Authenticated customization of machine-learning models

A system comprising:

• one or more processing systems;
• and
• one or more computer-readable media storing instructions which, when executed by the one or more processing systems, cause the system to perform operations comprising:
• accessing a message that includes timestamp data and user identification data;
• identifying a training group of secured data entities including patient information, wherein each secured data entity in the training group:
• (i) is included in an appointment dataset associated with the user identification data, and
• (ii) includes appointment time data within a time window that is based on the timestamp data;
• determining, based on the training group of the secured data entities, at least one training dataset;
• modifying at least one pre-trained machine-learning model based on the at least one training dataset;
• and
• providing, during an authenticated network session associated with the user identification data, the at least one modified pre-trained machine-learning model.

One or more non-transitory computer-readable media storing instructions which, when executed by one or more processors, cause a system to perform operations comprising:

• accessing a message that includes timestamp data and user identification data;
• identifying a training group of data entities including patient information, wherein each data entity in the training group:
• (i) is included in an appointment dataset associated with the user identification data, and
• (ii) includes appointment time data within a time window that is based on the timestamp data;
• determining, based on the training group of the data entities, at least one training dataset;
• modifying at least one pre-trained machine-learning model based on the at least one training dataset;
• and
• providing, during an authenticated network session associated with the user identification data, the at least one modified pre-trained machine-learning model.