Paper Citation Record · LEDGER

Predicting Survival of Hemodialysis Patients using Federated Learning

As of 12 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2412.10919.

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

pith.paper-citation-record.v1
2412.10919 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:31:48.118544Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

24 of 24 outbound references displayed

verified exact9
verified fuzzy2
unresolved11
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7a2a251a-269e-4199-ba57-822296533e43 · outbound

This paper cites an unresolved cited work.

Predicting Survival of Hemodialysis Patients using Federated Learning Unresolved cited work

Reference 1

Resolution: verified exact; doi, observed 2026-08-11T15:31:48.276047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b1edb796-5ef2-49ba-82b6-938391723ac0 · outbound

This paper cites an unresolved cited work.

Predicting Survival of Hemodialysis Patients using Federated Learning Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-11T15:31:48.985963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 442754cb-0538-4c25-8674-d78de3459966 · outbound

This paper cites Survival analysis of patients on maintenance hemodialysis.

Predicting Survival of Hemodialysis Patients using Federated Learning Survival analysis of patients on maintenance hemodialysis

Reference 3

Resolution: metadata mismatch; raw_fallback, observed 2026-08-11T15:31:48.920425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 64cd3c8a-4693-47a7-97c0-5a18db84d550 · outbound

This paper cites S., & Belmonte, A.

Predicting Survival of Hemodialysis Patients using Federated Learning S., & Belmonte, A

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T15:31:48.014496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b17b6b9e-599a-44b9-9137-d0910a736af6 · outbound

This paper cites Data -driven, two -stage machine learning algorithm -based prediction scheme for assessing 1-year and 3-year mortality risk in chronic hemodialysis patients.

Predicting Survival of Hemodialysis Patients using Federated Learning Data -driven, two -stage machine learning algorithm -based prediction scheme for assessing 1-year and 3-year mortality risk in chronic hemodialysis patients

Reference 5

Resolution: verified exact; doi, observed 2026-08-11T15:31:48.259823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 02293789-b15c-43d2-a280-e57dddbfa62d · outbound

This paper cites M., Griffith, J.

Predicting Survival of Hemodialysis Patients using Federated Learning M., Griffith, J

Reference 6

Resolution: verified exact; doi, observed 2026-08-11T15:31:48.245342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c4aaafa3-b806-4b7a-9ce9-4863dd20e977 · outbound

This paper cites an unresolved cited work.

Predicting Survival of Hemodialysis Patients using Federated Learning Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T15:31:48.031534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa112090-8e0c-4949-ba3f-ded85615db5a · outbound

This paper cites Communication-Efficient Learning of Deep Networks from Decentralized Data.

Predicting Survival of Hemodialysis Patients using Federated Learning Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T15:31:48.036681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49ec3ece-ec06-40db-b88a-a87a476781d6 · outbound

This paper cites an unresolved cited work.

Predicting Survival of Hemodialysis Patients using Federated Learning Unresolved cited work

Reference 9

Resolution: verified exact; raw_fallback, observed 2026-08-11T15:31:48.668740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9e84539c-10d6-4fa0-8988-25923baf199f · outbound

This paper cites Federated Survival Analysis with Discrete-Time Cox Models.

Predicting Survival of Hemodialysis Patients using Federated Learning Federated Survival Analysis with Discrete-Time Cox Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T15:31:48.047330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64790293-ae92-40d6-86dd-441d01e27584 · outbound

This paper cites Federated Cox Proportional Hazards Model with multicentric privacy -preserving LASSO feature selection for survival analysis from the perspective of personalized medicine,.

Predicting Survival of Hemodialysis Patients using Federated Learning Federated Cox Proportional Hazards Model with multicentric privacy -preserving LASSO feature selection for survival analysis from the perspective of personalized medicine,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T15:31:48.051941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bff3ac51-445f-4a3d-bfdf-f6317bcc1083 · outbound

This paper cites VERTICOX: Vertically Distributed Cox Proportional Hazards Model Using the Alternating Direction Method of Multipliers,.

Predicting Survival of Hemodialysis Patients using Federated Learning VERTICOX: Vertically Distributed Cox Proportional Hazards Model Using the Alternating Direction Method of Multipliers,

Reference 12

Resolution: verified exact; raw_fallback, observed 2026-08-11T15:31:48.468015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ead135ca-c126-45c3-8256-47d938bb430a · outbound

This paper cites R., Price, G., Field, M., Sarup, N., Zukauskaite, R., Johansen, J., Eriksen, J.

Predicting Survival of Hemodialysis Patients using Federated Learning R., Price, G., Field, M., Sarup, N., Zukauskaite, R., Johansen, J., Eriksen, J

Reference 13

Resolution: verified exact; doi, observed 2026-08-11T15:31:48.230636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 790b6794-5b1b-4021-92bc-696bfe15333c · outbound

This paper cites FedPseudo: Pseudo value-based Deep Learning Models for Federated Survival Analysis.

Predicting Survival of Hemodialysis Patients using Federated Learning FedPseudo: Pseudo value-based Deep Learning Models for Federated Survival Analysis

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T15:31:48.066832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39cecf34-c788-442b-864a-afe06c16ffea · outbound

This paper cites Federated Learning Approach for Breast Cancer Detection Based on DCNN,.

Predicting Survival of Hemodialysis Patients using Federated Learning Federated Learning Approach for Breast Cancer Detection Based on DCNN,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T15:31:48.072546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ea01bfb-c7ff-4784-8ad9-da16b5b1b606 · outbound

This paper cites K., Akhtar, S.

Predicting Survival of Hemodialysis Patients using Federated Learning K., Akhtar, S

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:31:48.970974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 28a4b130-1381-45ed-9f63-3842cea91ae5 · outbound

This paper cites M., & Grambsch, P.

Predicting Survival of Hemodialysis Patients using Federated Learning M., & Grambsch, P

Reference 17

Resolution: malformed identifier; no resolver link, observed 2026-08-11T15:31:48.082139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f8ebb46-cb83-4719-8e63-363e64446584 · outbound

This paper cites & General Electric Research and Development Center.

Predicting Survival of Hemodialysis Patients using Federated Learning & General Electric Research and Development Center

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:31:48.953052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 689a9707-a5be-4b1e-b5a1-56d75c6c6830 · outbound

This paper cites an unresolved cited work.

Predicting Survival of Hemodialysis Patients using Federated Learning Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-11T15:31:48.935655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e454f321-3936-4301-afdc-8b4c80b4a0e0 · outbound

This paper cites L., Shaham, U., Cloninger, A., Bates, J., Jiang, T., & Kluger, Y.

Predicting Survival of Hemodialysis Patients using Federated Learning L., Shaham, U., Cloninger, A., Bates, J., Jiang, T., & Kluger, Y

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T15:31:48.097298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1492abd5-07cf-4047-bd6c-694b00f538ed · outbound

This paper cites an unresolved cited work.

Predicting Survival of Hemodialysis Patients using Federated Learning Unresolved cited work

Reference 21

Resolution: verified exact; doi, observed 2026-08-11T15:31:48.193053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1ef6cb55-88d2-4726-9578-419703bc8248 · outbound

This paper cites Random survival forests.

Predicting Survival of Hemodialysis Patients using Federated Learning Random survival forests

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T15:31:48.107148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfc35682-9d7f-4e35-a145-dd07dfb8f810 · outbound

This paper cites Addressing Data Heterogeneity in Federated Learning of Cox Proportional Hazards Models.

Predicting Survival of Hemodialysis Patients using Federated Learning Addressing Data Heterogeneity in Federated Learning of Cox Proportional Hazards Models

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:31:48.165514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 965d77ae-4769-41e7-a4ef-29a459f0503e · outbound

This paper cites Federated Survival Forests.

Predicting Survival of Hemodialysis Patients using Federated Learning Federated Survival Forests

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:31:48.296726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

No inbound Pith citation observations are available.