Cohort eligibility classification

Apply explicitly supplied study criteria to synthetic records.

Step 01

Define and Align

Upload sample data, define your output schema, and provide feedback on the hardest cases.

Output schema
EligibleYes / No / Unknown

Whether the supplied record meets every explicit study criterion.

  • true
  • false
  • null
Unmet criteriaList of values

Criteria the record explicitly fails.

Missing evidenceList of values

Required evidence that is absent, such as documented consent.

app.sutro.sh/functions/cohort-eligibility-classification
Collecting feedback · 1/3
Apply explicitly supplied study criteria to synthetic records.
Example 1 of 3

Boundary criterion

Model input

Example study requires age at least 18. Synthetic subject is 17.

Model output
Eligible
Unmet criteriaMultiple values
Missing evidenceMultiple values

Step 02

Model Sweep

Compare quality and cost on your examples, then choose a model or use Sutro’s default.

Compare models on expert agreement and cost. The interactive chart uses illustrative measurements.

Illustrative sweep · select Value or Best to use that model in your function.

Step 03

Deployment

Call Sutro Functions like any other software. Swap the model as soon as something more performant is released.

Selected modelWaiting for sweep results.

Real-time

import sutro as so

input_data = {
    "text": "Example study requires age at least 18. Synthetic subject is 17."
}

result = so.run_function(
    "cohort-eligibility-classification",
    input_data,
)

Batch

import sutro as so

job_id = so.batch_run_function(
    name="cohort-eligibility-classification",
    data="cohort_eligibility_classification.csv",
)
results = so.await_job_completion(job_id)

Ready to get started?

Book time with the team

Join the self-serve waitlist

What are your bottlenecks? (Select any that apply)