Generate synthetic patient data for machine learning

Created by

John

Actor

Synthea - Create Synthetic FHIR Compliant Health Records

Generate synthetic patient records as FHIR R4 bundles for machine learning, with no real PHI. Set population size, age range, state, and random seed.

Try for free

Synthea - Create Synthetic FHIR Compliant Health Recordsjohnvc/synthea-medical-record-generator-api

Patient Count

Generation Timestamp

Generation Summary

Generated Files

Input

Population Size(required):10

Random Seed:1

Age Range:18-65

State:Massachusetts

Output fields

Patient Count

Generation Timestamp

Generation Summary

Generated Files

How it works

Sign up on Apify or log in

The Synthea - Create Synthetic FHIR Compliant Health Records Actor is ready to run with the inputs already set for "Generate synthetic patient data for machine learning". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Generate synthetic patient data for machine learning" task

The Synthea - Create Synthetic FHIR Compliant Health Records Actor will start running based on the input automatically. You can also change all the input fields, like population size, random seed, and more, to match your specific use case.

Receive the "Generate synthetic patient data for machine learning" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as patient count, generation timestamp, generation summary, and more.

Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Generate synthetic patient data for machine learning" task via API.