed. The method may comprise: receiving user data associated with a user from an external server via a secure network connection; storing the user data on a cloud-based data lake; transmitting the user data to a staging table; adding, to the staging table, user identification data and metadata; modifying the user data based on a determined correlation between the user data, the user identification data, and metadata to generate modified user data; comparing the modified user data and prior user data to determine a difference; upon determining the difference does not exceed a threshold, extracting, using a trained machine learning model, relevant data from the modified user data; formatting the relevant data into atomic data; generating a plurality of domains based on the atomic data, and presenting via a graphical user interface, graphical depictions of the plurality of domains.