Systems and Methods for Deploying a Machine-Learning Model for Performing a Specific Clinical Task

A computing system, comprising:

• control circuitry;
• memory;
• and
• one or more sets of instructions stored in the memory and configured for execution by the control circuitry, the one or more sets of instructions comprising instructions for:
• receiving, at a first computing system in communication with a machine-learning model that was trained to assist in performing one clinical task, a prompt, wherein the one clinical task is:
• (i) generating a report of a patient's medical records,
• (ii) guiding a patient through a care plan,
• (iii) creating patient care guidelines based on a patient's health profile,
• (iii) identifying patients requiring follow-up at a hospital,
• (v) identifying changes in a standard of care for a disease setting, or
• (vi) evaluating unstructured data associated with a patient to identify a cohort of similar patients;
• in response to receiving the prompt, generating, at the first computing system, a natural-language response that is responsive to the prompt and is based on an analysis by the machine-learning model of a repository of data that is determined to be relevant to the prompt;
• and
• providing the natural-language response to a second computing system that is distinct from the first computing system.

A non-transitory computer-readable storage medium storing one or more sets of instructions configured for execution by a computing device having control circuitry and memory, the one or more sets of instructions comprising instructions for:

• receiving, at a first computing system in communication with a machine-learning model that was trained to assist in performing one clinical task, a prompt, wherein the one clinical task is:
• (i) generating a report of a patient's medical records,
• (ii) guiding a patient through a care plan,
• (iii) creating patient care guidelines based on a patient's health profile,
• (iii) identifying patients requiring follow-up at a hospital,
• (v) identifying changes in a standard of care for a disease setting, or
• (vi) evaluating unstructured data associated with a patient to identify a cohort of similar patients;
• in response to receiving the prompt, generating, at the first computing system, a natural-language response that is responsive to the prompt and is based on an analysis by the machine-learning model of a repository of data that is determined to be relevant to the prompt;
• and
• providing the natural-language response to a second computing system that is distinct from the first computing system.