Abstract: Described herein are techniques for performing a task using a trained external machine learning model. In some embodiments, a user request comprising a task and one or more protected health information (PHI) parameters associated with a patient may be received. Using one or more trained machine learning models, the PHI parameters may be extracted and a revised user request may be generated by replacing the PHI parameters with one or more synthetic PHI parameters. The revised user request may be provided to the trained external machine learning model and a response to the task comprising the synthetic PHI parameters may be received. The trained machine learning models may generate a revised response to the task by replacing the synthetic PHI parameters with the PHI parameters of the user request.

Abstract: Described herein are techniques for performing a task using a trained external machine learning model. In some embodiments, a user request comprising a task and one or more protected health information (PHI) parameters associated with a patient may be received. Using one or more trained machine learning models, the PHI parameters may be extracted and a revised user request may be generated by replacing the PHI parameters with one or more synthetic PHI parameters. The revised user request may be provided to the trained external machine learning model and a response to the task comprising the synthetic PHI parameters may be received. The trained machine learning models may generate a revised response to the task by replacing the synthetic PHI parameters with the PHI parameters of the user request.