Abstract: Systems, methods, and devices for data ingestion and aggregation, file analysis, and predictive modeling. A method includes generating an aggregated data form comprising surgical preference data, wherein the aggregated data form identifies a plurality of medical items, and wherein the aggregated data form is associated with a surgeon, a facility, and a surgery type. The method includes electronically communicating with an inventory management solution associated with the facility to retrieve inventory data for the plurality of medical items. The method includes receiving from a machine learning algorithm an amendment suggestion for the aggregated data form, wherein the amendment suggestion comprises one or more of: an amendment to a quantity of a first medical item, an identity of a first product satisfying the first medical item, or an addition of a second medical item not included in the aggregated data form.

Abstract: Systems, methods, and devices for data ingestion and aggregation, file analysis, and predictive modeling. A method includes ingesting an unstructured file comprising text. The method includes providing the unstructured file to a file analysis machine learning algorithm configured to execute optical character recognition processing to identify one or more textual characters in the unstructured file. The method includes assigning the one or more identified textual characters to a data bucket associated with an aggregated data form. The method includes generating a virtual file comprising information from the aggregated data form, wherein the virtual file comprises structured data and unstructured data.

Abstract: A method includes receiving a user object specified by a user. A similarity score is computed using a similarity function between the user object and one or more candidate objects in a database based on respective feature vectors. A first subset of the one or more candidate objects is presented to the user based on the respective computed similarity scores. First feedback is received from the user about the first subset of candidate objects. The similarity function is adjusted based on the received first feedback.

Abstract: A method includes receiving a user object specified by a user. A similarity score is computed using a similarity function between the user object and one or more candidate objects in a database based on respective feature vectors. A first subset of the one or more candidate objects is presented to the user based on the respective computed similarity scores. First feedback is received from the user about the first subset of candidate objects. The similarity function is adjusted based on the received first feedback.