Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1903.09296.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T13:25:35.797196Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-14T11:57:36.707426Z
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 4bcec1a1-8bae-4fa4-9c2f-f986dc5794d1 · inbound
Two-stage Federated Phenotyping and Patient Representation Learning cites this paper.
Two-stage Federated Phenotyping and Patient Representation Learning Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T13:25:35.797196Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d2c699c8-1cf6-4888-9680-3f894d071017 · inbound
Federated Learning: Challenges, Methods, and Future Directions cites this paper.
Federated Learning: Challenges, Methods, and Future Directions Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records
Reference 51
- Resolution
- verified exact
- local_arxiv, observed 2026-08-14T11:57:36.711481Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.