Paper Citation Record · LEDGER

Pretraining EHR Foundation Models with Patient-Aware Sampling

As of 10 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2607.22114.

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

pith.paper-citation-record.v1
2607.22114 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T05:46:45.328304Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

40 of 40 outbound references displayed

verified exact0
verified fuzzy0
unresolved40
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 099b076e-cf8e-4b1b-9191-c313d3bbd313 · outbound

This paper cites Layer Normalization.

Pretraining EHR Foundation Models with Patient-Aware Sampling Layer Normalization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:42.045576Z

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Observation 0e853ccd-61d5-477b-9f60-27493a1f4cda · outbound

This paper cites Analysing The Impact of Sequence Composition on Language Model Pre-Training.

Pretraining EHR Foundation Models with Patient-Aware Sampling Analysing The Impact of Sequence Composition on Language Model Pre-Training

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:42.088536Z

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Observation 5300e691-4e30-44ea-9dca-63570c9d5c69 · outbound

This paper cites Proceedings of the 38th International Conference on Machine Learning , series =.

Pretraining EHR Foundation Models with Patient-Aware Sampling Proceedings of the 38th International Conference on Machine Learning , series =

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:42.194518Z

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Observation 4b3e595e-19e6-464b-9d0d-d492b80ab28e · outbound

This paper cites Advances in Neural Information Processing Systems , editor=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Advances in Neural Information Processing Systems , editor=

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:42.253317Z

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Observation d762e74b-b39a-4d56-b0e6-dbc4e2842e15 · outbound

This paper cites 2020 , eprint =.

Pretraining EHR Foundation Models with Patient-Aware Sampling 2020 , eprint =

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:42.312402Z

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Observation 7376fb60-ce65-45ea-aa4c-f780de025e64 · outbound

This paper cites Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) , year =.

Pretraining EHR Foundation Models with Patient-Aware Sampling Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) , year =

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:42.365679Z

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Observation c0520f8d-7e31-4988-a3ff-4d9f43dc8f5b · outbound

This paper cites OpenAI Technical Report , year =.

Pretraining EHR Foundation Models with Patient-Aware Sampling OpenAI Technical Report , year =

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:42.447693Z

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Observation 5b0b3379-6c97-4035-ad56-279c0236ef9d · outbound

This paper cites Workshop on Time Series Learning for Health (TS4H) at ICLR , year =.

Pretraining EHR Foundation Models with Patient-Aware Sampling Workshop on Time Series Learning for Health (TS4H) at ICLR , year =

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:42.557603Z

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Observation b811e32c-ad09-4d34-8c56-4fa921c5ba23 · outbound

This paper cites npj Digital Medicine , year =.

Pretraining EHR Foundation Models with Patient-Aware Sampling npj Digital Medicine , year =

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:42.736666Z

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Observation e86f72cf-3283-46f2-87a6-c29752c3cd1c · outbound

This paper cites 2024 , publisher =.

Pretraining EHR Foundation Models with Patient-Aware Sampling 2024 , publisher =

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:42.912815Z

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Observation b7331759-7a62-4109-a171-0602f83d0f1c · outbound

This paper cites 2023 , publisher =.

Pretraining EHR Foundation Models with Patient-Aware Sampling 2023 , publisher =

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:43.056597Z

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Observation eac1bcde-babd-44d2-88f6-ce0063507dc4 · outbound

This paper cites Circulation , year =.

Pretraining EHR Foundation Models with Patient-Aware Sampling Circulation , year =

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:43.193459Z

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Observation 0a55a9c1-3afe-46da-a5f4-e53b771ac2a1 · outbound

This paper cites Advances in neural information processing systems , volume=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Advances in neural information processing systems , volume=

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:43.239483Z

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Observation e6d8bcb3-255c-4e4a-afc1-ec0032be3ad1 · outbound

This paper cites JAMIA open , volume=.

Pretraining EHR Foundation Models with Patient-Aware Sampling JAMIA open , volume=

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:43.297064Z

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Observation 0cd4df30-89e2-4ed2-875a-de4b77c77f8b · outbound

This paper cites Sensing Cardiac Health Across Scenarios and Devices: A Multi-Modal Foundation Model Pretrained on Heterogeneous Data from 1.7 Million Individuals.

Pretraining EHR Foundation Models with Patient-Aware Sampling Sensing Cardiac Health Across Scenarios and Devices: A Multi-Modal Foundation Model Pretrained on Heterogeneous Data from 1.7 Million Individuals

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:43.373409Z

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Observation 1bf02397-bec4-4833-a46c-9de963e97b31 · outbound

This paper cites Nature medicine , volume=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Nature medicine , volume=

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:43.430909Z

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Observation b7c26e34-1b8b-463c-9c7b-c55ff577b655 · outbound

This paper cites Journal of biomedical informatics , volume=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Journal of biomedical informatics , volume=

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:43.514042Z

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Observation b2a925e8-a909-458a-ba59-b74e2318c477 · outbound

This paper cites Heliyon , volume=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Heliyon , volume=

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:43.599914Z

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Observation 97f79e58-4e25-4cf3-872e-ce66c4a8dc75 · outbound

This paper cites Journal of the American Medical Informatics Association , volume=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Journal of the American Medical Informatics Association , volume=

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:43.660172Z

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Observation edf70e17-c533-49ca-a897-385f3e0857c3 · outbound

This paper cites MedPatch: Confidence-Guided Multi-Stage Fusion for Multimodal Clinical Data.

Pretraining EHR Foundation Models with Patient-Aware Sampling MedPatch: Confidence-Guided Multi-Stage Fusion for Multimodal Clinical Data

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:43.683750Z

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Observation e40051d9-cd2c-4e25-9527-5b2a28eb3b5d · outbound

This paper cites Authorea Preprints , year=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Authorea Preprints , year=

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:43.701701Z

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Observation ed86bcd3-88b5-421d-be4d-75a46417eaf3 · outbound

This paper cites Machine Learning for Health , pages=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Machine Learning for Health , pages=

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:43.789519Z

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Observation b5f11cba-76e5-4cb6-84d7-51aa6beb298c · outbound

This paper cites Artificial Intelligence in Medicine , volume=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Artificial Intelligence in Medicine , volume=

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:43.905780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 850a473c-f119-4170-85a3-888ffa8fa615 · outbound

This paper cites Briefings in bioinformatics , volume=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Briefings in bioinformatics , volume=

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:44.005855Z

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Observation 5ea6e2b5-4713-4b23-b2d9-09ac525c0343 · outbound

This paper cites Scientific Reports , volume=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Scientific Reports , volume=

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:44.100514Z

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Observation 769de07e-255c-4a59-9e1f-0daa6cceda19 · outbound

This paper cites Modality-Agnostic Input Channels Enable Segmentation of Brain lesions in Multimodal MRI with Sequences Unavailable During Training.

Pretraining EHR Foundation Models with Patient-Aware Sampling Modality-Agnostic Input Channels Enable Segmentation of Brain lesions in Multimodal MRI with Sequences Unavailable During Training

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:44.204404Z

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Observation af441626-561c-43fd-972b-d72b3c40b3c2 · outbound

This paper cites Machine Learning for Health (ML4H) , pages=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Machine Learning for Health (ML4H) , pages=

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:44.305008Z

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Observation c5590589-21e8-4d59-9f3a-978ecb151fe8 · outbound

This paper cites Nejm Ai , volume=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Nejm Ai , volume=

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:44.394769Z

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Observation ff4ac864-1752-4430-93a0-5adab7be994f · outbound

This paper cites arXiv preprint arXiv:2510.23639 , year=.

Pretraining EHR Foundation Models with Patient-Aware Sampling arXiv preprint arXiv:2510.23639 , year=

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:44.499076Z

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Observation 41d9712d-3c4d-4144-a8f2-54a81fe8bea9 · outbound

This paper cites Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning.

Pretraining EHR Foundation Models with Patient-Aware Sampling Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:44.603301Z

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Observation 7da7f2b2-1566-4a80-8cfb-e9f8d8028d72 · outbound

This paper cites Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML.

Pretraining EHR Foundation Models with Patient-Aware Sampling Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:44.683998Z

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Observation c8e00d72-fa57-4b56-8a8f-a7218bce930a · outbound

This paper cites Scientific reports , volume=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Scientific reports , volume=

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:44.742321Z

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Observation 163c65ad-40f6-48dd-9f3e-9782eeb04fa9 · outbound

This paper cites arXiv preprint arXiv:2508.12104 , year=.

Pretraining EHR Foundation Models with Patient-Aware Sampling arXiv preprint arXiv:2508.12104 , year=

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:44.813911Z

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Observation 269f625a-4752-4f2f-bfa4-4d8db1ea739c · outbound

This paper cites Exploring Scaling Laws for EHR Foundation Models.

Pretraining EHR Foundation Models with Patient-Aware Sampling Exploring Scaling Laws for EHR Foundation Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:44.887446Z

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Observation 2f0187fe-839f-43d5-a5a6-ad10171e5ed6 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Pretraining EHR Foundation Models with Patient-Aware Sampling Advances in Neural Information Processing Systems , volume=

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:44.959793Z

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Observation d9f627df-5a0a-478f-99be-cac92036fb2d · outbound

This paper cites Foresight&.

Pretraining EHR Foundation Models with Patient-Aware Sampling Foresight&

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:45.034730Z

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Observation adeb6257-bf86-4523-bc4a-98762571790d · outbound

This paper cites 2025 , eprint=.

Pretraining EHR Foundation Models with Patient-Aware Sampling 2025 , eprint=

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:45.106694Z

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Observation ee97cd08-1846-4379-a760-2f58748faa11 · outbound

This paper cites GigaScience , volume =.

Pretraining EHR Foundation Models with Patient-Aware Sampling GigaScience , volume =

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:45.190132Z

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Observation e6524697-615a-4092-804f-366faea49d52 · outbound

This paper cites 2023 , month = jan, note =.

Pretraining EHR Foundation Models with Patient-Aware Sampling 2023 , month = jan, note =

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:45.237651Z

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Observation 3236ed2f-18ee-4941-8ee1-de802726c155 · outbound

This paper cites The Twelfth International Conference on Learning Representations , year=.

Pretraining EHR Foundation Models with Patient-Aware Sampling The Twelfth International Conference on Learning Representations , year=

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-01T05:46:45.328304Z

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Pith citing papers

No inbound Pith citation observations are available.