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Paper Citation Record · LEDGER

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models

As of 10 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2507.14151.

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

pith.paper-citation-record.v1
2507.14151 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:22:22.664824Z

measured 43 of 43 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:45:50.426049Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T14:45:51.226465Z

Reference resolution

42 of 42 outbound references displayed

  • verified exact7
  • verified fuzzy12
  • unresolved22
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 121d2ad3-229c-4cc6-9144-fdbe5d783557 · outbound

This paper cites Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-06T20:22:27.221115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 6e0f1616-a2bc-4d6e-8995-992839d2c3df · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 2

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no resolver link, observed 2026-08-06T20:22:18.987577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:18.987577Z digest=sha256:1c7531fd14f3ba35129c71b6c67f411c32f0f051aec5d0c6a270a0d130992c4c

Observation ec2bcde7-b832-4e38-a1db-c8e801473e1e · outbound

This paper cites Language Models are Few-Shot Learners.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Language Models are Few-Shot Learners

Reference 3

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no resolver link, observed 2026-08-06T20:22:19.060778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:19.060778Z digest=sha256:5cde46e6c9752b1ce8724bdeca075d3dc8c95cef3f11d4f210c7448255d5b97d

Observation 070f7dd6-7795-41ef-bbbf-f6c678083fda · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Learning Transferable Visual Models From Natural Language Supervision

Reference 4

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no resolver link, observed 2026-08-06T20:22:19.148990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:19.148990Z digest=sha256:18f8066fdec954feff0ec34eb280bbde3d61f3428d84cd5e2353d68e62e72f95

Observation 61780195-02e9-4233-9fb5-b8420d51c583 · outbound

This paper cites wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations

Reference 5

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no resolver link, observed 2026-08-06T20:22:19.222932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:19.222932Z digest=sha256:4665ff865564fc80d3aa98e5bca0be5d817bc259c2fdde25967365c410447828

Observation 900ab6b0-c280-4567-b53a-7efcc73b6655 · outbound

This paper cites Hubert: Self-supervised speech representation learning by masked prediction of hidden units.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Hubert: Self-supervised speech representation learning by masked prediction of hidden units

Reference 6

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no resolver link, observed 2026-08-06T20:22:19.262646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:19.262646Z digest=sha256:35d6774a5f6fd58e7b4b2767e22673a0f20e9402935c3e5896c9a2fca6c656aa

Observation 0befb845-5747-45eb-bb75-68260d04cae2 · outbound

This paper cites Sleepfm: Multi-modal representation learning for sleep across brain activity, ecg and respiratory signals.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Sleepfm: Multi-modal representation learning for sleep across brain activity, ecg and respiratory signals

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-06T20:22:26.991955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:19.331287Z digest=sha256:241e3c1ca5161a3870911c2422aa2d83a695ef2d418351e17f8f5b951822411b

Observation dfc995f4-3289-417e-a526-36d23003b1bb · outbound

This paper cites Nadkarni.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Nadkarni

Reference 8

Resolution
verified exact
doi, observed 2026-08-06T20:22:23.731654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:19.469570Z digest=sha256:9d71902a2156a518982b9f9672f7e6b36d318fe89ceddd8d33f14980a12be232

Observation c8836832-2ffe-492d-bc85-5dd58272b966 · outbound

This paper cites Applications of self-supervised learning to biomedical signals: A survey.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Applications of self-supervised learning to biomedical signals: A survey

Reference 9

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malformed identifier
raw_fallback, observed 2026-08-06T20:22:24.805364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:19.543623Z digest=sha256:9a36f26f667bd97d7dc76624f6793132880d8fa6824764352193a008daffde22

Observation 748b28d2-a0d6-4348-9498-49c9f2b9314e · outbound

This paper cites Foundation models in electrocardiogram: A review, 2024.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Foundation models in electrocardiogram: A review, 2024

Reference 10

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no resolver link, observed 2026-08-06T20:22:19.595057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:19.595057Z digest=sha256:c33f866eb3147e6ee7ee4ade0fbba2a1ffe0b2ed228d4ff4d2271535884eb531

Observation 4e8fa117-ac25-408e-a2f7-05accac03c12 · outbound

This paper cites ECG-FM: An Open Electrocardiogram Foundation Model.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models ECG-FM: An Open Electrocardiogram Foundation Model

Reference 11

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no resolver link, observed 2026-08-06T20:22:19.654371Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:19.654371Z digest=sha256:fba194f9f35b2df503481525c8faa1c97f590c7133d75b57b9730c9aec496792

Observation 197fa460-3ec8-4f59-bd9a-92e1736734e4 · outbound

This paper cites Large-scale Training of Foundation Models for Wearable Biosignals.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Large-scale Training of Foundation Models for Wearable Biosignals

Reference 12

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no resolver link, observed 2026-08-06T20:22:19.702906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:19.702906Z digest=sha256:b696855ea1bae2ce8ffe757cf789b9ecc4431be42550262f38cdb0153d8eda64

Observation ee32901a-9977-4f3e-8144-59bb757e34e7 · outbound

This paper cites Ecg semantic integrator (esi): A foundation ecg model pretrained with llm-enhanced cardiological text, 2024.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Ecg semantic integrator (esi): A foundation ecg model pretrained with llm-enhanced cardiological text, 2024

Reference 13

Resolution
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raw_fallback, observed 2026-08-06T20:22:26.793043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:19.762872Z digest=sha256:53c16c160b150f2725f261c09f771cb39e693f4e45e010a650191bd6ab78d27f

Observation 12094c11-fae8-4850-b240-abfee1983afe · outbound

This paper cites Foundation mod- els for cardiovascular disease detection via biosignals from digital stethoscopes.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Foundation mod- els for cardiovascular disease detection via biosignals from digital stethoscopes

Reference 14

Resolution
verified exact
doi, observed 2026-08-06T20:22:23.555155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:19.832148Z digest=sha256:d33fa9a3ff7f210eba3e9816e5e444c250c4ac7161cbd72d455f58c06c758108

Observation af001199-8d83-4dd6-b400-4242d29bd0c3 · outbound

This paper cites Remote and wearable ecg devices with diagnostic abilities in adults: a state-of-the-science scoping review.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Remote and wearable ecg devices with diagnostic abilities in adults: a state-of-the-science scoping review

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:22:26.657400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:19.904400Z digest=sha256:57425b4ff436a45a04498377eb6bf3ed0251f4c796794f8ab111c14dd5a4f104

Observation 745339a9-d2f5-4717-af21-77b45c0f2cb3 · outbound

This paper cites 3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models 3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations

Reference 16

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verified exact
local_arxiv, observed 2026-08-06T20:22:24.449912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:20.007607Z digest=sha256:acb0d8259003e1ef1b3b1c541d57b9e1800b7a1d6628bd148c4964e517870657

Observation 72e248de-35fc-40cd-8218-a23a1d8729e2 · outbound

This paper cites Dense lead contrast for self-supervised representation learning of multilead electrocardiograms.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Dense lead contrast for self-supervised representation learning of multilead electrocardiograms

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:20.110489Z digest=sha256:f4a21b1193c0ebfd200fc098359b36290cc18e6955571355c43fad82289a62d7

Observation a2bf97f9-28b4-4b9f-b81d-837c308d2ddd · outbound

This paper cites Lead-agnostic self- supervised learning for local and global representations of electrocardiogram.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Lead-agnostic self- supervised learning for local and global representations of electrocardiogram

Reference 18

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verified fuzzy
raw_fallback, observed 2026-08-06T20:22:26.471187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:20.199617Z digest=sha256:fd958428ae99a3fd3938e26e91ceddfd8f21d7afb7d9f9d4f0c82388aaeb4fe6

Observation 06b40af1-517c-47ac-b2b5-e80bdebb7148 · outbound

This paper cites Clegg, Andrea Cavallaro, and Hamed Haddadi.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Clegg, Andrea Cavallaro, and Hamed Haddadi

Reference 19

Resolution
verified exact
doi, observed 2026-08-06T20:22:23.413180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:20.263152Z digest=sha256:8a4487412609dfb40b2a2d30a5dcf80a36b13a237988e57ac62c90368129248b

Observation 517e46fc-830f-48c0-85b5-67cf4aff0161 · outbound

This paper cites An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 20

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no resolver link, observed 2026-08-06T20:22:20.328751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:20.328751Z digest=sha256:26c7755d615dda54643f389bcb2e0fb241ba9fbcdc7d7400a114f4a5b090f0ce

Observation ebd6829d-7669-4ff5-b174-44ae459e82fb · outbound

This paper cites Biot: Biosignal transformer for cross-data learning in the wild.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Biot: Biosignal transformer for cross-data learning in the wild

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-06T20:22:26.271296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:20.414680Z digest=sha256:f08115e5811b935c77388441e1984cb995b1bae2ba5462be3ede58ad0fcc0e42

Observation 67c00434-7d4b-42bd-90bb-099d083d2708 · outbound

This paper cites Will two do? varying dimensions in electrocardiography: The physionet/computing in cardiology challenge 2021.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Will two do? varying dimensions in electrocardiography: The physionet/computing in cardiology challenge 2021

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-06T20:22:26.089348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:20.473534Z digest=sha256:d85daaae229a6e7af6d3bfb8cea235a7f43eb7ec256194d2f8342289df8bbc05

Observation 5858e40e-ba34-4677-9b40-0a30905c97f8 · outbound

This paper cites Issues in the automated classification of multilead ecgs using heterogeneous labels and populations.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Issues in the automated classification of multilead ecgs using heterogeneous labels and populations

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-06T20:22:25.932092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:20.559276Z digest=sha256:ea883e08f9b676a7ecba0dc29217129d2602a427585e645a05d8e14f68a6f6d8

Observation b69bdb9a-4d05-4bb7-b3a2-14b5b807bdd1 · outbound

This paper cites A Simple Framework for Contrastive Learning of Visual Representations.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models A Simple Framework for Contrastive Learning of Visual Representations

Reference 24

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no resolver link, observed 2026-08-06T20:22:20.655345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:20.655345Z digest=sha256:5dc20e3d5e0088ff18cdcc99b9a1c120f36f95a138420a2d25726f5de2f79e0c

Observation f675f68c-78a1-4d6c-9ac0-0f585e22b310 · outbound

This paper cites Ribeiro, Manoel Horta Ribeiro, Gabriela M.M.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Ribeiro, Manoel Horta Ribeiro, Gabriela M.M

Reference 25

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unresolved
no resolver link, observed 2026-08-06T20:22:20.741826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:20.741826Z digest=sha256:b7715344ae2dffbb92dc25185315d562fb71a4eb7dba2aa4b4c02459751dfe9a

Observation 9a31b130-f8a8-4a90-ac98-d274dd93a762 · outbound

This paper cites Ribeiro, Gabriela M.M.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Ribeiro, Gabriela M.M

Reference 26

Resolution
verified exact
raw_fallback, observed 2026-08-06T20:22:24.241199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:20.814134Z digest=sha256:3872e8536cde8c9edbbd15e87f81545d5675260b4144c027535af4168432b3ca

Observation 47deab23-c0df-4521-9d34-56fe1df55afe · outbound

This paper cites Practical intelligent diagnostic algorithm for wearable 12-lead ecg via self- supervised learning on large-scale dataset.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Practical intelligent diagnostic algorithm for wearable 12-lead ecg via self- supervised learning on large-scale dataset

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:22:25.746363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:20.861152Z digest=sha256:2057f64203d8b47c504770c0bda62b70b13401c47083a2280d33ef418d0fc61c

Observation 2dd90054-3da3-4748-bdad-ee40cd384cf4 · outbound

This paper cites URL https://www.scidb.cn/en/ detail?dataSetId=58c4a92d5a01414390a78160d335380d.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models URL https://www.scidb.cn/en/ detail?dataSetId=58c4a92d5a01414390a78160d335380d

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-06T20:22:25.603586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:21.040077Z digest=sha256:2ca4ac3367380dce230b52283f3d93457c201658ced16aa0da9737bf6f4b4725

Observation 41632596-d2aa-4635-871a-a42b6b8d6ea7 · outbound

This paper cites an unresolved cited work.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Unresolved cited work

Reference 29

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no resolver link, observed 2026-08-06T20:22:21.159706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:21.159706Z digest=sha256:e0e6fdad10e7ac8ececeda7ca780cfc1d27d9ab6e6bcf5129c11aa73f24aecdb

Observation 92747d24-79c4-4182-93e5-671e778b7d01 · outbound

This paper cites Will two do? varying dimensions in electrocardiography: The physionet/computing in cardiology challenge 2021.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Will two do? varying dimensions in electrocardiography: The physionet/computing in cardiology challenge 2021

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:22:25.434145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:21.301537Z digest=sha256:e33ff6b499c231a01b3b069bf9aa28af3fe0f7d165639eab67b4c772e1e9f144

Observation 35f7e30a-cf5a-420d-a9d6-0fb73f85ce33 · outbound

This paper cites Optimal multi-stage arrhythmia classification approach.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Optimal multi-stage arrhythmia classification approach

Reference 31

Resolution
verified exact
doi, observed 2026-08-06T20:22:23.175715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:22:21.446978Z digest=sha256:8a34bfe7c1bd0a0b4b952775d72f10729e77b4a7040a7262f06247d1b3db9597

Observation 3ba7193a-88d0-4153-a43f-f46f3e38b6d5 · outbound

This paper cites A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients

Reference 32

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unresolved
no resolver link, observed 2026-08-06T20:22:21.607309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:21.607309Z digest=sha256:e729babe38c31e4b370f48c61e4f647f33a8f04044f0b9032006fd6446f3a915

Observation 54697ebc-1f33-4a3b-8a9e-54dd9a6908b4 · outbound

This paper cites An open access database for evaluating the algorithms of electrocardiogram rhythm and morphology abnormality detection.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models An open access database for evaluating the algorithms of electrocardiogram rhythm and morphology abnormality detection

Reference 33

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unresolved
no resolver link, observed 2026-08-06T20:22:21.744198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 61fa6a11-47e1-4ec8-aa86-64cb4697d62f · outbound

This paper cites Classification of ecg using ensemble of residual cnns with attention mechanism.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Classification of ecg using ensemble of residual cnns with attention mechanism

Reference 34

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This paper cites Analysis of augmentations for contrastive ecg representation learning.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Analysis of augmentations for contrastive ecg representation learning

Reference 35

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Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Self-supervised representation learning from 12-lead ecg data

Reference 36

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Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Unresolved cited work

Reference 37

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Observation b6087e89-76b5-4dc3-b583-ff33bdc96345 · outbound

This paper cites Selfeeg: A python library for self-supervised learning in electroencephalog- raphy.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models Selfeeg: A python library for self-supervised learning in electroencephalog- raphy

Reference 38

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Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models GitHub repository, 2023

Reference 39

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This paper cites On the Opportunities and Risks of Foundation Models.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models On the Opportunities and Risks of Foundation Models

Reference 2022

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Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models doi: 10.1038/s41467-023-39472-8

Reference 2023

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Observation ba94c0c8-0182-4dcf-80e5-edb26c5082ae · outbound

This paper cites SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals

Reference 2024

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Pith citing papers

Observation 00123c43-c86f-4837-bcbe-b63add727862 · inbound

LAEF: A Lead-Agnostic ECG Foundation Model Towards Point-of-Care Diagnostics cites this paper.

LAEF: A Lead-Agnostic ECG Foundation Model Towards Point-of-Care Diagnostics Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models

Reference 14

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