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Paper Citation Record · LEDGER

Generation of Synthetic Electronic Health Records Using a Federated GAN

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2109.02543.

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

pith.paper-citation-record.v1
2109.02543 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:26:54.504697Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T21:51:48.368271Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 152f2821-00bc-4caa-8064-c245631bc551 · inbound

Imputation of Longitudinal Data Using GANs: Challenges and Implications for Classification cites this paper.

Imputation of Longitudinal Data Using GANs: Challenges and Implications for Classification Generation of Synthetic Electronic Health Records Using a Federated GAN

Reference 204

Resolution
unresolved
no resolver link, observed 2026-08-06T23:26:54.504697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:26:54.504697Z digest=sha256:43a18c1a4c9194f0d22b7bc608c9fee3b530d0d71a748fdf0305f6fd0ed90a62

Observation d2439cf4-27e2-402b-b489-bb2f912e05d3 · inbound

Federated Timeline Synthesis: Scalable and Private Methodology For Model Training and Deployment cites this paper.

Federated Timeline Synthesis: Scalable and Private Methodology For Model Training and Deployment Generation of Synthetic Electronic Health Records Using a Federated GAN

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-06T21:51:48.438541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:51:47.035424Z digest=sha256:5a8ba3c2302bad7770afe18b01993e441c3e24894627a1a1f40c78f6d5968fd7