Paper Citation Record · LEDGER

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation

As of 18 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2606.28346.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2606.28346 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T11:09:43.602086Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

verified exact0
verified fuzzy36
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 434b8683-866b-47bf-8b1e-297f8517b1f7 · outbound

This paper cites Dai, Nissan Hajaj, Michaela Hardt, Peter J.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Dai, Nissan Hajaj, Michaela Hardt, Peter J

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.612044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9bfe6023-e99b-4768-bf7b-050b8fcee675 · outbound

This paper cites A guide to deep learning in healthcare.Nature Medicine, 25(1):24–29, 2019.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation A guide to deep learning in healthcare.Nature Medicine, 25(1):24–29, 2019

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.614000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7e7b0e11-ad70-4cc3-8ab6-98cc2b77665c · outbound

This paper cites an unresolved cited work.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-07-09T11:36:12.602172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b1f67fbf-7f67-4b5f-a1df-a25c57e06173 · outbound

This paper cites Anonymising and sharing individual patient data.BMJ, 350:h1139, 2015.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Anonymising and sharing individual patient data.BMJ, 350:h1139, 2015

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.649657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8f4e1196-49e6-45bf-a34c-dc61c9b52eb2 · outbound

This paper cites Beyond safe harbor: Automatic discovery of health information de-identification policy alternatives.Journal of the American Medical Informatics Association, 17(6):706–712, 2010.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Beyond safe harbor: Automatic discovery of health information de-identification policy alternatives.Journal of the American Medical Informatics Association, 17(6):706–712, 2010

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.651542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c717fdc7-ec22-44e9-9e48-bf4fc62e5ab7 · outbound

This paper cites Chen, Ming Y.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Chen, Ming Y

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.653141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3dc0e3ae-fe9a-40c4-bd72-bbeb1863bb6e · outbound

This paper cites an unresolved cited work.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-07-09T11:36:12.655103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f864d892-fa3e-4056-adf1-13b4df890a74 · outbound

This paper cites Department of Health and Human Services.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Department of Health and Human Services

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.658681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ac1c28d1-e562-417f-be97-2456119ff619 · outbound

This paper cites Regulation (EU) 2016/679 of the european parliament and of the council on the protection of natural persons with regard to the processing of personal data (GDPR).

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Regulation (EU) 2016/679 of the european parliament and of the council on the protection of natural persons with regard to the processing of personal data (GDPR)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.642466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3822cd36-4785-4aa4-94b0-8d9cb71196e1 · outbound

This paper cites Harris, K.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Harris, K

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.640512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 99896dec-6d4e-48c1-91e3-8a3c05ca8a68 · outbound

This paper cites Data structures for statistical computing in Python.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Data structures for statistical computing in Python

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.644259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5bb08ab2-cfe7-45ce-9a0d-1212c0f07801 · outbound

This paper cites PyTorch: An imperative style, high-performance deep learning library.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation PyTorch: An imperative style, high-performance deep learning library

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.647969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ecb74a7d-8d17-47bb-b546-2b5f09b82f9c · outbound

This paper cites TensorFlow: A system for large-scale machine learning.Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI), pages 265–283, 2016.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation TensorFlow: A system for large-scale machine learning.Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI), pages 265–283, 2016

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.666254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 05d2b00f-7090-4bfa-8803-a6a295b0a8b2 · outbound

This paper cites Scikit- learn: Machine learning in Python.Journal of Machine Learning Research, 12:2825–2830, 2011.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Scikit- learn: Machine learning in Python.Journal of Machine Learning Research, 12:2825–2830, 2011

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.621876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4d747504-d527-4249-89f6-edda82a55116 · outbound

This paper cites Dask: Parallel computation with blocked algorithms and task scheduling.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Dask: Parallel computation with blocked algorithms and task scheduling

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.624147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a2e7616c-ab9f-49f4-bba3-8f357390bda4 · outbound

This paper cites Xin, Patrick Wendell, Tathagata Das, Michael Armbrust, Ankur Dave, Xiangrui Meng, Josh Rosen, Shivaram Venkataraman, Michael J.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Xin, Patrick Wendell, Tathagata Das, Michael Armbrust, Ankur Dave, Xiangrui Meng, Josh Rosen, Shivaram Venkataraman, Michael J

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.626324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c4e3a264-bef2-4e54-9ec7-863c22c356f8 · outbound

This paper cites Jupyter notebooks – a publishing format for reproducible computational workflows.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Jupyter notebooks – a publishing format for reproducible computational workflows

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.615931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 708098bc-7aca-47e3-a351-f96b0b645633 · outbound

This paper cites Transformers: State- of-the-art natural language processing.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Transformers: State- of-the-art natural language processing

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.664393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation acc549e4-8f41-4ae3-bb55-a6b24b836db1 · outbound

This paper cites Pfeffer, Jason Fries, and Nigam H.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Pfeffer, Jason Fries, and Nigam H

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.617942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3ce9a2c0-a432-43e9-8dd0-602b3964b5e5 · outbound

This paper cites an unresolved cited work.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-07-09T11:36:12.598682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5a412958-7e75-4b62-8e18-648f7aba3864 · outbound

This paper cites uv: An extremely fast Python package and project manager.https://github.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation uv: An extremely fast Python package and project manager.https://github

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.597023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 53601d7f-e203-482e-84ff-32d219a699ed · outbound

This paper cites Synthea: Synthetic patient population simulator.https://github.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Synthea: Synthetic patient population simulator.https://github

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.600694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 33da728c-1cde-4e3e-b592-694d15c06d35 · outbound

This paper cites Implementing a generic framework for the simulation of synthetic patient populations and electronic health records.Studies in Health Technology and Informatics, 281:123–127, 2021.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Implementing a generic framework for the simulation of synthetic patient populations and electronic health records.Studies in Health Technology and Informatics, 281:123–127, 2021

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.608401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 32a73cef-8698-446e-97e3-99b57cd98be0 · outbound

This paper cites HL7 FHIR: An agile and RESTful approach to healthcare information exchange.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation HL7 FHIR: An agile and RESTful approach to healthcare information exchange

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.604194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e623a2de-3de9-4b92-8cc6-9c1942ec3ef4 · outbound

This paper cites HL7 FHIR Release 4.https://www.hl7.org/fhir/R4/, 2019.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation HL7 FHIR Release 4.https://www.hl7.org/fhir/R4/, 2019

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.606069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1e576c77-5f07-4d03-b8c8-69c84425007d · outbound

This paper cites SNOMED CT: Systematized nomenclature of medicine – clinical terms.https://www.snomed.org/, 2024.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation SNOMED CT: Systematized nomenclature of medicine – clinical terms.https://www.snomed.org/, 2024

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.595257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 128bb82c-9cb7-4663-8353-76fb008cae0e · outbound

This paper cites LOINC: Logical observation identifiers names and codes.https://loinc.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation LOINC: Logical observation identifiers names and codes.https://loinc

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.619802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a0162cf8-9670-429e-805c-69aea1bcd187 · outbound

This paper cites Mandel, David A.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Mandel, David A

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.660264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 13f36e06-17ce-4dbb-9598-90a958c90650 · outbound

This paper cites Mooney, and Bradley A.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Mooney, and Bradley A

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.646106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation be67306f-14d6-43fc-8796-9a6f63d59e84 · outbound

This paper cites Synthea novel coronavirus (covid-19) model and synthetic data set.Intelligence-Based Medicine, 1:100007, 2020.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Synthea novel coronavirus (covid-19) model and synthetic data set.Intelligence-Based Medicine, 1:100007, 2020

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.662297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 935dd455-2f3c-4eab-b82e-70dd6c830590 · outbound

This paper cites Apache Airflow.https://airflow.apache.org/, 2024.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Apache Airflow.https://airflow.apache.org/, 2024

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.633394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 37b312a7-024c-41c4-989b-c8ac64db7ccb · outbound

This paper cites Johnson, Tom J.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Johnson, Tom J

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.614970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2503af7d-2b86-470e-9322-0a894739983d · outbound

This paper cites Johnson, Lucas Bulgarelli, Lu Shen, Alvin Gayles, Ayad Shammout, Steven Horng, Tom J.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Johnson, Lucas Bulgarelli, Lu Shen, Alvin Gayles, Ayad Shammout, Steven Horng, Tom J

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.631596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e014a73c-e50b-4b41-8530-00ba4a237666 · outbound

This paper cites Pollard, Alistair E.W.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Pollard, Alistair E.W

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.635179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 23c3429c-c376-42fa-9777-e51db43e2eda · outbound

This paper cites Gomez, ŁukaszKaiser, andIlliaPolosukhin.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Gomez, ŁukaszKaiser, andIlliaPolosukhin

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.657007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3d32b393-a078-415d-ad00-75c28d380127 · outbound

This paper cites Apache Parquet.https://parquet.apache.org/, 2024.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Apache Parquet.https://parquet.apache.org/, 2024

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.636905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e6fc1c95-9425-4be3-a651-bdc9ee47bfe3 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Communication-efficient learning of deep networks from decentralized data

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.628266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e4d07f8e-e48d-42fb-b59e-a28d93b0f68c · outbound

This paper cites Stewart, and Jimeng Sun.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Stewart, and Jimeng Sun

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.629920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a0e36c8e-f5e9-4292-889e-1d594ac0d9ab · outbound

This paper cites Differential privacy.

PySynthea: A Python-Native Framework for Scalable Synthetic Healthcare Data Generation Differential privacy

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T11:36:12.638592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

No inbound Pith citation observations are available.