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Prediction of codes across many different systems are supported through a single REST endpoint request:
Pass your clinical context in the request body and receive a structured list of medical codes ready for review.
1

Choose one or more coding systems

Set system to an array of one or more system identifiers. Systems are typically combined by encounter type — for example, icd10cm-outpatient + cpt for office visits and ED encounters, or icd10cm-inpatient + icd10pcs for hospital admissions. See Coding Systems for the full list.
2

Pass your clinical context

The context field is an array of context objects. Two input types are supported:
  • Texttype: "text" with the clinical text in text. Pass multiple objects to provide multiple context sources.
  • Documenttype: "documentId" with a document ID in documentId, referencing a document already stored in Corti.
3

Read the response

codes contains the medical entities the model predicts should be coded. candidates contains entities that are clinically relevant but not strictly required — optional codes surfaced for human review. usageInfo.creditsConsumed reports the credits used for the request, which is reflected in your account billing.

Examples

Notice the response includes codes from all requested systems in the same codes array, each tagged with its system value:

Next Steps

Coding Systems

Details on available systems and recommendations of pairings by use case.

Integration Guides

Learn how to combine code prediction with agents and client-side content to build coding workflows.

Codes and candidates

Learn more about the predict codes response message including two objects, codes and candidates.

Code filtering

Learn how to restrict codes the model may predict using the filter field.
Please contact us if you need help getting started or run into issues with your first request.