Systems and Methods for Enabling Data Transforms Across a Plurality of Task-Specific Orchestrations

1 . A method, comprising:

in accordance with determining that a prompt, received based on a user input, requests assistance with one or more clinical tasks, selecting, by a machine-learning model trained to select from among a plurality of task-specific components, a set of task-specific components from among the plurality of task-specific components based on the prompt;

obtaining orchestration data about the set of task-specific components, wherein each respective task-specific components in the set of task-specific components is configured to assist with a respective clinical task of the one or more clinical tasks;

determining, from the orchestration data, at least one data-compatibility criterion for clinical task data relating to the one or more clinical tasks;

receiving the clinical task data; and

in accordance with a determination that the clinical task data does not satisfy the at least one data-compatibility criterion, providing a notification to a user indicating that the one or more clinical tasks cannot be performed using the clinical task data.

2 . The method of claim 1 , further comprising:

identifying a set of one or more data interfaces based on the obtained orchestration data, wherein each respective data interface of the set of data interfaces corresponds to a respective task-specific component of the set of task-specific components, and wherein the at least one data-compatibility criterion is determined based on one or more attributes of the set of data interface.

3 . The method of claim 1 , further comprising:

in accordance with a determination that the clinical task data satisfies the at least one data-compatibility criterion, providing another notification to the user indicating that the clinical task data is validated for the one or more clinical tasks.

4 . The method of claim 1 , further comprising:

receiving the prompt as a textual input from the user;

identifying an intent of the textual input; and

determining that the prompt requests assistance with the one or more clinical tasks based on the identified intent.

5 . The method of claim 1 , wherein the clinical task data comprises image data, and wherein the at least one data-compatibility criterion relates to at least one of: a size of the image data, a resolution of the image data, and a color spectrum of the image data.

6 . The method of claim 1 , wherein the orchestration data comprises one or more of: one or more attributes for the set of task-specific machine-learning models, one or more input parameters for the set of task-specific machine-learning models, and one or more configuration parameters for the set of task-specific machine-learning models.

7 . The method of claim 1 , wherein the at least one data-compatibility criterion comprises at least one of: a data formatting requirement, a data type requirement, and a data labeling requirement.

8 . The method of claim 1 , wherein the plurality of task-specific components comprises a plurality of task-specific machine-learning models.

9 . The method of claim 1 , wherein the plurality of task-specific components comprises one or more transform components, each transform component of the one or more transform components configured to apply a transform to biological data to generate an output.

10 . The method of claim 1 , further comprising:

in accordance with a determination that the clinical task data satisfies the at least one data-compatibility criterion:

obtaining one or more task results by performing, via the set of task-specific components, the one or more clinical tasks; and

providing an output to the user indicating the one or more task results.

11 . The method of claim 10 , wherein the output comprises a natural language output that summarizes the one or more task results.

12 . The method of claim 10 , wherein the output is generated by a machine-learning component using the one or more task results.

13 . The method of claim 10 , further comprising obtaining subject data about a subject, wherein the output indicates how the one or more task results relate to the subject.

14 . The method of claim 10 , wherein the output is personalized to a particular subject.

15 . The method of claim 10 , wherein the user input includes a user query, and wherein the output provides an answer to the user query based on the one or more task results.

16 . The method of claim 15 , wherein the user query relates to a particular subject.

17 . 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:

in accordance with determining that a prompt, received based on a user input, requests assistance with one or more clinical tasks, selecting, by a machine-learning model trained to select from among a plurality of task-specific components, a set of task-specific components from among the plurality of task-specific components based on the prompt;

obtaining orchestration data about the set of task-specific components, wherein each respective task-specific components in the set of task-specific components is configured to assist with a respective clinical task of the one or more clinical tasks;

determining, from the orchestration data, at least one data-compatibility criterion for clinical task data relating to the one or more clinical tasks;

receiving the clinical task data; and

in accordance with a determination that the clinical task data does not satisfy the at least one data-compatibility criterion, providing a notification to a user indicating that the one or more clinical tasks cannot be performed using the clinical task data.

18 . The computing system of claim 17 , wherein the at least one data-compatibility criterion comprises at least one of: a data formatting requirement, a data type requirement, and a data labeling requirement.

19 . 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:

in accordance with determining that a prompt, received based on a user input, requests assistance with one or more clinical tasks, selecting, by a machine-learning model trained to select from among a plurality of task-specific components, a set of task-specific components from among the plurality of task-specific components based on the prompt;

obtaining orchestration data about the set of task-specific components, wherein each respective task-specific components in the set of task-specific components is configured to assist with a respective clinical task of the one or more clinical tasks;

determining, from the orchestration data, at least one data-compatibility criterion for clinical task data relating to the one or more clinical tasks;

receiving the clinical task data; and

in accordance with a determination that the clinical task data does not satisfy the at least one data-compatibility criterion, providing a notification to a user indicating that the one or more clinical tasks cannot be performed using the clinical task data.

20 . The non-transitory computer-readable storage medium of claim 19 , wherein the at least one data-compatibility criterion comprises at least one of: a data formatting requirement, a data type requirement, and a data labeling requirement.