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Paper Citation Record · LEDGER

Improving Myocardial Infarction Detection via Synthetic ECG Pretraining

As of 10 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2506.23259.

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

pith.paper-citation-record.v1
2506.23259 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:50:25.628652Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

13 of 13 outbound references displayed

  • verified exact2
  • verified fuzzy2
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 90c4b3e3-85b0-4bc8-8919-6da5bf908c8e · outbound

This paper cites Deep learning for ecg arrhythmia detection and classification: an overview of progress for period 2017--2023.

Improving Myocardial Infarction Detection via Synthetic ECG Pretraining Deep learning for ecg arrhythmia detection and classification: an overview of progress for period 2017--2023

Reference 1

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T21:50:26.873187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T21:50:24.456873Z digest=sha256:2117dafbc8ccd685c3b117b207cbbc70728c828ed050b303297c66d997891ace

Observation f84ab8c6-7fd1-41f5-bc84-41c8772a3a9c · outbound

This paper cites Generative adversarial networks in electrocardiogram synthesis: Recent developments and challenges.

Improving Myocardial Infarction Detection via Synthetic ECG Pretraining Generative adversarial networks in electrocardiogram synthesis: Recent developments and challenges

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T21:50:24.547365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:50:24.547365Z digest=sha256:19f939536229fb32ac4b1ea809988b7c8fc74a1ad628bfed6ea83a3d4b6d6f1b

Observation 34f82be7-22a3-4e4e-a891-7ba124ae9380 · outbound

This paper cites Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

Improving Myocardial Infarction Detection via Synthetic ECG Pretraining Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T21:50:24.628087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:50:24.628087Z digest=sha256:8c18fa5693367533963fd05f2afb59b4f17af68f7a4834cf66860701888acfbb

Observation 151f4a2f-4a60-43be-81e9-813d32cae46d · outbound

This paper cites J., Brammer, J.

Improving Myocardial Infarction Detection via Synthetic ECG Pretraining J., Brammer, J

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T21:50:24.762588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:50:24.762588Z digest=sha256:2d0081871f7be5979bc9cc30f2fea4fbf2404a72feb8281f12076e4d8abafd5d

Observation 3fa560dd-7ddd-4020-a7f0-ab3e349de0f2 · outbound

This paper cites E., Clifford, G.

Improving Myocardial Infarction Detection via Synthetic ECG Pretraining E., Clifford, G

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:50:27.164561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T21:50:24.845435Z digest=sha256:6507a4356ad16ea7eb533f9865681ff2ec45edc94069783c88de89ed2f812074

Observation f2710c43-ef4f-47e2-87e3-474d63a7c6ec · outbound

This paper cites In silico evaluation of cell therapy in acute versus chronic infarction.

Improving Myocardial Infarction Detection via Synthetic ECG Pretraining In silico evaluation of cell therapy in acute versus chronic infarction

Reference 6

Resolution
verified exact
doi, observed 2026-08-06T21:50:26.103719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T21:50:24.990732Z digest=sha256:54cee12ca3a94de86220ba5d3cd785da51aef3d02e8208d2e66983b2f3d38f26

Observation f853e7ae-4e19-49d1-92d0-1ed230f37039 · outbound

This paper cites Applying masked autoencoder-based self-supervised learning for high-capability vision transformers of electrocardiographies.

Improving Myocardial Infarction Detection via Synthetic ECG Pretraining Applying masked autoencoder-based self-supervised learning for high-capability vision transformers of electrocardiographies

Reference 7

Resolution
verified exact
doi, observed 2026-08-06T21:50:25.886453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T21:50:25.086463Z digest=sha256:6700db47e23d24e0f6ea024bb85fb2801ea7a5ea647ff40779215e31c9f13737

Observation 6b89e743-45cc-4616-b215-4563a055c174 · outbound

This paper cites Deep learning for ecg analysis: Benchmarks and insights from ptb-xl.

Improving Myocardial Infarction Detection via Synthetic ECG Pretraining Deep learning for ecg analysis: Benchmarks and insights from ptb-xl

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T21:50:25.158496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:50:25.158496Z digest=sha256:f193d3fc9cb3460f6c0fbfa0e6c32978f89d930bfd08267e1e673043dc4652d6

Observation aebeeee5-9012-4cb8-a85d-531c4fe73fe3 · outbound

This paper cites A multi-lead group network for myocardial infarction detection and localization based on clinical knowledge-driven and dynamic-static feature fusion.

Improving Myocardial Infarction Detection via Synthetic ECG Pretraining A multi-lead group network for myocardial infarction detection and localization based on clinical knowledge-driven and dynamic-static feature fusion

Reference 9

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T21:50:26.448429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T21:50:25.267994Z digest=sha256:9e1a5c3db632c00eb8a057948878a039470109fbfa3db21aa72a9aa64109d58b

Observation 224c42e1-8100-4596-9296-0eb20a1159f8 · outbound

This paper cites N., Kaiser, ., and Polosukhin, I.

Improving Myocardial Infarction Detection via Synthetic ECG Pretraining N., Kaiser, ., and Polosukhin, I

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T21:50:25.360825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:50:25.360825Z digest=sha256:749d0af7d356fffd49811ffef56e527dee7544996fcd81e6131a8c5f0cac348e

Observation 63ab0f4a-3659-4a0d-8744-5909fbd75f88 · outbound

This paper cites I., Samek, W., and Schaeffter, T.

Improving Myocardial Infarction Detection via Synthetic ECG Pretraining I., Samek, W., and Schaeffter, T

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:50:27.008031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T21:50:25.458975Z digest=sha256:48e4e356d82dd04031e1efdb6336322c283bdb16394586e5fb51fa7832a8bc8d

Observation d41fa7ac-47d9-475d-ab90-65c85093e519 · outbound

This paper cites Masked Transformer for Electrocardiogram Classification.

Improving Myocardial Infarction Detection via Synthetic ECG Pretraining Masked Transformer for Electrocardiogram Classification

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T21:50:25.542613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:50:25.542613Z digest=sha256:0f40913d025fb480940162ea9e5bd777e50da4bc8cb2aa5b39e1f64656adeabf

Observation fa68ff0d-c8d8-4944-84b6-acd1dfa4360a · outbound

This paper cites write newline.

Improving Myocardial Infarction Detection via Synthetic ECG Pretraining write newline

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T21:50:25.628652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:50:25.628652Z digest=sha256:26357a5c459d4452f9ccc0d37d4f2eb2ce64a4268220262ec7352b79b5bad7e6

Pith citing papers

No inbound Pith citation observations are available.